WorldWideScience

Sample records for resolution aerial images

  1. Detection of Aspens Using High Resolution Aerial Laser Scanning Data and Digital Aerial Images

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    Kalle Eerikäinen

    2008-08-01

    Full Text Available The aim was to use high resolution Aerial Laser Scanning (ALS data and aerial images to detect European aspen (Populus tremula L. from among other deciduous trees. The field data consisted of 14 sample plots of 30 m × 30 m size located in the Koli National Park in the North Karelia, Eastern Finland. A Canopy Height Model (CHM was interpolated from the ALS data with a pulse density of 3.86/m2, low-pass filtered using Height-Based Filtering (HBF and binarized to create the mask needed to separate the ground pixels from the canopy pixels within individual areas. Watershed segmentation was applied to the low-pass filtered CHM in order to create preliminary canopy segments, from which the non-canopy elements were extracted to obtain the final canopy segmentation, i.e. the ground mask was analysed against the canopy mask. A manual classification of aerial images was employed to separate the canopy segments of deciduous trees from those of coniferous trees. Finally, linear discriminant analysis was applied to the correctly classified canopy segments of deciduous trees to classify them into segments belonging to aspen and those belonging to other deciduous trees. The independent variables used in the classification were obtained from the first pulse ALS point data. The accuracy of discrimination between aspen and other deciduous trees was 78.6%. The independent variables in the classification function were the proportion of vegetation hits, the standard deviation of in pulse heights, accumulated intensity at the 90th percentile and the proportion of laser points reflected at the 60th height percentile. The accuracy of classification corresponded to the validation results of earlier ALS-based studies on the classification of individual deciduous trees to tree species.

  2. ANALYZING SPECTRAL CHARACTERISTICS OF SHADOW AREA FROM ADS-40 HIGH RADIOMETRIC RESOLUTION AERIAL IMAGES

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    Y.-T. Hsieh

    2016-06-01

    Full Text Available The shadows in optical remote sensing images are regarded as image nuisances in numerous applications. The classification and interpretation of shadow area in a remote sensing image are a challenge, because of the reduction or total loss of spectral information in those areas. In recent years, airborne multispectral aerial image devices have been developed 12-bit or higher radiometric resolution data, including Leica ADS-40, Intergraph DMC. The increased radiometric resolution of digital imagery provides more radiometric details of potential use in classification or interpretation of land cover of shadow areas. Therefore, the objectives of this study are to analyze the spectral properties of the land cover in the shadow areas by ADS-40 high radiometric resolution aerial images, and to investigate the spectral and vegetation index differences between the various shadow and non-shadow land covers. According to research findings of spectral analysis of ADS-40 image: (i The DN values in shadow area are much lower than in nonshadow area; (ii DN values received from shadowed areas that will also be affected by different land cover, and it shows the possibility of land cover property retrieval as in nonshadow area; (iii The DN values received from shadowed regions decrease in the visible band from short to long wavelengths due to scattering; (iv The shadow area NIR of vegetation category also shows a strong reflection; (v Generally, vegetation indexes (NDVI still have utility to classify the vegetation and non-vegetation in shadow area. The spectral data of high radiometric resolution images (ADS-40 is potential for the extract land cover information of shadow areas.

  3. Semantic labeling of high-resolution aerial images using an ensemble of fully convolutional networks

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    Sun, Xiaofeng; Shen, Shuhan; Lin, Xiangguo; Hu, Zhanyi

    2017-10-01

    High-resolution remote sensing data classification has been a challenging and promising research topic in the community of remote sensing. In recent years, with the rapid advances of deep learning, remarkable progress has been made in this field, which facilitates a transition from hand-crafted features designing to an automatic end-to-end learning. A deep fully convolutional networks (FCNs) based ensemble learning method is proposed to label the high-resolution aerial images. To fully tap the potentials of FCNs, both the Visual Geometry Group network and a deeper residual network, ResNet, are employed. Furthermore, to enlarge training samples with diversity and gain better generalization, in addition to the commonly used data augmentation methods (e.g., rotation, multiscale, and aspect ratio) in the literature, aerial images from other datasets are also collected for cross-scene learning. Finally, we combine these learned models to form an effective FCN ensemble and refine the results using a fully connected conditional random field graph model. Experiments on the ISPRS 2-D Semantic Labeling Contest dataset show that our proposed end-to-end classification method achieves an overall accuracy of 90.7%, a state-of-the-art in the field.

  4. Low-resolution ship detection from high-altitude aerial images

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    Qi, Shengxiang; Wu, Jianmin; Zhou, Qing; Kang, Minyang

    2018-02-01

    Ship detection from optical images taken by high-altitude aircrafts such as unmanned long-endurance airships and unmanned aerial vehicles has broad applications in marine fishery management, ship monitoring and vessel salvage. However, the major challenge is the limited capability of information processing on unmanned high-altitude platforms. Furthermore, in order to guarantee the wide detection range, unmanned aircrafts generally cruise at high altitudes, resulting in imagery with low-resolution targets and strong clutters suffered by heavy clouds. In this paper, we propose a low-resolution ship detection method to extract ships from these high-altitude optical images. Inspired by a recent research on visual saliency detection indicating that small salient signals could be well detected by a gradient enhancement operation combined with Gaussian smoothing, we propose the facet kernel filtering to rapidly suppress cluttered backgrounds and delineate candidate target regions from the sea surface. Then, the principal component analysis (PCA) is used to compute the orientation of the target axis, followed by a simplified histogram of oriented gradient (HOG) descriptor to characterize the ship shape property. Finally, support vector machine (SVM) is applied to discriminate real targets and false alarms. Experimental results show that the proposed method actually has high efficiency in low-resolution ship detection.

  5. A New Approach to Urban Road Extraction Using High-Resolution Aerial Image

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    Jianhua Wang

    2016-07-01

    Full Text Available Road information is fundamental not only in the military field but also common daily living. Automatic road extraction from a remote sensing images can provide references for city planning as well as transportation database and map updating. However, owing to the spectral similarity between roads and impervious structures, the current methods solely using spectral characteristics are often ineffective. By contrast, the detailed information discernible from the high-resolution aerial images enables road extraction with spatial texture features. In this study, a knowledge-based method is established and proposed; this method incorporates the spatial texture feature into urban road extraction. The spatial texture feature is initially extracted by the local Moran’s I, and the derived texture is added to the spectral bands of image for image segmentation. Subsequently, features like brightness, standard deviation, rectangularity, aspect ratio, and area are selected to form the hypothesis and verification model based on road knowledge. Finally, roads are extracted by applying the hypothesis and verification model and are post-processed based on the mathematical morphology. The newly proposed method is evaluated by conducting two experiments. Results show that the completeness, correctness, and quality of the results could reach approximately 94%, 90% and 86% respectively, indicating that the proposed method is effective for urban road extraction.

  6. Random Access Memories: A New Paradigm for Target Detection in High Resolution Aerial Remote Sensing Images.

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    Zou, Zhengxia; Shi, Zhenwei

    2018-03-01

    We propose a new paradigm for target detection in high resolution aerial remote sensing images under small target priors. Previous remote sensing target detection methods frame the detection as learning of detection model + inference of class-label and bounding-box coordinates. Instead, we formulate it from a Bayesian view that at inference stage, the detection model is adaptively updated to maximize its posterior that is determined by both training and observation. We call this paradigm "random access memories (RAM)." In this paradigm, "Memories" can be interpreted as any model distribution learned from training data and "random access" means accessing memories and randomly adjusting the model at detection phase to obtain better adaptivity to any unseen distribution of test data. By leveraging some latest detection techniques e.g., deep Convolutional Neural Networks and multi-scale anchors, experimental results on a public remote sensing target detection data set show our method outperforms several other state of the art methods. We also introduce a new data set "LEarning, VIsion and Remote sensing laboratory (LEVIR)", which is one order of magnitude larger than other data sets of this field. LEVIR consists of a large set of Google Earth images, with over 22 k images and 10 k independently labeled targets. RAM gives noticeable upgrade of accuracy (an mean average precision improvement of 1% ~ 4%) of our baseline detectors with acceptable computational overhead.

  7. Cost-Effective Class-Imbalance Aware CNN for Vehicle Localization and Categorization in High Resolution Aerial Images

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    Feimo Li

    2017-05-01

    Full Text Available Joint vehicle localization and categorization in high resolution aerial images can provide useful information for applications such as traffic flow structure analysis. To maintain sufficient features to recognize small-scaled vehicles, a regions with convolutional neural network features (R-CNN -like detection structure is employed. In this setting, cascaded localization error can be averted by equally treating the negatives and differently typed positives as a multi-class classification task, but the problem of class-imbalance remains. To address this issue, a cost-effective network extension scheme is proposed. In it, the correlated convolution and connection costs during extension are reduced by feature map selection and bi-partite main-side network construction, which are realized with the assistance of a novel feature map class-importance measurement and a new class-imbalance sensitive main-side loss function. By using an image classification dataset established from a set of traditional real-colored aerial images with 0.13 m ground sampling distance which are taken from the height of 1000 m by an imaging system composed of non-metric cameras, the effectiveness of the proposed network extension is verified by comparing with its similarly shaped strong counter-parts. Experiments show an equivalent or better performance, while requiring the least parameter and memory overheads are required.

  8. Individual Building Rooftop and Tree Crown Segmentation from High-Resolution Urban Aerial Optical Images

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    Jichao Jiao

    2016-01-01

    Full Text Available We segment buildings and trees from aerial photographs by using superpixels, and we estimate the tree’s parameters by using a cost function proposed in this paper. A method based on image complexity is proposed to refine superpixels boundaries. In order to classify buildings from ground and classify trees from grass, the salient feature vectors that include colors, Features from Accelerated Segment Test (FAST corners, and Gabor edges are extracted from refined superpixels. The vectors are used to train the classifier based on Naive Bayes classifier. The trained classifier is used to classify refined superpixels as object or nonobject. The properties of a tree, including its locations and radius, are estimated by minimizing the cost function. The shadow is used to calculate the tree height using sun angle and the time when the image was taken. Our segmentation algorithm is compared with other two state-of-the-art segmentation algorithms, and the tree parameters obtained in this paper are compared to the ground truth data. Experiments show that the proposed method can segment trees and buildings appropriately, yielding higher precision and better recall rates, and the tree parameters are in good agreement with the ground truth data.

  9. Land Cover Change Detection in Urban Lake Areas Using Multi-Temporary Very High Spatial Resolution Aerial Images

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    Wenyuan Zhang

    2018-01-01

    Full Text Available The availability of very high spatial resolution (VHR remote sensing imagery provides unique opportunities to exploit meaningful change information in detail with object-oriented image analysis. This study investigated land cover (LC changes in Shahu Lake of Wuhan using multi-temporal VHR aerial images in the years 1978, 1981, 1989, 1995, 2003, and 2011. A multi-resolution segmentation algorithm and CART (classification and regression trees classifier were employed to perform highly accurate LC classification of the individual images, while a post-classification comparison method was used to detect changes. The experiments demonstrated that significant changes in LC occurred along with the rapid urbanization during 1978–2011. The dominant changes that took place in the study area were lake and vegetation shrinking, replaced by high density buildings and roads. The total area of Shahu Lake decreased from ~7.64 km2 to ~3.60 km2 during the past 33 years, where 52.91% of its original area was lost. The presented results also indicated that urban expansion and inadequate legislative protection are the main factors in Shahu Lake’s shrinking. The object-oriented change detection schema presented in this manuscript enables us to better understand the specific spatial changes of Shahu Lake, which can be used to make reasonable decisions for lake protection and urban development.

  10. Generation and Assessment of Urban Land Cover Maps Using High-Resolution Multispectral Aerial Images

    DEFF Research Database (Denmark)

    Höhle, Joachim; Höhle, Michael

    2013-01-01

    a unique method for the automatic generation of urban land cover maps. In the present paper, imagery of a new medium-format aerial camera and advanced geoprocessing software are applied to derive normalized digital surface models and vegetation maps. These two intermediate products then become input...... to a tree structured classifier, which automatically derives land cover maps in 2D or 3D. We investigate the thematic accuracy of the produced land cover map by a class-wise stratified design and provide a method for deriving necessary sample sizes. Corresponding survey adjusted accuracy measures...... and their associated confidence intervals are used to adequately reflect uncertainty in the assessment based on the chosen sample size. Proof of concept for the method is given for an urban area in Switzerland. Here, the produced land cover map with six classes (building, wall and carport, road and parking lot, hedge...

  11. Marker Detection in Aerial Images

    KAUST Repository

    Alharbi, Yazeed

    2017-04-09

    The problem that the thesis is trying to solve is the detection of small markers in high-resolution aerial images. Given a high-resolution image, the goal is to return the pixel coordinates corresponding to the center of the marker in the image. The marker has the shape of two triangles sharing a vertex in the middle, and it occupies no more than 0.01% of the image size. An improvement on the Histogram of Oriented Gradients (HOG) is proposed, eliminating the majority of baseline HOG false positives for marker detection. The improvement is guided by the observation that standard HOG description struggles to separate markers from negatives patches containing an X shape. The proposed method alters intensities with the aim of altering gradients. The intensity-dependent gradient alteration leads to more separation between filled and unfilled shapes. The improvement is used in a two-stage algorithm to achieve high recall and high precision in detection of markers in aerial images. In the first stage, two classifiers are used: one to quickly eliminate most of the uninteresting parts of the image, and one to carefully select the marker among the remaining interesting regions. Interesting regions are selected by scanning the image with a fast classifier trained on the HOG features of markers in all rotations and scales. The next classifier is more precise and uses our method to eliminate the majority of the false positives of standard HOG. In the second stage, detected markers are tracked forward and backward in time. Tracking is needed to detect extremely blurred or distorted markers that are missed by the previous stage. The algorithm achieves 94% recall with minimal user guidance. An average of 30 guesses are given per image; the user verifies for each whether it is a marker or not. The brute force approach would return 100,000 guesses per image.

  12. A geometric stochastic approach based on marked point processes for road mark detection from high resolution aerial images

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    Tournaire, O.; Paparoditis, N.

    Road detection has been a topic of great interest in the photogrammetric and remote sensing communities since the end of the 70s. Many approaches dealing with various sensor resolutions, the nature of the scene or the wished accuracy of the extracted objects have been presented. This topic remains challenging today as the need for accurate and up-to-date data is becoming more and more important. Based on this context, we will study in this paper the road network from a particular point of view, focusing on road marks, and in particular dashed lines. Indeed, they are very useful clues, for evidence of a road, but also for tasks of a higher level. For instance, they can be used to enhance quality and to improve road databases. It is also possible to delineate the different circulation lanes, their width and functionality (speed limit, special lanes for buses or bicycles...). In this paper, we propose a new robust and accurate top-down approach for dashed line detection based on stochastic geometry. Our approach is automatic in the sense that no intervention from a human operator is necessary to initialise the algorithm or to track errors during the process. The core of our approach relies on defining geometric, radiometric and relational models for dashed lines objects. The model also has to deal with the interactions between the different objects making up a line, meaning that it introduces external knowledge taken from specifications. Our strategy is based on a stochastic method, and in particular marked point processes. Our goal is to find the objects configuration minimising an energy function made-up of a data attachment term measuring the consistency of the image with respect to the objects and a regularising term managing the relationship between neighbouring objects. To sample the energy function, we use Green algorithm's; coupled with a simulated annealing to find its minimum. Results from aerial images at various resolutions are presented showing that our

  13. Detection of rice sheath blight using an unmanned aerial system with high-resolution color and multispectral imaging.

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    Zhang, Dongyan; Zhou, Xingen; Zhang, Jian; Lan, Yubin; Xu, Chao; Liang, Dong

    2018-01-01

    Detection and monitoring are the first essential step for effective management of sheath blight (ShB), a major disease in rice worldwide. Unmanned aerial systems have a high potential of being utilized to improve this detection process since they can reduce the time needed for scouting for the disease at a field scale, and are affordable and user-friendly in operation. In this study, a commercialized quadrotor unmanned aerial vehicle (UAV), equipped with digital and multispectral cameras, was used to capture imagery data of research plots with 67 rice cultivars and elite lines. Collected imagery data were then processed and analyzed to characterize the development of ShB and quantify different levels of the disease in the field. Through color features extraction and color space transformation of images, it was found that the color transformation could qualitatively detect the infected areas of ShB in the field plots. However, it was less effective to detect different levels of the disease. Five vegetation indices were then calculated from the multispectral images, and ground truths of disease severity and GreenSeeker measured NDVI (Normalized Difference Vegetation Index) were collected. The results of relationship analyses indicate that there was a strong correlation between ground-measured NDVIs and image-extracted NDVIs with the R2 of 0.907 and the root mean square error (RMSE) of 0.0854, and a good correlation between image-extracted NDVIs and disease severity with the R2 of 0.627 and the RMSE of 0.0852. Use of image-based NDVIs extracted from multispectral images could quantify different levels of ShB in the field plots with an accuracy of 63%. These results demonstrate that a customer-grade UAV integrated with digital and multispectral cameras can be an effective tool to detect the ShB disease at a field scale.

  14. COMPARATIVE ASSESSMENT OF VERY HIGH RESOLUTION SATELLITE AND AERIAL ORTHOIMAGERY

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    P. Agrafiotis

    2015-03-01

    Full Text Available This paper aims to assess the accuracy and radiometric quality of orthorectified high resolution satellite imagery from Pleiades-1B satellites through a comparative evaluation of their quantitative and qualitative properties. A Pleiades-B1 stereopair of high resolution images taken in 2013, two adjacent GeoEye-1 stereopairs from 2011 and aerial orthomosaic (LSO provided by NCMA S.A (Hellenic Cadastre from 2007 have been used for the comparison tests. As control dataset orthomosaic from aerial imagery provided also by NCMA S.A (0.25m GSD from 2012 was selected. The process for DSM and orthoimage production was performed using commercial digital photogrammetric workstations. The two resulting orthoimages and the aerial orthomosaic (LSO were relatively and absolutely evaluated for their quantitative and qualitative properties. Test measurements were performed using the same check points in order to establish their accuracy both as far as the single point coordinates as well as their distances are concerned. Check points were distributed according to JRC Guidelines for Best Practice and Quality Checking of Ortho Imagery and NSSDA standards while areas with different terrain relief and land cover were also included. The tests performed were based also on JRC and NSSDA accuracy standards. Finally, tests were carried out in order to assess the radiometric quality of the orthoimagery. The results are presented with a statistical analysis and they are evaluated in order to present the merits and demerits of the imaging sensors involved for orthoimage production. The results also serve for a critical approach for the usability and cost efficiency of satellite imagery for the production of Large Scale Orthophotos.

  15. A Simple Aerial Photogrammetric Mapping System Overview and Image Acquisition Using Unmanned Aerial Vehicles (UAVs

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    Wenang Anurogo

    2017-06-01

    Full Text Available Aerial photogrammetry is one of the Alternative technologies for more detailed data, real time, fast and cheaper. Nowadays, many photogrammetric mapping methods have used UAV / unmanned drones or drones to retrieve and record data from an object in the earth. The application of drones in the field of geospatial science today is in great demand because of its relatively easy operation and relatively affordable cost compared to satellite systems especially high - resolution satellite imagery.  This research aims to determine the stage or overview of data retrieval process with DJI Phantom 4 (multi - rotor quad - copter drone with processing using third party software. This research also produces 2 - dimensional high resolution image data on the research area. Utilization of third party software (Agisoft PhotoScan making it easier to acquire and process aerial photogrammetric data. The results of aerial photogrammetric recording with a flying altitude of 70 meters obtained high resolution images with a spatial resolution of 2 inches / pixels.

  16. High Resolution Urban Land Cover Mapping Using NAIP Aerial Photography and Image Processing for the USEPA National Atlas of Sustainability and Ecosystem Services

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    Pilant, A. N.; Baynes, J.; Dannenberg, M.

    2012-12-01

    The US EPA National Atlas for Sustainability is a web-based, easy-to-use, mapping application that allows users to view and analyze multiple ecosystem services in a specific region. The Atlas provides users with a visual method for interpreting ecosystem services and understanding how they can be conserved and enhanced for a sustainable future. The Urban Atlas component of the National Atlas will provide fine-scale information linking human health and well-being to environmental conditions such as urban heat islands, near-road pollution, resource use, access to recreation, drinking water quality and other quality of life indicators. The National Land Cover Data (NLCD) derived from 30 m scale 2006 Landsat imagery provides the land cover base for the Atlas. However, urban features and phenomena occur at finer spatial scales, so higher spatial resolution and more current LC maps are required. We used 4 band USDA NAIP imagery (1 m pixel size) and various classification approaches to produce urban land cover maps with these classes: impervious surface, grass and herbaceous, trees and forest, soil and barren, and water. Here we present the remote sensing methods used and results from four pilot cities in this effort, highlighting the pros and cons of the approach, and the benefits to sustainability and ecosystem services analysis. Example of high resolution land cover map derived from USDA NAIP aerial photo. Compare 30 m and 1 m resolution land cover maps of downtown Durham, NC.

  17. Disaster damage detection through synergistic use of deep learning and 3D point cloud features derived from very high resolution oblique aerial images, and multiple-kernel-learning

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    Vetrivel, Anand; Gerke, Markus; Kerle, Norman; Nex, Francesco; Vosselman, George

    2018-06-01

    Oblique aerial images offer views of both building roofs and façades, and thus have been recognized as a potential source to detect severe building damages caused by destructive disaster events such as earthquakes. Therefore, they represent an important source of information for first responders or other stakeholders involved in the post-disaster response process. Several automated methods based on supervised learning have already been demonstrated for damage detection using oblique airborne images. However, they often do not generalize well when data from new unseen sites need to be processed, hampering their practical use. Reasons for this limitation include image and scene characteristics, though the most prominent one relates to the image features being used for training the classifier. Recently features based on deep learning approaches, such as convolutional neural networks (CNNs), have been shown to be more effective than conventional hand-crafted features, and have become the state-of-the-art in many domains, including remote sensing. Moreover, often oblique images are captured with high block overlap, facilitating the generation of dense 3D point clouds - an ideal source to derive geometric characteristics. We hypothesized that the use of CNN features, either independently or in combination with 3D point cloud features, would yield improved performance in damage detection. To this end we used CNN and 3D features, both independently and in combination, using images from manned and unmanned aerial platforms over several geographic locations that vary significantly in terms of image and scene characteristics. A multiple-kernel-learning framework, an effective way for integrating features from different modalities, was used for combining the two sets of features for classification. The results are encouraging: while CNN features produced an average classification accuracy of about 91%, the integration of 3D point cloud features led to an additional

  18. Peach Flower Monitoring Using Aerial Multispectral Imaging

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    Ryan Horton

    2017-01-01

    Full Text Available One of the tools for optimal crop production is regular monitoring and assessment of crops. During the growing season of fruit trees, the bloom period has increased photosynthetic rates that correlate with the fruiting process. This paper presents the development of an image processing algorithm to detect peach blossoms on trees. Aerial images of peach (Prunus persica trees were acquired from both experimental and commercial peach orchards in the southwestern part of Idaho using an off-the-shelf unmanned aerial system (UAS, equipped with a multispectral camera (near-infrared, green, blue. The image processing algorithm included contrast stretching of the three bands to enhance the image and thresholding segmentation method to detect the peach blossoms. Initial results showed that the image processing algorithm could detect peach blossoms with an average detection rate of 84.3% and demonstrated good potential as a monitoring tool for orchard management.

  19. Improving settlement type classification of aerial images

    CSIR Research Space (South Africa)

    Mdakane, L

    2014-10-01

    Full Text Available , an automated method can be used to help identify human settlements in a fixed, repeatable and timely manner. The main contribution of this work is to improve generalisation on settlement type classification of aerial imagery. Images acquired at different dates...

  20. Orientation Strategies for Aerial Oblique Images

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    Wiedemann, A.; Moré, J.

    2012-07-01

    Oblique aerial images become more and more distributed to fill the gap between vertical aerial images and mobile mapping systems. Different systems are on the market. For some applications, like texture mapping, precise orientation data are required. One point is the stable interior orientation, which can be achieved by stable camera systems, the other a precise exterior orientation. A sufficient exterior orientation can be achieved by a large effort in direct sensor orientation, whereas minor errors in the angles have a larger effect than in vertical imagery. The more appropriate approach is by determine the precise orientation parameters by photogrammetric methods using an adapted aerial triangulation. Due to the different points of view towards the object the traditional aerotriangulation matching tools fail, as they produce a bunch of blunders and require a lot of manual work to achieve a sufficient solution. In this paper some approaches are discussed and results are presented for the most promising approaches. We describe a single step approach with an aerotriangulation using all available images; a two step approach with an aerotriangulation only of the vertical images plus a mathematical transformation of the oblique images using the oblique cameras excentricity; and finally the extended functional model for a bundle block adjustment considering the mechanical connection between vertical and oblique images. Beside accuracy also other aspects like efficiency and required manual work have to be considered.

  1. Analysis of the impact of spatial resolution on land/water classifications using high-resolution aerial imagery

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    Enwright, Nicholas M.; Jones, William R.; Garber, Adrienne L.; Keller, Matthew J.

    2014-01-01

    Long-term monitoring efforts often use remote sensing to track trends in habitat or landscape conditions over time. To most appropriately compare observations over time, long-term monitoring efforts strive for consistency in methods. Thus, advances and changes in technology over time can present a challenge. For instance, modern camera technology has led to an increasing availability of very high-resolution imagery (i.e. submetre and metre) and a shift from analogue to digital photography. While numerous studies have shown that image resolution can impact the accuracy of classifications, most of these studies have focused on the impacts of comparing spatial resolution changes greater than 2 m. Thus, a knowledge gap exists on the impacts of minor changes in spatial resolution (i.e. submetre to about 1.5 m) in very high-resolution aerial imagery (i.e. 2 m resolution or less). This study compared the impact of spatial resolution on land/water classifications of an area dominated by coastal marsh vegetation in Louisiana, USA, using 1:12,000 scale colour-infrared analogue aerial photography (AAP) scanned at four different dot-per-inch resolutions simulating ground sample distances (GSDs) of 0.33, 0.54, 1, and 2 m. Analysis of the impact of spatial resolution on land/water classifications was conducted by exploring various spatial aspects of the classifications including density of waterbodies and frequency distributions in waterbody sizes. This study found that a small-magnitude change (1–1.5 m) in spatial resolution had little to no impact on the amount of water classified (i.e. percentage mapped was less than 1.5%), but had a significant impact on the mapping of very small waterbodies (i.e. waterbodies ≤ 250 m2). These findings should interest those using temporal image classifications derived from very high-resolution aerial photography as a component of long-term monitoring programs.

  2. Automated Archiving of Archaeological Aerial Images

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    Michael Doneus

    2016-03-01

    Full Text Available The main purpose of any aerial photo archive is to allow quick access to images based on content and location. Therefore, next to a description of technical parameters and depicted content, georeferencing of every image is of vital importance. This can be done either by identifying the main photographed object (georeferencing of the image content or by mapping the center point and/or the outline of the image footprint. The paper proposes a new image archiving workflow. The new pipeline is based on the parameters that are logged by a commercial, but cost-effective GNSS/IMU solution and processed with in-house-developed software. Together, these components allow one to automatically geolocate and rectify the (oblique aerial images (by a simple planar rectification using the exterior orientation parameters and to retrieve their footprints with reasonable accuracy, which is automatically stored as a vector file. The data of three test flights were used to determine the accuracy of the device, which turned out to be better than 1° for roll and pitch (mean between 0.0 and 0.21 with a standard deviation of 0.17–0.46 and better than 2.5° for yaw angles (mean between 0.0 and −0.14 with a standard deviation of 0.58–0.94. This turned out to be sufficient to enable a fast and almost automatic GIS-based archiving of all of the imagery.

  3. Mapping Urban Ecosystem Services Using High Resolution Aerial Photography

    Science.gov (United States)

    Pilant, A. N.; Neale, A.; Wilhelm, D.

    2010-12-01

    Ecosystem services (ES) are the many life-sustaining benefits we receive from nature: e.g., clean air and water, food and fiber, cultural-aesthetic-recreational benefits, pollination and flood control. The ES concept is emerging as a means of integrating complex environmental and economic information to support informed environmental decision making. The US EPA is developing a web-based National Atlas of Ecosystem Services, with a component for urban ecosystems. Currently, the only wall-to-wall, national scale land cover data suitable for this analysis is the National Land Cover Data (NLCD) at 30 m spatial resolution with 5 and 10 year updates. However, aerial photography is acquired at higher spatial resolution (0.5-3 m) and more frequently (1-5 years, typically) for most urban areas. Land cover was mapped in Raleigh, NC using freely available USDA National Agricultural Imagery Program (NAIP) with 1 m ground sample distance to test the suitability of aerial photography for urban ES analysis. Automated feature extraction techniques were used to extract five land cover classes, and an accuracy assessment was performed using standard techniques. Results will be presented that demonstrate applications to mapping ES in urban environments: greenways, corridors, fragmentation, habitat, impervious surfaces, dark and light pavement (urban heat island). Automated feature extraction results mapped over NAIP color aerial photograph. At this scale, we can look at land cover and related ecosystem services at the 2-10 m scale. Small features such as individual trees and sidewalks are visible and mappable. Classified aerial photo of Downtown Raleigh NC Red: impervious surface Dark Green: trees Light Green: grass Tan: soil

  4. A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification

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    Yunlong Yu

    2018-01-01

    Full Text Available One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new two-stream deep architecture for aerial scene classification. First, we use two pretrained convolutional neural networks (CNNs as feature extractor to learn deep features from the original aerial image and the processed aerial image through saliency detection, respectively. Second, two feature fusion strategies are adopted to fuse the two different types of deep convolutional features extracted by the original RGB stream and the saliency stream. Finally, we use the extreme learning machine (ELM classifier for final classification with the fused features. The effectiveness of the proposed architecture is tested on four challenging datasets: UC-Merced dataset with 21 scene categories, WHU-RS dataset with 19 scene categories, AID dataset with 30 scene categories, and NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that our architecture gets a significant classification accuracy improvement over all state-of-the-art references.

  5. Direct Penguin Counting Using Unmanned Aerial Vehicle Image

    Science.gov (United States)

    Hyun, C. U.; Kim, H. C.; Kim, J. H.; Hong, S. G.

    2015-12-01

    This study presents an application of unmanned aerial vehicle (UAV) images to monitor penguin colony in Baton Peninsula, King George Island, Antarctica. The area around Narębski Point located on the southeast coast of Barton Peninsula was designated as Antarctic Specially Protected Area No. 171 (ASPA 171), and Chinstrap and Gentoo penguins inhabit in this area. The UAV images were acquired in a part of ASPA 171 from four flights in a single day, Jan 18, 2014. About 360 images were mosaicked as an image of about 3 cm spatial resolution and then a subset including representative penguin rookeries was selected. The subset image was segmented based on gradient map of pixel values, and spectral and spatial attributes were assigned to each segment. The object based image analysis (OBIA) was conducted with consideration of spectral attributes including mean and minimum values of each segment and various shape attributes such as area, length, compactness and roundness to detect individual penguin. The segments indicating individual penguin were effectively detected on rookeries with high contrasts in the spectral and shape attributes. The importance of periodic and precise monitoring of penguins has been recognized because variations of their populations reflect environmental changes and disturbance from human activities. Utilization of very high resolution imaging method shown in this study can be applied to other penguin habitats in Antarctica, and the results will be able to support establishing effective environmental management plans.

  6. Automated Identification of River Hydromorphological Features Using UAV High Resolution Aerial Imagery

    Directory of Open Access Journals (Sweden)

    Monica Rivas Casado

    2015-11-01

    Full Text Available European legislation is driving the development of methods for river ecosystem protection in light of concerns over water quality and ecology. Key to their success is the accurate and rapid characterisation of physical features (i.e., hydromorphology along the river. Image pattern recognition techniques have been successfully used for this purpose. The reliability of the methodology depends on both the quality of the aerial imagery and the pattern recognition technique used. Recent studies have proved the potential of Unmanned Aerial Vehicles (UAVs to increase the quality of the imagery by capturing high resolution photography. Similarly, Artificial Neural Networks (ANN have been shown to be a high precision tool for automated recognition of environmental patterns. This paper presents a UAV based framework for the identification of hydromorphological features from high resolution RGB aerial imagery using a novel classification technique based on ANNs. The framework is developed for a 1.4 km river reach along the river Dee in Wales, United Kingdom. For this purpose, a Falcon 8 octocopter was used to gather 2.5 cm resolution imagery. The results show that the accuracy of the framework is above 81%, performing particularly well at recognising vegetation. These results leverage the use of UAVs for environmental policy implementation and demonstrate the potential of ANNs and RGB imagery for high precision river monitoring and river management.

  7. Local Deep Hashing Matching of Aerial Images Based on Relative Distance and Absolute Distance Constraints

    Directory of Open Access Journals (Sweden)

    Suting Chen

    2017-12-01

    Full Text Available Aerial images have features of high resolution, complex background, and usually require large amounts of calculation, however, most algorithms used in matching of aerial images adopt the shallow hand-crafted features expressed as floating-point descriptors (e.g., SIFT (Scale-invariant Feature Transform, SURF (Speeded Up Robust Features, which may suffer from poor matching speed and are not well represented in the literature. Here, we propose a novel Local Deep Hashing Matching (LDHM method for matching of aerial images with large size and with lower complexity or fast matching speed. The basic idea of the proposed algorithm is to utilize the deep network model in the local area of the aerial images, and study the local features, as well as the hash function of the images. Firstly, according to the course overlap rate of aerial images, the algorithm extracts the local areas for matching to avoid the processing of redundant information. Secondly, a triplet network structure is proposed to mine the deep features of the patches of the local image, and the learned features are imported to the hash layer, thus obtaining the representation of a binary hash code. Thirdly, the constraints of the positive samples to the absolute distance are added on the basis of the triplet loss, a new objective function is constructed to optimize the parameters of the network and enhance the discriminating capabilities of image patch features. Finally, the obtained deep hash code of each image patch is used for the similarity comparison of the image patches in the Hamming space to complete the matching of aerial images. The proposed LDHM algorithm evaluates the UltraCam-D dataset and a set of actual aerial images, simulation result demonstrates that it may significantly outperform the state-of-the-art algorithm in terms of the efficiency and performance.

  8. Superpixel-Based Feature for Aerial Image Scene Recognition

    Directory of Open Access Journals (Sweden)

    Hongguang Li

    2018-01-01

    Full Text Available Image scene recognition is a core technology for many aerial remote sensing applications. Different landforms are inputted as different scenes in aerial imaging, and all landform information is regarded as valuable for aerial image scene recognition. However, the conventional features of the Bag-of-Words model are designed using local points or other related information and thus are unable to fully describe landform areas. This limitation cannot be ignored when the aim is to ensure accurate aerial scene recognition. A novel superpixel-based feature is proposed in this study to characterize aerial image scenes. Then, based on the proposed feature, a scene recognition method of the Bag-of-Words model for aerial imaging is designed. The proposed superpixel-based feature that utilizes landform information establishes top-task superpixel extraction of landforms to bottom-task expression of feature vectors. This characterization technique comprises the following steps: simple linear iterative clustering based superpixel segmentation, adaptive filter bank construction, Lie group-based feature quantification, and visual saliency model-based feature weighting. Experiments of image scene recognition are carried out using real image data captured by an unmanned aerial vehicle (UAV. The recognition accuracy of the proposed superpixel-based feature is 95.1%, which is higher than those of scene recognition algorithms based on other local features.

  9. Semantic Segmentation of Aerial Images with AN Ensemble of Cnns

    Science.gov (United States)

    Marmanis, D.; Wegner, J. D.; Galliani, S.; Schindler, K.; Datcu, M.; Stilla, U.

    2016-06-01

    This paper describes a deep learning approach to semantic segmentation of very high resolution (aerial) images. Deep neural architectures hold the promise of end-to-end learning from raw images, making heuristic feature design obsolete. Over the last decade this idea has seen a revival, and in recent years deep convolutional neural networks (CNNs) have emerged as the method of choice for a range of image interpretation tasks like visual recognition and object detection. Still, standard CNNs do not lend themselves to per-pixel semantic segmentation, mainly because one of their fundamental principles is to gradually aggregate information over larger and larger image regions, making it hard to disentangle contributions from different pixels. Very recently two extensions of the CNN framework have made it possible to trace the semantic information back to a precise pixel position: deconvolutional network layers undo the spatial downsampling, and Fully Convolution Networks (FCNs) modify the fully connected classification layers of the network in such a way that the location of individual activations remains explicit. We design a FCN which takes as input intensity and range data and, with the help of aggressive deconvolution and recycling of early network layers, converts them into a pixelwise classification at full resolution. We discuss design choices and intricacies of such a network, and demonstrate that an ensemble of several networks achieves excellent results on challenging data such as the ISPRS semantic labeling benchmark, using only the raw data as input.

  10. Aerial Triangulation Close-range Images with Dual Quaternion

    Directory of Open Access Journals (Sweden)

    SHENG Qinghong

    2015-05-01

    Full Text Available A new method for the aerial triangulation of close-range images based on dual quaternion is presented. Using dual quaternion to represent the spiral screw motion of the beam in the space, the real part of dual quaternion represents the angular elements of all the beams in the close-range area networks, the real part and the dual part of dual quaternion represents the line elements corporately. Finally, an aerial triangulation adjustment model based on dual quaternion is established, and the elements of interior orientation and exterior orientation and the object coordinates of the ground points are calculated. Real images and large attitude angle simulated images are selected to run the experiments of aerial triangulation. The experimental results show that the new method for the aerial triangulation of close-range images based on dual quaternion can obtain higher accuracy.

  11. The Evaluation of High Resolution Aerial Imagery for Monitoring of ...

    African Journals Online (AJOL)

    The Royal Natal National Park and the Rugged Glen Nature Reserve are part of the uKhahlamba Drakensberg Park (UDP) World Heritage Site and have infestations of bracken fern (Pteridium aquilinum [L.] Kuhn). Prior image classification research on bracken fern were constrained by low resolution satellite imagery and ...

  12. FITTING OF PARAMETRIC BUILDING MODELS TO OBLIQUE AERIAL IMAGES

    Directory of Open Access Journals (Sweden)

    U. S. Panday

    2012-09-01

    Full Text Available In literature and in photogrammetric workstations many approaches and systems to automatically reconstruct buildings from remote sensing data are described and available. Those building models are being used for instance in city modeling or in cadastre context. If a roof overhang is present, the building walls cannot be estimated correctly from nadir-view aerial images or airborne laser scanning (ALS data. This leads to inconsistent building outlines, which has a negative influence on visual impression, but more seriously also represents a wrong legal boundary in the cadaster. Oblique aerial images as opposed to nadir-view images reveal greater detail, enabling to see different views of an object taken from different directions. Building walls are visible from oblique images directly and those images are used for automated roof overhang estimation in this research. A fitting algorithm is employed to find roof parameters of simple buildings. It uses a least squares algorithm to fit projected wire frames to their corresponding edge lines extracted from the images. Self-occlusion is detected based on intersection result of viewing ray and the planes formed by the building whereas occlusion from other objects is detected using an ALS point cloud. Overhang and ground height are obtained by sweeping vertical and horizontal planes respectively. Experimental results are verified with high resolution ortho-images, field survey, and ALS data. Planimetric accuracy of 1cm mean and 5cm standard deviation was obtained, while buildings' orientation were accurate to mean of 0.23° and standard deviation of 0.96° with ortho-image. Overhang parameters were aligned to approximately 10cm with field survey. The ground and roof heights were accurate to mean of – 9cm and 8cm with standard deviations of 16cm and 8cm with ALS respectively. The developed approach reconstructs 3D building models well in cases of sufficient texture. More images should be acquired for

  13. Accuracy assessment of cadastral maps using high resolution aerial photos

    Directory of Open Access Journals (Sweden)

    Alwan Imzahim

    2018-01-01

    Full Text Available A cadastral map is a map that shows the boundaries and ownership of land parcels. Some cadastral maps show additional details, such as survey district names, unique identifying numbers for parcels, certificate of title numbers, positions of existing structures, section or lot numbers and their respective areas, adjoining and adjacent street names, selected boundary dimensions and references to prior maps. In Iraq / Baghdad Governorate, the main problem is that the cadastral maps are georeferenced to a local geodetic datum known as Clark 1880 while the widely used reference system for navigation purpose (GPS and GNSS and uses Word Geodetic System 1984 (WGS84 as a base reference datum. The objective of this paper is to produce a cadastral map with scale 1:500 (metric scale by using aerial photographs 2009 with high ground spatial resolution 10 cm reference WGS84 system. The accuracy assessment for the cadastral maps updating approach to urban large scale cadastral maps (1:500-1:1000 was ± 0.115 meters; which complies with the American Social for Photogrammetry and Remote Sensing Standards (ASPRS.

  14. High Density Aerial Image Matching: State-Of and Future Prospects

    Science.gov (United States)

    Haala, N.; Cavegn, S.

    2016-06-01

    Ongoing innovations in matching algorithms are continuously improving the quality of geometric surface representations generated automatically from aerial images. This development motivated the launch of the joint ISPRS/EuroSDR project "Benchmark on High Density Aerial Image Matching", which aims on the evaluation of photogrammetric 3D data capture in view of the current developments in dense multi-view stereo-image matching. Originally, the test aimed on image based DSM computation from conventional aerial image flights for different landuse and image block configurations. The second phase then put an additional focus on high quality, high resolution 3D geometric data capture in complex urban areas. This includes both the extension of the test scenario to oblique aerial image flights as well as the generation of filtered point clouds as additional output of the respective multi-view reconstruction. The paper uses the preliminary outcomes of the benchmark to demonstrate the state-of-the-art in airborne image matching with a special focus of high quality geometric data capture in urban scenarios.

  15. Combining Constraint Types From Public Data in Aerial Image Segmentation

    DEFF Research Database (Denmark)

    Jacobsen, Thomas Stig; Jensen, Jacob Jon; Jensen, Daniel Rune

    2013-01-01

    We introduce a method for image segmentation that constraints the clustering with map and point data. The method is showcased by applying the spectral clustering algorithm on aerial images for building detection with constraints built from a height map and address point data. We automatically det...

  16. Characterizing Pavement Surface Distress Conditions with Hyper-Spatial Resolution Natural Color Aerial Photography

    Directory of Open Access Journals (Sweden)

    Su Zhang

    2016-05-01

    Full Text Available Roadway pavement surface distress information is critical for effective pavement asset management, and subsequently, transportation management agencies at all levels (i.e., federal, state, and local dedicate a large amount of time and money to routinely evaluate pavement surface distress conditions as the core of their asset management programs. However, currently adopted ground-based evaluation methods for pavement surface conditions have many disadvantages, like being time-consuming and expensive. Aircraft-based evaluation methods, although getting more attention, have not been used for any operational evaluation programs yet because the acquired images lack the spatial resolution to resolve finer scale pavement surface distresses. Hyper-spatial resolution natural color aerial photography (HSR-AP provides a potential method for collecting pavement surface distress information that can supplement or substitute for currently adopted evaluation methods. Using roadway pavement sections located in the State of New Mexico as an example, this research explored the utility of aerial triangulation (AT technique and HSR-AP acquired from a low-altitude and low-cost small-unmanned aircraft system (S-UAS, in this case a tethered helium weather balloon, to permit characterization of detailed pavement surface distress conditions. The Wilcoxon Signed Rank test, Mann-Whitney U test, and visual comparison were used to compare detailed pavement surface distress rates measured from HSR-AP derived products (orthophotos and digital surface models generated from AT with reference distress rates manually collected on the ground using standard protocols. The results reveal that S-UAS based hyper-spatial resolution imaging and AT techniques can provide detailed and reliable primary observations suitable for characterizing detailed pavement surface distress conditions comparable to the ground-based manual measurement, which lays the foundation for the future application

  17. High spatial resolution mapping of folds and fractures using Unmanned Aerial Vehicle (UAV) photogrammetry

    Science.gov (United States)

    Cruden, A. R.; Vollgger, S.

    2016-12-01

    The emerging capability of UAV photogrammetry combines a simple and cost-effective method to acquire digital aerial images with advanced computer vision algorithms that compute spatial datasets from a sequence of overlapping digital photographs from various viewpoints. Depending on flight altitude and camera setup, sub-centimeter spatial resolution orthophotographs and textured dense point clouds can be achieved. Orientation data can be collected for detailed structural analysis by digitally mapping such high-resolution spatial datasets in a fraction of time and with higher fidelity compared to traditional mapping techniques. Here we describe a photogrammetric workflow applied to a structural study of folds and fractures within alternating layers of sandstone and mudstone at a coastal outcrop in SE Australia. We surveyed this location using a downward looking digital camera mounted on commercially available multi-rotor UAV that autonomously followed waypoints at a set altitude and speed to ensure sufficient image overlap, minimum motion blur and an appropriate resolution. The use of surveyed ground control points allowed us to produce a geo-referenced 3D point cloud and an orthophotograph from hundreds of digital images at a spatial resolution automatically extracted from these high-resolution datasets using open-source software. This resulted in an extensive and statistically relevant orientation dataset that was used to 1) interpret the progressive development of folds and faults in the region, and 2) to generate a 3D structural model that underlines the complex internal structure of the outcrop and quantifies spatial variations in fold geometries. Overall, our work highlights how UAV photogrammetry can contribute to new insights in structural analysis.

  18. Augmenting camera images for operators of Unmanned Aerial Vehicles

    NARCIS (Netherlands)

    Veltman, J.A.; Oving, A.B.

    2003-01-01

    The manual control of the camera of an unmanned aerial vehicle (UAV) can be difficult due to several factors such as 1) time delays between steering input and changes of the monitor content, 2) low update rates of the camera images and 3) lack of situation awareness due to the remote position of the

  19. Rectification of aerial images using piecewise linear transformation

    International Nuclear Information System (INIS)

    Liew, L H; Lee, B Y; Wang, Y C; Cheah, W S

    2014-01-01

    Aerial images are widely used in various activities by providing visual records. This type of remotely sensed image is helpful in generating digital maps, managing ecology, monitoring crop growth and region surveying. Such images could provide insight into areas of interest that have lower altitude, particularly in regions where optical satellite imaging is prevented due to cloudiness. Aerial images captured using a non-metric cameras contain real details of the images as well as unexpected distortions. Distortions would affect the actual length, direction and shape of objects in the images. There are many sources that could cause distortions such as lens, earth curvature, topographic relief and the attitude of the aircraft that is used to carry the camera. These distortions occur differently, collectively and irregularly in the entire image. Image rectification is an essential image pre-processing step to eliminate or at least reduce the effect of distortions. In this paper, a non-parametric approach with piecewise linear transformation is investigated in rectifying distorted aerial images. The non-parametric approach requires a set of corresponding control points obtained from a reference image and a distorted image. The corresponding control points are then applied with piecewise linear transformation as geometric transformation. Piecewise linear transformation divides the image into regions by triangulation. Different linear transformations are employed separately to triangular regions instead of using a single transformation as the rectification model for the entire image. The result of rectification is evaluated using total root mean square error (RMSE). Experiments show that piecewise linear transformation could assist in improving the limitation of using global transformation to rectify images

  20. Aerial imaging for FABs: productivity and yield aspects

    Science.gov (United States)

    Englard, Ilan; Cohen, Yaron; Elblinger, Yair; Attal, Shay; Berns, Neil; Shoval, Lior; Ben-Yishai, Michael; Mangan, Shmoolik

    2009-03-01

    variations. Furthermore, aggressive cleaning may damage the delicate sub-resolution assist features. IntenCD based CDU fingerprint correction can optimize the regular mask cleaning schedule, extending clean intervals therefore extending the overall mask life span. This mask availability enhancement alone reduces the amount of mask sets required during the product life cycle and potentially leads to significant savings to the fab. This mask availability enhancement alone reduces the amount of mask sets required during the product life cycle and leads to significant savings to the fab. In this paper we present three case studies from a wafer production fab and a mask shop. The data presented demonstrates clear productivity and yield enhancements. The data presented is the outcome of a range of new applications which became possible by integrating the recently introduced Applied Materials Aera2TM for Lithography aerial imaging inspection tool with the litho cluster.

  1. Vehicle detection from very-high-resolution (VHR) aerial imagery using attribute belief propagation (ABP)

    Science.gov (United States)

    Wang, Yanli; Li, Ying; Zhang, Li; Huang, Yuchun

    2016-10-01

    With the popularity of very-high-resolution (VHR) aerial imagery, the shape, color, and context attribute of vehicles are better characterized. Due to the various road surroundings and imaging conditions, vehicle attributes could be adversely affected so that vehicle is mistakenly detected or missed. This paper is motivated to robustly extract the rich attribute feature for detecting the vehicles of VHR imagery under different scenarios. Based on the hierarchical component tree of vehicle context, attribute belief propagation (ABP) is proposed to detect salient vehicles from the statistical perspective. With the Max-tree data structure, the multi-level component tree around the road network is efficiently created. The spatial relationship between vehicle and its belonging context is established with the belief definition of vehicle attribute. To effectively correct single-level belief error, the inter-level belief linkages enforce consistency of belief assignment between corresponding components at different levels. ABP starts from an initial set of vehicle belief calculated by vehicle attribute, and then iterates through each component by applying inter-level belief passing until convergence. The optimal value of vehicle belief of each component is obtained via minimizing its belief function iteratively. The proposed algorithm is tested on a diverse set of VHR imagery acquired in the city and inter-city areas of the West and South China. Experimental results show that the proposed algorithm can detect vehicle efficiently and suppress the erroneous effectively. The proposed ABP framework is promising to robustly classify the vehicles from VHR Aerial imagery.

  2. Radiometric corrections of the vignetting effect in aerial digital images

    Directory of Open Access Journals (Sweden)

    Andrés L. G. Jaime

    2004-07-01

    Full Text Available Monitoring agriculture cultures by aerial remote sensing present high potential of application. Despite of that potential, some problems still have been detected. One of them is the vignetting effect. This phenomenon introduces error in DN as far away as geometric image center the target is, according to the cos4Theta law. To study this effect it was adopted the procedure that computes Equation - Equação. If these values increase with the distances from images geometric center then the vignetting effect increases proportionally. The study was carried out analyzing the DN of white plate targets in aerial images in two dates 02/11/2001 and 11/04/2002. The white plate targets were distributed in the field and could be seen around the images geometric center, in different distances. In the aerial images the DN from the plates were extracted according to the cos4Theta law and compared to several distances in conformity to Equation - Equação. The results showed that the effect was observed in the first (02/11/2001 images, but not in later (11/04/2002 images. That difference can be explained by the different atmospheric haze and sensor-illumination source geometry. On the other hand when the experiment was performed at ground level the vignetting effect was identified. Therefore the effect exists and can be modeled.

  3. CMOS Imaging Sensor Technology for Aerial Mapping Cameras

    Science.gov (United States)

    Neumann, Klaus; Welzenbach, Martin; Timm, Martin

    2016-06-01

    In June 2015 Leica Geosystems launched the first large format aerial mapping camera using CMOS sensor technology, the Leica DMC III. This paper describes the motivation to change from CCD sensor technology to CMOS for the development of this new aerial mapping camera. In 2002 the DMC first generation was developed by Z/I Imaging. It was the first large format digital frame sensor designed for mapping applications. In 2009 Z/I Imaging designed the DMC II which was the first digital aerial mapping camera using a single ultra large CCD sensor to avoid stitching of smaller CCDs. The DMC III is now the third generation of large format frame sensor developed by Z/I Imaging and Leica Geosystems for the DMC camera family. It is an evolution of the DMC II using the same system design with one large monolithic PAN sensor and four multi spectral camera heads for R,G, B and NIR. For the first time a 391 Megapixel large CMOS sensor had been used as PAN chromatic sensor, which is an industry record. Along with CMOS technology goes a range of technical benefits. The dynamic range of the CMOS sensor is approx. twice the range of a comparable CCD sensor and the signal to noise ratio is significantly better than with CCDs. Finally results from the first DMC III customer installations and test flights will be presented and compared with other CCD based aerial sensors.

  4. Aerial Images and Convolutional Neural Network for Cotton Bloom Detection.

    Science.gov (United States)

    Xu, Rui; Li, Changying; Paterson, Andrew H; Jiang, Yu; Sun, Shangpeng; Robertson, Jon S

    2017-01-01

    Monitoring flower development can provide useful information for production management, estimating yield and selecting specific genotypes of crops. The main goal of this study was to develop a methodology to detect and count cotton flowers, or blooms, using color images acquired by an unmanned aerial system. The aerial images were collected from two test fields in 4 days. A convolutional neural network (CNN) was designed and trained to detect cotton blooms in raw images, and their 3D locations were calculated using the dense point cloud constructed from the aerial images with the structure from motion method. The quality of the dense point cloud was analyzed and plots with poor quality were excluded from data analysis. A constrained clustering algorithm was developed to register the same bloom detected from different images based on the 3D location of the bloom. The accuracy and incompleteness of the dense point cloud were analyzed because they affected the accuracy of the 3D location of the blooms and thus the accuracy of the bloom registration result. The constrained clustering algorithm was validated using simulated data, showing good efficiency and accuracy. The bloom count from the proposed method was comparable with the number counted manually with an error of -4 to 3 blooms for the field with a single plant per plot. However, more plots were underestimated in the field with multiple plants per plot due to hidden blooms that were not captured by the aerial images. The proposed methodology provides a high-throughput method to continuously monitor the flowering progress of cotton.

  5. ACCURACY OF MEASUREMENTS IN OBLIQUE AERIAL IMAGES FOR URBAN ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    W. Ostrowski

    2016-10-01

    Full Text Available Oblique aerial images have been a source of data for urban areas for several years. However, the accuracy of measurements in oblique images during this time has been limited to a single meter due to the use of direct -georeferencing technology and the underlying digital elevation model. Therefore, oblique images have been used mostly for visualization purposes. This situation changed in recent years as new methods, which allowed for a higher accuracy of exterior orientation, were developed. Current developments include the process of determining exterior orientation and the previous but still crucial process of tie point extraction. Progress in this area was shown in the ISPRS/EUROSDR Benchmark on Multi-Platform Photogrammetry and is also noticeable in the growing interest in the use of this kind of imagery. The higher level of accuracy in the orientation of oblique aerial images that has become possible in the last few years should result in a higher level of accuracy in the measurements of these types of images. The main goal of this research was to set and empirically verify the accuracy of measurements in oblique aerial images. The research focused on photogrammetric measurements composed of many images, which use a high overlap within an oblique dataset and different view angles. During the experiments, two series of images of urban areas were used. Both were captured using five DigiCam cameras in a Maltese cross configuration. The tilt angles of the oblique cameras were 45 degrees, and the position of the cameras during flight used a high grade GPS/INS navigation system. The orientation of the images was set using the Pix4D Mapper Pro software with both measurements of the in-flight camera position and the ground control points (measured with GPS RTK technology. To control the accuracy, check points were used (which were also measured with GPS RTK technology. As reference data for the whole study, an area of the city-based map was used

  6. Damage Degree Evaluation of Earthquake Area Using UAV Aerial Image

    Directory of Open Access Journals (Sweden)

    Jinhong Chen

    2016-01-01

    Full Text Available An Unmanned Aerial Vehicle (UAV system and its aerial image analysis method are developed to evaluate the damage degree of earthquake area. Both the single-rotor and the six-rotor UAVs are used to capture the visible light image of ground targets. Five types of typical ground targets are considered for the damage degree evaluation: the building, the road, the mountain, the riverway, and the vegetation. When implementing the image analysis, first the Image Quality Evaluation Metrics (IQEMs, that is, the image contrast, the image blur, and the image noise, are used to assess the imaging definition. Second, once the image quality is qualified, the Gray Level Cooccurrence Matrix (GLCM texture feature, the Tamura texture feature, and the Gabor wavelet texture feature are computed. Third, the Support Vector Machine (SVM classifier is employed to evaluate the damage degree. Finally, a new damage degree evaluation (DDE index is defined to assess the damage intensity of earthquake. Many experiment results have verified the correctness of proposed system and method.

  7. Moving object detection in top-view aerial videos improved by image stacking

    Science.gov (United States)

    Teutsch, Michael; Krüger, Wolfgang; Beyerer, Jürgen

    2017-08-01

    Image stacking is a well-known method that is used to improve the quality of images in video data. A set of consecutive images is aligned by applying image registration and warping. In the resulting image stack, each pixel has redundant information about its intensity value. This redundant information can be used to suppress image noise, resharpen blurry images, or even enhance the spatial image resolution as done in super-resolution. Small moving objects in the videos usually get blurred or distorted by image stacking and thus need to be handled explicitly. We use image stacking in an innovative way: image registration is applied to small moving objects only, and image warping blurs the stationary background that surrounds the moving objects. Our video data are coming from a small fixed-wing unmanned aerial vehicle (UAV) that acquires top-view gray-value images of urban scenes. Moving objects are mainly cars but also other vehicles such as motorcycles. The resulting images, after applying our proposed image stacking approach, are used to improve baseline algorithms for vehicle detection and segmentation. We improve precision and recall by up to 0.011, which corresponds to a reduction of the number of false positive and false negative detections by more than 3 per second. Furthermore, we show how our proposed image stacking approach can be implemented efficiently.

  8. BUILDING DETECTION USING AERIAL IMAGES AND DIGITAL SURFACE MODELS

    Directory of Open Access Journals (Sweden)

    J. Mu

    2017-05-01

    Full Text Available In this paper a method for building detection in aerial images based on variational inference of logistic regression is proposed. It consists of three steps. In order to characterize the appearances of buildings in aerial images, an effective bag-of-Words (BoW method is applied for feature extraction in the first step. In the second step, a classifier of logistic regression is learned using these local features. The logistic regression can be trained using different methods. In this paper we adopt a fully Bayesian treatment for learning the classifier, which has a number of obvious advantages over other learning methods. Due to the presence of hyper prior in the probabilistic model of logistic regression, approximate inference methods have to be applied for prediction. In order to speed up the inference, a variational inference method based on mean field instead of stochastic approximation such as Markov Chain Monte Carlo is applied. After the prediction, a probabilistic map is obtained. In the third step, a fully connected conditional random field model is formulated and the probabilistic map is used as the data term in the model. A mean field inference is utilized in order to obtain a binary building mask. A benchmark data set consisting of aerial images and digital surfaced model (DSM released by ISPRS for 2D semantic labeling is used for performance evaluation. The results demonstrate the effectiveness of the proposed method.

  9. Hourglass-ShapeNetwork Based Semantic Segmentation for High Resolution Aerial Imagery

    Directory of Open Access Journals (Sweden)

    Yu Liu

    2017-05-01

    Full Text Available A new convolution neural network (CNN architecture for semantic segmentation of high resolution aerial imagery is proposed in this paper. The proposed architecture follows an hourglass-shaped network (HSN design being structured into encoding and decoding stages. By taking advantage of recent advances in CNN designs, we use the composed inception module to replace common convolutional layers, providing the network with multi-scale receptive areas with rich context. Additionally, in order to reduce spatial ambiguities in the up-sampling stage, skip connections with residual units are also employed to feed forward encoding-stage information directly to the decoder. Moreover, overlap inference is employed to alleviate boundary effects occurring when high resolution images are inferred from small-sized patches. Finally, we also propose a post-processing method based on weighted belief propagation to visually enhance the classification results. Extensive experiments based on the Vaihingen and Potsdam datasets demonstrate that the proposed architectures outperform three reference state-of-the-art network designs both numerically and visually.

  10. Evaluation of Color Settings in Aerial Images with the Use of Eye-Tracking User Study

    Science.gov (United States)

    Mirijovsky, J.; Popelka, S.

    2016-06-01

    The main aim of presented paper is to find the most realistic and preferred color settings for four different types of surfaces on the aerial images. This will be achieved through user study with the use of eye-movement recording. Aerial images taken by the unmanned aerial system were used as stimuli. From each image, squared crop area containing one of the studied types of surfaces (asphalt, concrete, water, soil, and grass) was selected. For each type of surface, the real value of reflectance was found with the use of precise spectroradiometer ASD HandHeld 2 which measures the reflectance. The device was used at the same time as aerial images were captured, so lighting conditions and state of vegetation were equal. The spectral resolution of the ASD device is better than 3.0 nm. For defining the RGB values of selected type of surface, the spectral reflectance values recorded by the device were merged into wider groups. Finally, we get three groups corresponding to RGB color system. Captured images were edited with the graphic editor Photoshop CS6. Contrast, clarity, and brightness were edited for all surface types on images. Finally, we get a set of 12 images of the same area with different color settings. These images were put into the grid and used as stimuli for the eye-tracking experiment. Eye-tracking is one of the methods of usability studies and it is considered as relatively objective. Eye-tracker SMI RED 250 with the sampling frequency 250 Hz was used in the study. As respondents, a group of 24 students of Geoinformatics and Geography was used. Their task was to select which image in the grid has the best color settings. The next task was to select which color settings they prefer. Respondents' answers were evaluated and the most realistic and most preferable color settings were found. The advantage of the eye-tracking evaluation was that also the process of the selection of the answers was analyzed. Areas of Interest were marked around each image in the

  11. Conflict detection and resolution system architecture for unmanned aerial vehicles in civil airspace

    NARCIS (Netherlands)

    Jenie, Y.I.; van Kampen, E.J.; Ellerbroek, J.; Hoekstra, J.M.

    2015-01-01

    A novel architecture for a general Unmanned Aerial Vehicle (UAV) Conflict Detection and Resolution (CD&R) system, in the context of their integration into the civilian airspace, is proposed in this paper. The architecture consists of layers of safety approaches ,each representing a combination of

  12. Taxonomy of Conflict Detection and Resolution Approaches for Unmanned Aerial Vehicle in an Integrated Airspace

    NARCIS (Netherlands)

    Jenie, Y.I.; van Kampen, E.; Ellerbroek, J.; Hoekstra, J.M.

    2016-01-01

    This paper proposes a taxonomy of Conflict Detection and Resolution (CD&R) approaches for Unmanned Aerial Vehicles (UAV) operation in an integrated airspace. Possible approaches for UAVs are surveyed and broken down based on their types of surveillance, coordination, maneuver, and autonomy. The

  13. A FAST APPROACH FOR STITCHING OF AERIAL IMAGES

    Directory of Open Access Journals (Sweden)

    A. Moussa

    2016-06-01

    Full Text Available The last few years have witnessed an increasing volume of aerial image data because of the extensive improvements of the Unmanned Aerial Vehicles (UAVs. These newly developed UAVs have led to a wide variety of applications. A fast assessment of the achieved coverage and overlap of the acquired images of a UAV flight mission is of great help to save the time and cost of the further steps. A fast automatic stitching of the acquired images can help to visually assess the achieved coverage and overlap during the flight mission. This paper proposes an automatic image stitching approach that creates a single overview stitched image using the acquired images during a UAV flight mission along with a coverage image that represents the count of overlaps between the acquired images. The main challenge of such task is the huge number of images that are typically involved in such scenarios. A short flight mission with image acquisition frequency of one second can capture hundreds to thousands of images. The main focus of the proposed approach is to reduce the processing time of the image stitching procedure by exploiting the initial knowledge about the images positions provided by the navigation sensors. The proposed approach also avoids solving for all the transformation parameters of all the photos together to save the expected long computation time if all the parameters were considered simultaneously. After extracting the points of interest of all the involved images using Scale-Invariant Feature Transform (SIFT algorithm, the proposed approach uses the initial image’s coordinates to build an incremental constrained Delaunay triangulation that represents the neighborhood of each image. This triangulation helps to match only the neighbor images and therefore reduces the time-consuming features matching step. The estimated relative orientation between the matched images is used to find a candidate seed image for the stitching process. The pre

  14. Comparisons of feature extraction algorithm based on unmanned aerial vehicle image

    Directory of Open Access Journals (Sweden)

    Xi Wenfei

    2017-07-01

    Full Text Available Feature point extraction technology has become a research hotspot in the photogrammetry and computer vision. The commonly used point feature extraction operators are SIFT operator, Forstner operator, Harris operator and Moravec operator, etc. With the high spatial resolution characteristics, UAV image is different from the traditional aviation image. Based on these characteristics of the unmanned aerial vehicle (UAV, this paper uses several operators referred above to extract feature points from the building images, grassland images, shrubbery images, and vegetable greenhouses images. Through the practical case analysis, the performance, advantages, disadvantages and adaptability of each algorithm are compared and analyzed by considering their speed and accuracy. Finally, the suggestions of how to adapt different algorithms in diverse environment are proposed.

  15. An automatic high precision registration method between large area aerial images and aerial light detection and ranging data

    Science.gov (United States)

    Du, Q.; Xie, D.; Sun, Y.

    2015-06-01

    The integration of digital aerial photogrammetry and Light Detetion And Ranging (LiDAR) is an inevitable trend in Surveying and Mapping field. We calculate the external orientation elements of images which identical with LiDAR coordinate to realize automatic high precision registration between aerial images and LiDAR data. There are two ways to calculate orientation elements. One is single image spatial resection using image matching 3D points that registered to LiDAR. The other one is Position and Orientation System (POS) data supported aerotriangulation. The high precision registration points are selected as Ground Control Points (GCPs) instead of measuring GCPs manually during aerotriangulation. The registration experiments indicate that the method which registering aerial images and LiDAR points has a great advantage in higher automation and precision compare with manual registration.

  16. Highway extraction from high resolution aerial photography using a geometric active contour model

    Science.gov (United States)

    Niu, Xutong

    Highway extraction and vehicle detection are two of the most important steps in traffic-flow analysis from multi-frame aerial photographs. The traditional method of deriving traffic flow trajectories relies on manual vehicle counting from a sequence of aerial photographs, which is tedious and time-consuming. This research presents a new framework for semi-automatic highway extraction. The basis of the new framework is an improved geometric active contour (GAC) model. This novel model seeks to minimize an objective function that transforms a problem of propagation of regular curves into an optimization problem. The implementation of curve propagation is based on level set theory. By using an implicit representation of a two-dimensional curve, a level set approach can be used to deal with topological changes naturally, and the output is unaffected by different initial positions of the curve. However, the original GAC model, on which the new model is based, only incorporates boundary information into the curve propagation process. An error-producing phenomenon called leakage is inevitable wherever there is an uncertain weak edge. In this research, region-based information is added as a constraint into the original GAC model, thereby, giving this proposed method the ability of integrating both boundary and region-based information during the curve propagation. Adding the region-based constraint eliminates the leakage problem. This dissertation applies the proposed augmented GAC model to the problem of highway extraction from high-resolution aerial photography. First, an optimized stopping criterion is designed and used in the implementation of the GAC model. It effectively saves processing time and computations. Second, a seed point propagation framework is designed and implemented. This framework incorporates highway extraction, tracking, and linking into one procedure. A seed point is usually placed at an end node of highway segments close to the boundary of the

  17. First demonstration of aerial gamma-ray imaging using drone for prompt radiation survey in Fukushima

    Science.gov (United States)

    Mochizuki, S.; Kataoka, J.; Tagawa, L.; Iwamoto, Y.; Okochi, H.; Katsumi, N.; Kinno, S.; Arimoto, M.; Maruhashi, T.; Fujieda, K.; Kurihara, T.; Ohsuka, S.

    2017-11-01

    Considerable amounts of radioactive substances (mainly 137Cs and 134Cs) were released into the environment after the Japanese nuclear disaster in 2011. Some restrictions on residence areas were lifted in April 2017, owing to the successive and effective decontamination operations. However, the distribution of radioactive substances in vast areas of mountain, forest and satoyama close to the city is still unknown; thus, decontamination operations in such areas are being hampered. In this paper, we report on the first aerial gamma-ray imaging of a schoolyard in Fukushima using a drone that carries a high sensitivity Compton camera. We show that the distribution of 137Cs in regions with a diameter of several tens to a hundred meters can be imaged with a typical resolution of 2-5 m within a 10-20 min flights duration. The aerial gamma-ray images taken 10 m and 20 m above the ground are qualitatively consistent with a dose map reconstructed from the ground-based measurements using a survey meter. Although further quantification is needed for the distance and air-absorption corrections to derive in situ dose map, such an aerial drone system can reduce measurement time by a factor of ten and is suitable for place where ground-based measurement are difficult.

  18. Pedestrian Detection and Tracking from Low-Resolution Unmanned Aerial Vehicle Thermal Imagery

    Directory of Open Access Journals (Sweden)

    Yalong Ma

    2016-03-01

    Full Text Available Driven by the prominent thermal signature of humans and following the growing availability of unmanned aerial vehicles (UAVs, more and more research efforts have been focusing on the detection and tracking of pedestrians using thermal infrared images recorded from UAVs. However, pedestrian detection and tracking from the thermal images obtained from UAVs pose many challenges due to the low-resolution of imagery, platform motion, image instability and the relatively small size of the objects. This research tackles these challenges by proposing a pedestrian detection and tracking system. A two-stage blob-based approach is first developed for pedestrian detection. This approach first extracts pedestrian blobs using the regional gradient feature and geometric constraints filtering and then classifies the detected blobs by using a linear Support Vector Machine (SVM with a hybrid descriptor, which sophisticatedly combines Histogram of Oriented Gradient (HOG and Discrete Cosine Transform (DCT features in order to achieve accurate detection. This research further proposes an approach for pedestrian tracking. This approach employs the feature tracker with the update of detected pedestrian location to track pedestrian objects from the registered videos and extracts the motion trajectory data. The proposed detection and tracking approaches have been evaluated by multiple different datasets, and the results illustrate the effectiveness of the proposed methods. This research is expected to significantly benefit many transportation applications, such as the multimodal traffic performance measure, pedestrian behavior study and pedestrian-vehicle crash analysis. Future work will focus on using fused thermal and visual images to further improve the detection efficiency and effectiveness.

  19. BUILDING FAÇADE SEPARATION IN VERTICAL AERIAL IMAGES

    Directory of Open Access Journals (Sweden)

    P. Meixner

    2012-07-01

    Full Text Available Three-dimensional models of urban environments have great appeal and offer promises of interesting applications. While initially it was of interest to just have such 3D data, it increasingly becomes evident that one really would like to have interpreted urban objects. To be able to interpret buildings we have to split a visible whole building block into its different single buildings. Usually this is done using cadastral information to divide the single land parcels. The problem in this case is that sometimes the building boundaries derived from the cadastre are insufficiently accurate due to several reasons like old databases with lower accuracies or inaccuracies due to transformation between two coordinate systems. For this reason it can happen that a cadastral boundary coming from an old map is displaced by up to several meters and therefore divides two buildings incorrectly. To overcome such problems we incorporate the information from vertical aerial images. We introduce a façade separation method that is able to find individual building façades using multi view stereo. The purpose is to identify the individual façades and separate them from one another before on proceeds with the analysis of a façade's details. The source was a set of overlapping, thus "redundant" vertical aerial images taken by an UltraCam digital aerial camera. Therefore in a first step we determine the building block outlines using the building classification and use the height values from the Digital Surface Model (DSM to determine approximate "façade quadrilaterals". We also incorporate height discontinuities using the height profiles along the building outlines to enhance our façade separation. In a next step we detect repeated pattern in these "façade images" and use them to separate the façades respectively building blocks from one another. We show that this method can be successfully used to separate building façades using vertical aerial images with a

  20. Automatic Georeferencing of Aerial Images by Means of Topographic Database Information

    DEFF Research Database (Denmark)

    Høhle, Joachim

    The book includes a preface and four articles which deal with the automatic georeferencing of aerial images. The articles are the written contribution of an seminar, held at Aalborg University in October 2002. The georeferencing or orientation of aerial images is the first step in mapping tasks l...... like generation of orthoimages, updating of topographic map data bases and generation of digial terrain models.......The book includes a preface and four articles which deal with the automatic georeferencing of aerial images. The articles are the written contribution of an seminar, held at Aalborg University in October 2002. The georeferencing or orientation of aerial images is the first step in mapping tasks...

  1. Modeling vegetation heights from high resolution stereo aerial photography: an application for broad-scale rangeland monitoring.

    Science.gov (United States)

    Gillan, Jeffrey K; Karl, Jason W; Duniway, Michael; Elaksher, Ahmed

    2014-11-01

    Vertical vegetation structure in rangeland ecosystems can be a valuable indicator for assessing rangeland health and monitoring riparian areas, post-fire recovery, available forage for livestock, and wildlife habitat. Federal land management agencies are directed to monitor and manage rangelands at landscapes scales, but traditional field methods for measuring vegetation heights are often too costly and time consuming to apply at these broad scales. Most emerging remote sensing techniques capable of measuring surface and vegetation height (e.g., LiDAR or synthetic aperture radar) are often too expensive, and require specialized sensors. An alternative remote sensing approach that is potentially more practical for managers is to measure vegetation heights from digital stereo aerial photographs. As aerial photography is already commonly used for rangeland monitoring, acquiring it in stereo enables three-dimensional modeling and estimation of vegetation height. The purpose of this study was to test the feasibility and accuracy of estimating shrub heights from high-resolution (HR, 3-cm ground sampling distance) digital stereo-pair aerial images. Overlapping HR imagery was taken in March 2009 near Lake Mead, Nevada and 5-cm resolution digital surface models (DSMs) were created by photogrammetric methods (aerial triangulation, digital image matching) for twenty-six test plots. We compared the heights of individual shrubs and plot averages derived from the DSMs to field measurements. We found strong positive correlations between field and image measurements for several metrics. Individual shrub heights tended to be underestimated in the imagery, however, accuracy was higher for dense, compact shrubs compared with shrubs with thin branches. Plot averages of shrub height from DSMs were also strongly correlated to field measurements but consistently underestimated. Grasses and forbs were generally too small to be detected with the resolution of the DSMs. Estimates of

  2. Integration of aerial imaging and variable-rate technology for site-specific aerial herbicide application

    Science.gov (United States)

    As remote sensing and variable rate technology are becoming more available for aerial applicators, practical methodologies on effective integration of these technologies are needed for site-specific aerial applications of crop production and protection materials. The objectives of this study were to...

  3. Quantifying Efficacy and Limits of Unmanned Aerial Vehicle (UAV Technology for Weed Seedling Detection as Affected by Sensor Resolution

    Directory of Open Access Journals (Sweden)

    José M. Peña

    2015-03-01

    Full Text Available In order to optimize the application of herbicides in weed-crop systems, accurate and timely weed maps of the crop-field are required. In this context, this investigation quantified the efficacy and limitations of remote images collected with an unmanned aerial vehicle (UAV for early detection of weed seedlings. The ability to discriminate weeds was significantly affected by the imagery spectral (type of camera, spatial (flight altitude and temporal (the date of the study resolutions. The colour-infrared images captured at 40 m and 50 days after sowing (date 2, when plants had 5–6 true leaves, had the highest weed detection accuracy (up to 91%. At this flight altitude, the images captured before date 2 had slightly better results than the images captured later. However, this trend changed in the visible-light images captured at 60 m and higher, which had notably better results on date 3 (57 days after sowing because of the larger size of the weed plants. Our results showed the requirements on spectral and spatial resolutions needed to generate a suitable weed map early in the growing season, as well as the best moment for the UAV image acquisition, with the ultimate objective of applying site-specific weed management operations.

  4. Quantifying efficacy and limits of unmanned aerial vehicle (UAV) technology for weed seedling detection as affected by sensor resolution.

    Science.gov (United States)

    Peña, José M; Torres-Sánchez, Jorge; Serrano-Pérez, Angélica; de Castro, Ana I; López-Granados, Francisca

    2015-03-06

    In order to optimize the application of herbicides in weed-crop systems, accurate and timely weed maps of the crop-field are required. In this context, this investigation quantified the efficacy and limitations of remote images collected with an unmanned aerial vehicle (UAV) for early detection of weed seedlings. The ability to discriminate weeds was significantly affected by the imagery spectral (type of camera), spatial (flight altitude) and temporal (the date of the study) resolutions. The colour-infrared images captured at 40 m and 50 days after sowing (date 2), when plants had 5-6 true leaves, had the highest weed detection accuracy (up to 91%). At this flight altitude, the images captured before date 2 had slightly better results than the images captured later. However, this trend changed in the visible-light images captured at 60 m and higher, which had notably better results on date 3 (57 days after sowing) because of the larger size of the weed plants. Our results showed the requirements on spectral and spatial resolutions needed to generate a suitable weed map early in the growing season, as well as the best moment for the UAV image acquisition, with the ultimate objective of applying site-specific weed management operations.

  5. High resolution metric imaging payload

    Science.gov (United States)

    Delclaud, Y.

    2017-11-01

    Alcatel Space Industries has become Europe's leader in the field of high and very high resolution optical payloads, in the frame work of earth observation system able to provide military government with metric images from space. This leadership allowed ALCATEL to propose for the export market, within a French collaboration frame, a complete space based system for metric observation.

  6. Research of aerial imaging spectrometer data acquisition technology based on USB 3.0

    Science.gov (United States)

    Huang, Junze; Wang, Yueming; He, Daogang; Yu, Yanan

    2016-11-01

    With the emergence of UAV (unmanned aerial vehicle) platform for aerial imaging spectrometer, research of aerial imaging spectrometer DAS(data acquisition system) faces new challenges. Due to the limitation of platform and other factors, the aerial imaging spectrometer DAS requires small-light, low-cost and universal. Traditional aerial imaging spectrometer DAS system is expensive, bulky, non-universal and unsupported plug-and-play based on PCIe. So that has been unable to meet promotion and application of the aerial imaging spectrometer. In order to solve these problems, the new data acquisition scheme bases on USB3.0 interface.USB3.0 can provide guarantee of small-light, low-cost and universal relying on the forward-looking technology advantage. USB3.0 transmission theory is up to 5Gbps.And the GPIF programming interface achieves 3.2Gbps of the effective theoretical data bandwidth.USB3.0 can fully meet the needs of the aerial imaging spectrometer data transmission rate. The scheme uses the slave FIFO asynchronous data transmission mode between FPGA and USB3014 interface chip. Firstly system collects spectral data from TLK2711 of high-speed serial interface chip. Then FPGA receives data in DDR2 cache after ping-pong data processing. Finally USB3014 interface chip transmits data via automatic-dma approach and uploads to PC by USB3.0 cable. During the manufacture of aerial imaging spectrometer, the DAS can achieve image acquisition, transmission, storage and display. All functions can provide the necessary test detection for aerial imaging spectrometer. The test shows that system performs stable and no data lose. Average transmission speed and storage speed of writing SSD can stabilize at 1.28Gbps. Consequently ,this data acquisition system can meet application requirements for aerial imaging spectrometer.

  7. Decentralized cooperative unmanned aerial vehicles conflict resolution by neural network-based tree search method

    Directory of Open Access Journals (Sweden)

    Jian Yang

    2016-09-01

    Full Text Available In this article, a tree search algorithm is proposed to find the near optimal conflict avoidance solutions for unmanned aerial vehicles. In the dynamic environment, the unmodeled elements, such as wind, would make UAVs deviate from nominal traces. It brings about difficulties for conflict detection and resolution. The back propagation neural networks are utilized to approximate the unmodeled dynamics of the environment. To satisfy the online planning requirement, the search length of the tree search algorithm would be limited. Therefore, the algorithm may not be able to reach the goal states in search process. The midterm reward function for assessing each node is devised, with consideration given to two factors, namely, the safe separation requirement and the mission of each unmanned aerial vehicle. The simulation examples and the comparisons with previous approaches are provided to illustrate the smooth and convincing behaviours of the proposed algorithm.

  8. Using Unmanned Aerial Vehicles (UAV for High-Resolution Reconstruction of Topography: The Structure from Motion Approach on Coastal Environments

    Directory of Open Access Journals (Sweden)

    Francesco Mancini

    2013-12-01

    Full Text Available The availability of high-resolution Digital Surface Models of coastal environments is of increasing interest for scientists involved in the study of the coastal system processes. Among the range of terrestrial and aerial methods available to produce such a dataset, this study tests the utility of the Structure from Motion (SfM approach to low-altitude aerial imageries collected by Unmanned Aerial Vehicle (UAV. The SfM image-based approach was selected whilst searching for a rapid, inexpensive, and highly automated method, able to produce 3D information from unstructured aerial images. In particular, it was used to generate a dense point cloud and successively a high-resolution Digital Surface Models (DSM of a beach dune system in Marina di Ravenna (Italy. The quality of the elevation dataset produced by the UAV-SfM was initially evaluated by comparison with point cloud generated by a Terrestrial Laser Scanning (TLS surveys. Such a comparison served to highlight an average difference in the vertical values of 0.05 m (RMS = 0.19 m. However, although the points cloud comparison is the best approach to investigate the absolute or relative correspondence between UAV and TLS methods, the assessment of geomorphic features is usually based on multi-temporal surfaces analysis, where an interpolation process is required. DSMs were therefore generated from UAV and TLS points clouds and vertical absolute accuracies assessed by comparison with a Global Navigation Satellite System (GNSS survey. The vertical comparison of UAV and TLS DSMs with respect to GNSS measurements pointed out an average distance at cm-level (RMS = 0.011 m. The successive point by point direct comparison between UAV and TLS elevations show a very small average distance, 0.015 m, with RMS = 0.220 m. Larger values are encountered in areas where sudden changes in topography are present. The UAV-based approach was demonstrated to be a straightforward one and accuracy of the vertical dataset

  9. Siamese-GAN: Learning Invariant Representations for Aerial Vehicle Image Categorization

    Directory of Open Access Journals (Sweden)

    Laila Bashmal

    2018-02-01

    Full Text Available In this paper, we present a new algorithm for cross-domain classification in aerial vehicle images based on generative adversarial networks (GANs. The proposed method, called Siamese-GAN, learns invariant feature representations for both labeled and unlabeled images coming from two different domains. To this end, we train in an adversarial manner a Siamese encoder–decoder architecture coupled with a discriminator network. The encoder–decoder network has the task of matching the distributions of both domains in a shared space regularized by the reconstruction ability, while the discriminator seeks to distinguish between them. After this phase, we feed the resulting encoded labeled and unlabeled features to another network composed of two fully-connected layers for training and classification, respectively. Experiments on several cross-domain datasets composed of extremely high resolution (EHR images acquired by manned/unmanned aerial vehicles (MAV/UAV over the cities of Vaihingen, Toronto, Potsdam, and Trento are reported and discussed.

  10. Section on High Resolution Optical Imaging (HROI)

    Data.gov (United States)

    Federal Laboratory Consortium — The Section on High Resolution Optical Imaging (HROI) develops novel technologies for studying biological processes at unprecedented speed and resolution. Research...

  11. SPECT imaging with resolution recovery

    International Nuclear Information System (INIS)

    Bronnikov, A. V.

    2011-01-01

    Single-photon emission computed tomography (SPECT) is a method of choice for imaging spatial distributions of radioisotopes. Many applications of this method are found in nuclear industry, medicine, and biomedical research. We study mathematical modeling of a micro-SPECT system by using a point-spread function (PSF) and implement an OSEM-based iterative algorithm for image reconstruction with resolution recovery. Unlike other known implementations of the OSEM algorithm, we apply en efficient computation scheme based on a useful approximation of the PSF, which ensures relatively fast computations. The proposed approach can be applied with the data acquired with any type of collimators, including parallel-beam fan-beam, cone-beam and pinhole collimators. Experimental results obtained with a micro SPECT system demonstrate high efficiency of resolution recovery. (authors)

  12. 3D Power Line Extraction from Multiple Aerial Images

    Directory of Open Access Journals (Sweden)

    Jaehong Oh

    2017-09-01

    Full Text Available Power lines are cables that carry electrical power from a power plant to an electrical substation. They must be connected between the tower structures in such a way that ensures minimum tension and sufficient clearance from the ground. Power lines can stretch and sag with the changing weather, eventually exceeding the planned tolerances. The excessive sags can then cause serious accidents, while hindering the durability of the power lines. We used photogrammetric techniques with a low-cost drone to achieve efficient 3D mapping of power lines that are often difficult to approach. Unlike the conventional image-to-object space approach, we used the object-to-image space approach using cubic grid points. We processed four strips of aerial images to automatically extract the power line points in the object space. Experimental results showed that the approach could successfully extract the positions of the power line points for power line generation and sag measurement with the elevation accuracy of a few centimeters.

  13. Autonomous aerial vehicles : guidance, control, signal and image processing platform

    International Nuclear Information System (INIS)

    Al-Jarrah, M.; Adiansyah, S.; Marji, Z. M.; Chowdhury, M. S.

    2011-01-01

    The use of unmanned systems is gaining momentum in civil applications after successful use by the armed forces around the globe. Autonomous aerial vehicles are important for providing assistance in monitoring highways, power grid lines, borders, and surveillance of critical infrastructures. It is envisioned that cargo shipping will be completely handled by UAVs by the 2025. Civil use of unmanned autonomous systems brings serious challenges. The need for cost effectiveness, reliability, operation simplicity, safety, and cooperation with human and with other agents are among these challenges. Aerial vehicles operating in the civilian aerospace is the ultimate goal which requires these systems to achieve the reliability of manned aircraft while maintaining their cost effectiveness. In this presentation the development of an autonomous fixed and rotary wing aerial vehicle will be discussed. The architecture of the system from the mission requirements to low level auto pilot control laws will be discussed. Trajectory tracking and path following guidance and control algorithms commonly used and their implementation using of the shelf low cost components will be presented. Autonomous takeo? landing is a key feature that was implemented onboard the vehicle to complete its degree of autonomy. This is implemented based on accurate air-data system designed and fused with sonar measurements, INS/GPS measurements, and vector field method guidance laws. The outcomes of the proposed research is that the AUS-UAV platform named MAZARI is capable of autonomous takeoff and landing based on a pre scheduled flight path using way point navigation and sensor fusion of the inertial navigation system (INS) and global positioning system (GPS). Several technologies need to be mastered when developing a UAV. The navigation task and the need to fuse sensory information to estimate the location of the vehicle is critical to successful autonomous vehicle. Currently extended Kalman filtering is

  14. Mapping Reflectance Anisotropy of a Potato Canopy Using Aerial Images Acquired with an Unmanned Aerial Vehicle

    Directory of Open Access Journals (Sweden)

    Peter P. J. Roosjen

    2017-04-01

    Full Text Available Viewing and illumination geometry has a strong influence on optical measurements of natural surfaces due to their anisotropic reflectance properties. Typically, cameras on-board unmanned aerial vehicles (UAVs are affected by this because of their relatively large field of view (FOV and thus large range of viewing angles. In this study, we investigated the magnitude of reflectance anisotropy effects in the 500–900 nm range, captured by a frame camera mounted on a UAV during a standard mapping flight. After orthorectification and georeferencing of the images collected by the camera, we calculated the viewing geometry of all observations of each georeferenced ground pixel, forming a dataset with multi-angular observations. We performed UAV flights on two days during the summer of 2016 over an experimental potato field where different zones in the field received different nitrogen fertilization treatments. These fertilization levels caused variation in potato plant growth and thereby differences in structural properties such as leaf area index (LAI and canopy cover. We fitted the Rahman–Pinty–Verstraete (RPV model through the multi-angular observations of each ground pixel to quantify, interpret, and visualize the anisotropy patterns in our study area. The Θ parameter of the RPV model, which controls the proportion of forward and backward scattering, showed strong correlation with canopy cover, where in general an increase in canopy cover resulted in a reduction of backward scattering intensity, indicating that reflectance anisotropy contains information on canopy structure. In this paper, we demonstrated that anisotropy data can be extracted from measurements using a frame camera, collected during a typical UAV mapping flight. Future research will focus on how to use the anisotropy signal as a source of information for estimation of physical vegetation properties.

  15. Using aerial photography and image analysis to measure changes in giant reed populations

    Science.gov (United States)

    A study was conducted along the Rio Grande in southwest Texas to evaluate color-infrared aerial photography combined with supervised image analysis to quantify changes in giant reed (Arundo donax L.) populations over a 6-year period. Aerial photographs from 2002 and 2008 of the same seven study site...

  16. Spatially explicit rangeland erosion monitoring using high-resolution digital aerial imagery

    Science.gov (United States)

    Gillan, Jeffrey K.; Karl, Jason W.; Barger, Nichole N.; Elaksher, Ahmed; Duniway, Michael C.

    2016-01-01

    Nearly all of the ecosystem services supported by rangelands, including production of livestock forage, carbon sequestration, and provisioning of clean water, are negatively impacted by soil erosion. Accordingly, monitoring the severity, spatial extent, and rate of soil erosion is essential for long-term sustainable management. Traditional field-based methods of monitoring erosion (sediment traps, erosion pins, and bridges) can be labor intensive and therefore are generally limited in spatial intensity and/or extent. There is a growing effort to monitor natural resources at broad scales, which is driving the need for new soil erosion monitoring tools. One remote-sensing technique that can be used to monitor soil movement is a time series of digital elevation models (DEMs) created using aerial photogrammetry methods. By geographically coregistering the DEMs and subtracting one surface from the other, an estimate of soil elevation change can be created. Such analysis enables spatially explicit quantification and visualization of net soil movement including erosion, deposition, and redistribution. We constructed DEMs (12-cm ground sampling distance) on the basis of aerial photography immediately before and 1 year after a vegetation removal treatment on a 31-ha Piñon-Juniper woodland in southeastern Utah to evaluate the use of aerial photography in detecting soil surface change. On average, we were able to detect surface elevation change of ± 8−9cm and greater, which was sufficient for the large amount of soil movement exhibited on the study area. Detecting more subtle soil erosion could be achieved using the same technique with higher-resolution imagery from lower-flying aircraft such as unmanned aerial vehicles. DEM differencing and process-focused field methods provided complementary information and a more complete assessment of soil loss and movement than any single technique alone. Photogrammetric DEM differencing could be used as a technique to

  17. Single Image Super Resolution via Sparse Reconstruction

    NARCIS (Netherlands)

    Kruithof, M.C.; Eekeren, A.W.M. van; Dijk, J.; Schutte, K.

    2012-01-01

    High resolution sensors are required for recognition purposes. Low resolution sensors, however, are still widely used. Software can be used to increase the resolution of such sensors. One way of increasing the resolution of the images produced is using multi-frame super resolution algorithms.

  18. Comparison of Small Unmanned Aerial Vehicles Performance Using Image Processing

    Directory of Open Access Journals (Sweden)

    Esteban Cano

    2017-01-01

    Full Text Available Precision agriculture is a farm management technology that involves sensing and then responding to the observed variability in the field. Remote sensing is one of the tools of precision agriculture. The emergence of small unmanned aerial vehicles (sUAV have paved the way to accessible remote sensing tools for farmers. This paper describes the development of an image processing approach to compare two popular off-the-shelf sUAVs: 3DR Iris+ and DJI Phantom 2. Both units are equipped with a camera gimbal attached with a GoPro camera. The comparison of the two sUAV involves a hovering test and a rectilinear motion test. In the hovering test, the sUAV was allowed to hover over a known object and images were taken every quarter of a second for two minutes. For the image processing evaluation, the position of the object in the images was measured and this was used to assess the stability of the sUAV while hovering. In the rectilinear test, the sUAV was allowed to follow a straight path and images of a lined track were acquired. The lines on the images were then measured on how accurate the sUAV followed the path. The hovering test results show that the 3DR Iris+ had a maximum position deviation of 0.64 m (0.126 m root mean square RMS displacement while the DJI Phantom 2 had a maximum deviation of 0.79 m (0.150 m RMS displacement. In the rectilinear motion test, the maximum displacement for the 3DR Iris+ and the DJI phantom 2 were 0.85 m (0.134 m RMS displacement and 0.73 m (0.372 m RMS displacement. These results demonstrated that the two sUAVs performed well in both the hovering test and the rectilinear motion test and thus demonstrated that both sUAVs can be used for civilian applications such as agricultural monitoring. The results also showed that the developed image processing approach can be used to evaluate performance of a sUAV and has the potential to be used as another feedback control parameter for autonomous navigation.

  19. Mapping reflectance anisotropy of a potato canopy using aerial images acquired with an unmanned aerial vehicle

    NARCIS (Netherlands)

    Roosjen, Peter; Suomalainen, Juha; Bartholomeus, Harm; Kooistra, Lammert; Clevers, Jan

    2017-01-01

    Viewing and illumination geometry has a strong influence on optical measurements of natural surfaces due to their anisotropic reflectance properties. Typically, cameras on-board unmanned aerial vehicles (UAVs) are affected by this because of their relatively large field of view (FOV) and thus large

  20. Aerial 3D display by use of a 3D-shaped screen with aerial imaging by retro-reflection (AIRR)

    Science.gov (United States)

    Kurokawa, Nao; Ito, Shusei; Yamamoto, Hirotsugu

    2017-06-01

    The purpose of this paper is to realize an aerial 3D display. We design optical system that employs a projector below a retro-reflector and a 3D-shaped screen. A floating 3D image is formed with aerial imaging by retro-reflection (AIRR). Our proposed system is composed of a 3D-shaped screen, a projector, a quarter-wave retarder, a retro-reflector, and a reflective polarizer. Because AIRR forms aerial images that are plane-symmetric of the light sources regarding the reflective polarizer, the shape of the 3D screen is inverted from a desired aerial 3D image. In order to expand viewing angle, the 3D-shaped screen is surrounded by a retro-reflector. In order to separate the aerial image from reflected lights on the retro- reflector surface, the retro-reflector is tilted by 30 degrees. A projector is located below the retro-reflector at the same height of the 3D-shaped screen. The optical axis of the projector is orthogonal to the 3D-shaped screen. Scattered light on the 3D-shaped screen forms the aerial 3D image. In order to demonstrate the proposed optical design, a corner-cube-shaped screen is used for the 3D-shaped screen. Thus, the aerial 3D image is a cube that is floating above the reflective polarizer. For example, an aerial green cube is formed by projecting a calculated image on the 3D-shaped screen. The green cube image is digitally inverted in depth by our developed software. Thus, we have succeeded in forming aerial 3D image with our designed optical system.

  1. Pre-harvest assessment of perennial weeds in cereals based on images from unmanned aerial systems (UAS)

    DEFF Research Database (Denmark)

    Egilsson, Jon; Pedersen, Kim Steenstrup; Olsen, Søren Ingvor

    2015-01-01

    Unmanned aerial systems (UAS) are able to deliver images of agricultural fields of high spatial and temporal resolution. It is, however, not trivial to extract quantitative information about weed infestations from images. This study contributes to weed research by using state-of-the-art computer....... In order to provide ground truth prior to the modeling phase in Python, a subset of 600 images was annotated by experts with 16000 regions of weeds or crop. Following this, images were segmented into regions with weeds or crop by subdividing each image into 64 by 64 pixel patches and classifying each patch...... as either crop or weed. A collection of geo-referenced segmented images may subsequently be used to map weed occurrences in fields. To find a robust and fully automated assessment method both texture and color information was used to build a number of different competing weed-crop classifiers, including...

  2. Robust vehicle detection in aerial images based on salient region selection and superpixel classification

    Science.gov (United States)

    Sahli, Samir; Duval, Pierre-Luc; Sheng, Yunlong; Lavigne, Daniel A.

    2011-05-01

    For detecting vehicles in large scale aerial images we first used a non-parametric method proposed recently by Rosin to define the regions of interest, where the vehicles appear with dense edges. The saliency map is a sum of distance transforms (DT) of a set of edges maps, which are obtained by a threshold decomposition of the gradient image with a set of thresholds. A binary mask for highlighting the regions of interest is then obtained by a moment-preserving thresholding of the normalized saliency map. Secondly, the regions of interest were over-segmented by the SLIC superpixels proposed recently by Achanta et al. to cluster pixels into the color constancy sub-regions. In the aerial images of 11.2 cm/pixel resolution, the vehicles in general do not exceed 20 x 40 pixels. We introduced a size constraint to guarantee no superpixels exceed the size of a vehicle. The superpixels were then classified to vehicle or non-vehicle by the Support Vector Machine (SVM), in which the Scale Invariant Feature Transform (SIFT) features and the Linear Binary Pattern (LBP) texture features were used. Both features were extracted at two scales with two size patches. The small patches capture local structures and the larger patches include the neighborhood information. Preliminary results show a significant gain in the detection. The vehicles were detected with a dense concentration of the vehicle-class superpixels. Even dark color cars were successfully detected. A validation process will follow to reduce the presence of isolated false alarms in the background.

  3. Structure-from-Motion Using Historical Aerial Images to Analyse Changes in Glacier Surface Elevation

    Directory of Open Access Journals (Sweden)

    Nico Mölg

    2017-10-01

    Full Text Available The application of structure-from-motion (SfM to generate digital terrain models (DTMs derived from different image sources has strongly increased, the major reason for this being that processing is substantially easier with SfM than with conventional photogrammetry. To test the functionality in a demanding environment, we applied SfM and conventional photogrammetry to archival aerial images from Zmuttgletscher, a mountain glacier in Switzerland, for nine dates between 1946 and 2005 using the most popular software packages, and compared the results regarding bundle adjustment and final DTM quality. The results suggest that by using SfM it is possible to produce DTMs of similar quality as with conventional photogrammetry. Higher point cloud density and less noise allow a higher ground resolution of the final DTM, and the time effort from the user is 3–6 times smaller, while the controls of the commercial software packages Agisoft PhotoScan (Version 1.2; Agisoft, St. Petersburg, Russia and Pix4Dmapper (Version 3.0; Pix4D, Lausanne, Switzerland are limited in comparison to ERDAS photogrammetry. SfM performs less reliably when few images with little overlap are processed. Even though SfM facilitates the largely automated production of high quality DTMs, the user is not exempt from a thorough quality check, at best with reference data where available. The resulting DTM time series revealed an average change in surface elevation at the glacier tongue of −67.0 ± 5.3 m. The spatial pattern of changes over time reflects the influence of flow dynamics and the melt of clean ice and that under debris cover. With continued technological advances, we expect to see an increasing use of SfM in glaciology for a variety of purposes, also in processing archival aerial imagery.

  4. Ultrahigh Resolution 3-Dimensional Imaging, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Southwest Sciences proposes to develop innovative instrumentation for the rapid, 3-dimensional imaging of biological tissues with cellular resolution. Our approach...

  5. Use of Aerial Hyperspectral Imaging For Monitoring Forest Health

    Science.gov (United States)

    Milton O. Smith; Nolan J. Hess; Stephen Gulick; Lori G. Eckhardt; Roger D. Menard

    2004-01-01

    This project evaluates the effectiveness of aerial hyperspectral digital imagery in the assessment of forest health of loblolly stands in central Alabama. The imagery covers 50 square miles, in Bibb and Hale Counties, south of Tuscaloosa, AL, which includes intensive managed forest industry sites and National Forest lands with multiple use objectives. Loblolly stands...

  6. LiDAR The Generation of Automatic Mapping for Buildings, Using High Spatial Resolution Digital Vertical Aerial Photography and LiDAR Point Clouds

    Directory of Open Access Journals (Sweden)

    William Barragán Zaque

    2015-06-01

    Full Text Available The aim of this paper is to generate photogrammetrie products and to automatically map buildings in the area of interest in vector format. The research was conducted Bogotá using high resolution digital vertical aerial photographs and point clouds obtained using LIDAR technology. Image segmentation was also used, alongside radiometric and geometric digital processes. The process took into account aspects including building height, segmentation algorithms, and spectral band combination. The results had an effectiveness of 97.2 % validated through ground-truthing.

  7. AERIAL IMAGES FROM AN UAV SYSTEM: 3D MODELING AND TREE SPECIES CLASSIFICATION IN A PARK AREA

    Directory of Open Access Journals (Sweden)

    R. Gini

    2012-07-01

    Full Text Available The use of aerial imagery acquired by Unmanned Aerial Vehicles (UAVs is scheduled within the FoGLIE project (Fruition of Goods Landscape in Interactive Environment: it starts from the need to enhance the natural, artistic and cultural heritage, to produce a better usability of it by employing audiovisual movable systems of 3D reconstruction and to improve monitoring procedures, by using new media for integrating the fruition phase with the preservation ones. The pilot project focus on a test area, Parco Adda Nord, which encloses various goods' types (small buildings, agricultural fields and different tree species and bushes. Multispectral high resolution images were taken by two digital compact cameras: a Pentax Optio A40 for RGB photos and a Sigma DP1 modified to acquire the NIR band. Then, some tests were performed in order to analyze the UAV images' quality with both photogrammetric and photo-interpretation purposes, to validate the vector-sensor system, the image block geometry and to study the feasibility of tree species classification. Many pre-signalized Control Points were surveyed through GPS to allow accuracy analysis. Aerial Triangulations (ATs were carried out with photogrammetric commercial software, Leica Photogrammetry Suite (LPS and PhotoModeler, with manual or automatic selection of Tie Points, to pick out pros and cons of each package in managing non conventional aerial imagery as well as the differences in the modeling approach. Further analysis were done on the differences between the EO parameters and the corresponding data coming from the on board UAV navigation system.

  8. A Robust Transform Estimator Based on Residual Analysis and Its Application on UAV Aerial Images

    Directory of Open Access Journals (Sweden)

    Guorong Cai

    2018-02-01

    Full Text Available Estimating the transformation between two images from the same scene is a fundamental step for image registration, image stitching and 3D reconstruction. State-of-the-art methods are mainly based on sorted residual for generating hypotheses. This scheme has acquired encouraging results in many remote sensing applications. Unfortunately, mainstream residual based methods may fail in estimating the transform between Unmanned Aerial Vehicle (UAV low altitude remote sensing images, due to the fact that UAV images always have repetitive patterns and severe viewpoint changes, which produce lower inlier rate and higher pseudo outlier rate than other tasks. We performed extensive experiments and found the main reason is that these methods compute feature pair similarity within a fixed window, making them sensitive to the size of residual window. To solve this problem, three schemes that based on the distribution of residuals are proposed, which are called Relational Window (RW, Sliding Window (SW, Reverse Residual Order (RRO, respectively. Specially, RW employs a relaxation residual window size to evaluate the highest similarity within a relaxation model length. SW fixes the number of overlap models while varying the length of window size. RRO takes the permutation of residual values into consideration to measure similarity, not only including the number of overlap structures, but also giving penalty to reverse number within the overlap structures. Experimental results conducted on our own built UAV high resolution remote sensing images show that the proposed three strategies all outperform traditional methods in the presence of severe perspective distortion due to viewpoint change.

  9. Mapping Urban Tree Canopy Coverage and Structure using Data Fusion of High Resolution Satellite Imagery and Aerial Lidar

    Science.gov (United States)

    Elmes, A.; Rogan, J.; Williams, C. A.; Martin, D. G.; Ratick, S.; Nowak, D.

    2015-12-01

    Urban tree canopy (UTC) coverage is a critical component of sustainable urban areas. Trees provide a number of important ecosystem services, including air pollution mitigation, water runoff control, and aesthetic and cultural values. Critically, urban trees also act to mitigate the urban heat island (UHI) effect by shading impervious surfaces and via evaporative cooling. The cooling effect of urban trees can be seen locally, with individual trees reducing home HVAC costs, and at a citywide scale, reducing the extent and magnitude of an urban areas UHI. In order to accurately model the ecosystem services of a given urban forest, it is essential to map in detail the condition and composition of these trees at a fine scale, capturing individual tree crowns and their vertical structure. This paper presents methods for delineating UTC and measuring canopy structure at fine spatial resolution (body of methods, relying on a data fusion method to combine the information contained in high resolution WorldView-3 satellite imagery and aerial lidar data using an object-based image classification approach. The study area, Worcester, MA, has recently undergone a large-scale tree removal and reforestation program, following a pest eradication effort. Therefore, the urban canopy in this location provides a wide mix of tree age class and functional type, ideal for illustrating the effectiveness of the proposed methods. Early results show that the object-based classifier is indeed capable of identifying individual tree crowns, while continued research will focus on extracting crown structural characteristics using lidar-derived metrics. Ultimately, the resulting fine resolution UTC map will be compared with previously created UTC maps of the same area but for earlier dates, producing a canopy change map corresponding to the Worcester area tree removal and replanting effort.

  10. Integrating dynamic and distributed compressive sensing techniques to enhance image quality of the compressive line sensing system for unmanned aerial vehicles application

    Science.gov (United States)

    Ouyang, Bing; Hou, Weilin; Caimi, Frank M.; Dalgleish, Fraser R.; Vuorenkoski, Anni K.; Gong, Cuiling

    2017-07-01

    The compressive line sensing imaging system adopts distributed compressive sensing (CS) to acquire data and reconstruct images. Dynamic CS uses Bayesian inference to capture the correlated nature of the adjacent lines. An image reconstruction technique that incorporates dynamic CS in the distributed CS framework was developed to improve the quality of reconstructed images. The effectiveness of the technique was validated using experimental data acquired in an underwater imaging test facility. Results that demonstrate contrast and resolution improvements will be presented. The improved efficiency is desirable for unmanned aerial vehicles conducting long-duration missions.

  11. Atomic resolution images of graphite in air

    Energy Technology Data Exchange (ETDEWEB)

    Grigg, D.A.; Shedd, G.M.; Griffis, D.; Russell, P.E.

    1988-12-01

    One sample used for proof of operation for atomic resolution in STM is highly oriented pyrolytic graphite (HOPG). This sample has been imaged with many different STM`s obtaining similar results. Atomic resolution images of HOPG have now been obtained using an STM designed and built at the Precision Engineering Center. This paper discusses the theoretical predictions and experimental results obtained in imaging of HOPG.

  12. Method of transmission of dynamic multibit digital images from micro-unmanned aerial vehicles

    Science.gov (United States)

    Petrov, E. P.; Kharina, N. L.

    2018-01-01

    In connection with successful usage of nanotechnologies in remote sensing great attention is paid to the systems in micro-unmanned aerial vehicles (MUAVs) capable to provide high spatial resolution of dynamic multibit digital images (MDI). Limited energy resources on board the MUAV do not allow transferring a large amount of video information in the shortest possible time. It keeps back the broad development of MUAV. The search for methods to shorten the transmission time of dynamic MDIs from MUAV over the radio channel leads to the methods of MDI compression without computational operations onboard the MUAV. The known compression codecs of video information can not be applied because of the limited energy resources. In this paper we propose a method for reducing the transmission time of dynamic MDIs without computational operations and distortions onboard the MUAV. To develop the method a mathematical apparatus of the theory of conditional Markov processes with discrete arguments was used. On its basis a mathematical model for the transformation of the MDI represented by binary images (BI) in the MDI, consisting of groups of neighboring BIs (GBI) transmitted by multiphase (MP) signals, is constructed. The algorithm for multidimensional nonlinear filtering of MP signals is synthesized, realizing the statistical redundancy of the MDI to compensate for the noise stability losses caused by the use of MP signals.

  13. STUDY OF AUTOMATIC IMAGE RECTIFICATION AND REGISTRATION OF SCANNED HISTORICAL AERIAL PHOTOGRAPHS

    Directory of Open Access Journals (Sweden)

    H. R. Chen

    2016-06-01

    Full Text Available Historical aerial photographs directly provide good evidences of past times. The Research Center for Humanities and Social Sciences (RCHSS of Taiwan Academia Sinica has collected and scanned numerous historical maps and aerial images of Taiwan and China. Some maps or images have been geo-referenced manually, but most of historical aerial images have not been registered since there are no GPS or IMU data for orientation assisting in the past. In our research, we developed an automatic process of matching historical aerial images by SIFT (Scale Invariant Feature Transform for handling the great quantity of images by computer vision. SIFT is one of the most popular method of image feature extracting and matching. This algorithm extracts extreme values in scale space into invariant image features, which are robust to changing in rotation scale, noise, and illumination. We also use RANSAC (Random sample consensus to remove outliers, and obtain good conjugated points between photographs. Finally, we manually add control points for registration through least square adjustment based on collinear equation. In the future, we can use image feature points of more photographs to build control image database. Every new image will be treated as query image. If feature points of query image match the features in database, it means that the query image probably is overlapped with control images.With the updating of database, more and more query image can be matched and aligned automatically. Other research about multi-time period environmental changes can be investigated with those geo-referenced temporal spatial data.

  14. True Orthophoto Generation from Aerial Frame Images and LiDAR Data: An Update

    Directory of Open Access Journals (Sweden)

    Hamid Gharibi

    2018-04-01

    Full Text Available Image spectral and Light Detection and Ranging (LiDAR positional information can be related through the orthophoto generation process. Orthophotos have a uniform scale and represent all objects in their correct planimetric locations. However, orthophotos generated using conventional methods suffer from an artifact known as the double-mapping effect that occurs in areas occluded by tall objects. The double-mapping problem can be resolved through the commonly known true orthophoto generation procedure, in which an occlusion detection process is incorporated. This paper presents a review of occlusion detection methods, from which three techniques are compared and analyzed using experimental results. The paper also describes a framework for true orthophoto production based on an angle-based occlusion detection method. To improve the performance of the angle-based technique, two modifications to this method are introduced. These modifications, which aim at resolving false visibilities reported within the angle-based occlusion detection process, are referred to as occlusion extension and radial section overlap. A weighted averaging approach is also proposed to mitigate the seamline effect and spectral dissimilarity that may appear in true orthophoto mosaics. Moreover, true orthophotos generated from high-resolution aerial images and high-density LiDAR data using the updated version of angle-based methodology are illustrated for two urban study areas. To investigate the potential of image matching techniques in producing true orthophotos and point clouds, a comparison between the LiDAR-based and image-matching-based true orthophotos and digital surface models (DSMs for an urban study area is also presented in this paper. Among the investigated occlusion detection methods, the angle-based technique demonstrated a better performance in terms of output and running time. The LiDAR-based true orthophotos and DSMs showed higher qualities compared to their

  15. Advanced Tie Feature Matching for the Registration of Mobile Mapping Imaging Data and Aerial Imagery

    Science.gov (United States)

    Jende, P.; Peter, M.; Gerke, M.; Vosselman, G.

    2016-06-01

    Mobile Mapping's ability to acquire high-resolution ground data is opposing unreliable localisation capabilities of satellite-based positioning systems in urban areas. Buildings shape canyons impeding a direct line-of-sight to navigation satellites resulting in a deficiency to accurately estimate the mobile platform's position. Consequently, acquired data products' positioning quality is considerably diminished. This issue has been widely addressed in the literature and research projects. However, a consistent compliance of sub-decimetre accuracy as well as a correction of errors in height remain unsolved. We propose a novel approach to enhance Mobile Mapping (MM) image orientation based on the utilisation of highly accurate orientation parameters derived from aerial imagery. In addition to that, the diminished exterior orientation parameters of the MM platform will be utilised as they enable the application of accurate matching techniques needed to derive reliable tie information. This tie information will then be used within an adjustment solution to correct affected MM data. This paper presents an advanced feature matching procedure as a prerequisite to the aforementioned orientation update. MM data is ortho-projected to gain a higher resemblance to aerial nadir data simplifying the images' geometry for matching. By utilising MM exterior orientation parameters, search windows may be used in conjunction with a selective keypoint detection and template matching. Originating from different sensor systems, however, difficulties arise with respect to changes in illumination, radiometry and a different original perspective. To respond to these challenges for feature detection, the procedure relies on detecting keypoints in only one image. Initial tests indicate a considerable improvement in comparison to classic detector/descriptor approaches in this particular matching scenario. This method leads to a significant reduction of outliers due to the limited availability

  16. Monitoring the Invasion of Spartina alterniflora Using Very High Resolution Unmanned Aerial Vehicle Imagery in Beihai, Guangxi (China

    Directory of Open Access Journals (Sweden)

    Huawei Wan

    2014-01-01

    Full Text Available Spartina alterniflora was introduced to Beihai, Guangxi (China, for ecological engineering purposes in 1979. However, the exceptional adaptability and reproductive ability of this species have led to its extensive dispersal into other habitats, where it has had a negative impact on native species and threatens the local mangrove and mudflat ecosystems. To obtain the distribution and spread of Spartina alterniflora, we collected HJ-1 CCD imagery from 2009 and 2011 and very high resolution (VHR imagery from the unmanned aerial vehicle (UAV. The invasion area of Spartina alterniflora was 357.2 ha in 2011, which increased by 19.07% compared with the area in 2009. A field survey was conducted for verification and the total accuracy was 94.0%. The results of this paper show that VHR imagery can provide details on distribution, progress, and early detection of Spartina alterniflora invasion. OBIA, object based image analysis for remote sensing (RS detection method, can enable control measures to be more effective, accurate, and less expensive than a field survey of the invasive population.

  17. Super-Resolution of Plant Disease Images for the Acceleration of Image-based Phenotyping and Vigor Diagnosis in Agriculture.

    Science.gov (United States)

    Yamamoto, Kyosuke; Togami, Takashi; Yamaguchi, Norio

    2017-11-06

    Unmanned aerial vehicles (UAVs or drones) are a very promising branch of technology, and they have been utilized in agriculture-in cooperation with image processing technologies-for phenotyping and vigor diagnosis. One of the problems in the utilization of UAVs for agricultural purposes is the limitation in flight time. It is necessary to fly at a high altitude to capture the maximum number of plants in the limited time available, but this reduces the spatial resolution of the captured images. In this study, we applied a super-resolution method to the low-resolution images of tomato diseases to recover detailed appearances, such as lesions on plant organs. We also conducted disease classification using high-resolution, low-resolution, and super-resolution images to evaluate the effectiveness of super-resolution methods in disease classification. Our results indicated that the super-resolution method outperformed conventional image scaling methods in spatial resolution enhancement of tomato disease images. The results of disease classification showed that the accuracy attained was also better by a large margin with super-resolution images than with low-resolution images. These results indicated that our approach not only recovered the information lost in low-resolution images, but also exerted a beneficial influence on further image analysis. The proposed approach will accelerate image-based phenotyping and vigor diagnosis in the field, because it not only saves time to capture images of a crop in a cultivation field but also secures the accuracy of these images for further analysis.

  18. Super-Resolution of Plant Disease Images for the Acceleration of Image-based Phenotyping and Vigor Diagnosis in Agriculture

    Directory of Open Access Journals (Sweden)

    Kyosuke Yamamoto

    2017-11-01

    Full Text Available Unmanned aerial vehicles (UAVs or drones are a very promising branch of technology, and they have been utilized in agriculture—in cooperation with image processing technologies—for phenotyping and vigor diagnosis. One of the problems in the utilization of UAVs for agricultural purposes is the limitation in flight time. It is necessary to fly at a high altitude to capture the maximum number of plants in the limited time available, but this reduces the spatial resolution of the captured images. In this study, we applied a super-resolution method to the low-resolution images of tomato diseases to recover detailed appearances, such as lesions on plant organs. We also conducted disease classification using high-resolution, low-resolution, and super-resolution images to evaluate the effectiveness of super-resolution methods in disease classification. Our results indicated that the super-resolution method outperformed conventional image scaling methods in spatial resolution enhancement of tomato disease images. The results of disease classification showed that the accuracy attained was also better by a large margin with super-resolution images than with low-resolution images. These results indicated that our approach not only recovered the information lost in low-resolution images, but also exerted a beneficial influence on further image analysis. The proposed approach will accelerate image-based phenotyping and vigor diagnosis in the field, because it not only saves time to capture images of a crop in a cultivation field but also secures the accuracy of these images for further analysis.

  19. Multi-temporal high resolution monitoring of debris-covered glaciers using unmanned aerial vehicles

    Science.gov (United States)

    Kraaijenbrink, Philip; Immerzeel, Walter; de Jong, Steven; Shea, Joseph; Pellicciotti, Francesca; Meijer, Sander; Shresta, Arun

    2016-04-01

    Debris-covered glaciers in the Himalayas are relatively unstudied due to the difficulties in fieldwork caused by the inaccessible terrain and the presence of debris layers, which complicate in situ measurements. To overcome these difficulties an unmanned aerial vehicle (UAV) has been deployed multiple times over two debris covered glaciers in the Langtang catchment, located in the Nepalese Himalayas. Using differential GPS measurements and the Structure for Motion algorithm the UAV imagery was processed into accurate high-resolution digital elevation models and orthomosaics for both pre- and post-monsoon periods. These data were successfully used to estimate seasonal surface flow and mass wasting by using cross-correlation feature tracking and DEM differencing techniques. The results reveal large heterogeneity in mass loss and surface flow over the glacier surfaces, which are primarily caused by the presence of surface features such as ice cliffs and supra-glacial lakes. Accordingly, we systematically analyze those features using an object-based approach and relate their characteristics to the observed dynamics. We show that ice cliffs and supra-glacial lakes are contributing to a significant portion of the melt water of debris covered glaciers and we conclude that UAVs have great potential in understanding the key surface processes that remain largely undetected by using satellite remote sensing.

  20. High-resolution sensing for precision agriculture: from Earth-observing satellites to unmanned aerial vehicles

    Science.gov (United States)

    McCabe, Matthew F.; Houborg, Rasmus; Lucieer, Arko

    2016-10-01

    With global population projected to approach 9 billion by 2050, it has been estimated that a 40% increase in cereal production will be required to satisfy the worlds growing nutritional demands. Any such increases in agricultural productivity are likely to occur within a system that has limited room for growth and in a world with a climate that is different from that of today. Fundamental to achieving food and water security, is the capacity to monitor the health and condition of agricultural systems. While space-agency based satellites have provided the backbone for earth observation over the last few decades, many developments in the field of high-resolution earth observation have been advanced by the commercial sector. These advances relate not just to technological developments in the use of unmanned aerial vehicles (UAVs), but also the advent of nano-satellite constellations that offer a radical shift in the way earth observations are now being retrieved. Such technologies present opportunities for improving our description of the water, energy and carbon cycles. Efforts towards developing new observational techniques and interpretative frameworks are required to provide the tools and information needed to improve the management and security of agricultural and related sectors. These developments are one of the surest ways to better manage, protect and preserve national food and water resources. Here we review the capabilities of recently deployed satellite systems and UAVs and examine their potential for application in precision agriculture.

  1. High-resolution sensing for precision agriculture: from Earth-observing satellites to unmanned aerial vehicles

    KAUST Repository

    McCabe, Matthew

    2016-10-25

    With global population projected to approach 9 billion by 2050, it has been estimated that a 40% increase in cereal production will be required to satisfy the worlds growing nutritional demands. Any such increases in agricultural productivity are likely to occur within a system that has limited room for growth and in a world with a climate that is different from that of today. Fundamental to achieving food and water security, is the capacity to monitor the health and condition of agricultural systems. While space-Agency based satellites have provided the backbone for earth observation over the last few decades, many developments in the field of high-resolution earth observation have been advanced by the commercial sector. These advances relate not just to technological developments in the use of unmanned aerial vehicles (UAVs), but also the advent of nano-satellite constellations that offer a radical shift in the way earth observations are now being retrieved. Such technologies present opportunities for improving our description of the water, energy and carbon cycles. Efforts towards developing new observational techniques and interpretative frameworks are required to provide the tools and information needed to improve the management and security of agricultural and related sectors. These developments are one of the surest ways to better manage, protect and preserve national food and water resources. Here we review the capabilities of recently deployed satellite systems and UAVs and examine their potential for application in precision agriculture.

  2. NEAR REAL-TIME GEOREFERENCE OF UMANNED AERIAL VEHICLE IMAGES FOR POST-EARTHQUAKE RESPONSE

    OpenAIRE

    Wang, S.; Wang, X.; Dou, A.; Yuan, X.; Ding, L.; Ding, X.

    2018-01-01

    The rapid collection of Unmanned Aerial Vehicle (UAV) remote sensing images plays an important role in the fast submitting disaster information and the monitored serious damaged objects after the earthquake. However, for hundreds of UAV images collected in one flight sortie, the traditional data processing methods are image stitching and three-dimensional reconstruction, which take one to several hours, and affect the speed of disaster response. If the manual searching method is employed, we ...

  3. Semiconductor crystal high resolution imager

    Science.gov (United States)

    Levin, Craig S. (Inventor); Matteson, James (Inventor)

    2011-01-01

    A radiation imaging device (10). The radiation image device (10) comprises a subject radiation station (12) producing photon emissions (14), and at least one semiconductor crystal detector (16) arranged in an edge-on orientation with respect to the emitted photons (14) to directly receive the emitted photons (14) and produce a signal. The semiconductor crystal detector (16) comprises at least one anode and at least one cathode that produces the signal in response to the emitted photons (14).

  4. Color image guided depth image super resolution using fusion filter

    Science.gov (United States)

    He, Jin; Liang, Bin; He, Ying; Yang, Jun

    2018-04-01

    Depth cameras are currently playing an important role in many areas. However, most of them can only obtain lowresolution (LR) depth images. Color cameras can easily provide high-resolution (HR) color images. Using color image as a guide image is an efficient way to get a HR depth image. In this paper, we propose a depth image super resolution (SR) algorithm, which uses a HR color image as a guide image and a LR depth image as input. We use the fusion filter of guided filter and edge based joint bilateral filter to get HR depth image. Our experimental results on Middlebury 2005 datasets show that our method can provide better quality in HR depth images both numerically and visually.

  5. High Resolution Aerial Photography of the Main Eight Hawaiian Islands, 2000

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Aerial photographs were acquired for the Main Eight Hawaiian Islands Benthic Mapping Project in 2000 by NOAA Aircraft Operation Centers aircraft and National...

  6. Classification of high resolution satellite images

    OpenAIRE

    Karlsson, Anders

    2003-01-01

    In this thesis the Support Vector Machine (SVM)is applied on classification of high resolution satellite images. Sveral different measures for classification, including texture mesasures, 1st order statistics, and simple contextual information were evaluated. Additionnally, the image was segmented, using an enhanced watershed method, in order to improve the classification accuracy.

  7. Robust Vehicle Detection in Aerial Images Based on Cascaded Convolutional Neural Networks.

    Science.gov (United States)

    Zhong, Jiandan; Lei, Tao; Yao, Guangle

    2017-11-24

    Vehicle detection in aerial images is an important and challenging task. Traditionally, many target detection models based on sliding-window fashion were developed and achieved acceptable performance, but these models are time-consuming in the detection phase. Recently, with the great success of convolutional neural networks (CNNs) in computer vision, many state-of-the-art detectors have been designed based on deep CNNs. However, these CNN-based detectors are inefficient when applied in aerial image data due to the fact that the existing CNN-based models struggle with small-size object detection and precise localization. To improve the detection accuracy without decreasing speed, we propose a CNN-based detection model combining two independent convolutional neural networks, where the first network is applied to generate a set of vehicle-like regions from multi-feature maps of different hierarchies and scales. Because the multi-feature maps combine the advantage of the deep and shallow convolutional layer, the first network performs well on locating the small targets in aerial image data. Then, the generated candidate regions are fed into the second network for feature extraction and decision making. Comprehensive experiments are conducted on the Vehicle Detection in Aerial Imagery (VEDAI) dataset and Munich vehicle dataset. The proposed cascaded detection model yields high performance, not only in detection accuracy but also in detection speed.

  8. Road Extraction and Car Detection from Aerial Image Using Intensity and Color

    Directory of Open Access Journals (Sweden)

    Vahid Ghods

    2011-07-01

    Full Text Available In this paper a new automatic approach to road extraction from aerial images is proposed. The initialization strategies are based on the intensity, color, and Hough transform. After road elements extraction, chain codes are calculated. In the last step, using shadow, cars on the roads are detected. We implemented our method on the 25 images from "Google Earth" database. The experiments show an increase in both the completeness and the quality indexes for the extracted road.

  9. Resolution enhancement in medical ultrasound imaging.

    Science.gov (United States)

    Ploquin, Marie; Basarab, Adrian; Kouamé, Denis

    2015-01-01

    Image resolution enhancement is a problem of considerable interest in all medical imaging modalities. Unlike general purpose imaging or video processing, for a very long time, medical image resolution enhancement has been based on optimization of the imaging devices. Although some recent works purport to deal with image postprocessing, much remains to be done regarding medical image enhancement via postprocessing, especially in ultrasound imaging. We face a resolution improvement issue in the case of medical ultrasound imaging. We propose to investigate this problem using multidimensional autoregressive (AR) models. Noting that the estimation of the envelope of an ultrasound radio frequency (RF) signal is very similar to the estimation of classical Fourier-based power spectrum estimation, we theoretically show that a domain change and a multidimensional AR model can be used to achieve super-resolution in ultrasound imaging provided the order is estimated correctly. Here, this is done by means of a technique that simultaneously estimates the order and the parameters of a multidimensional model using relevant regression matrix factorization. Doing so, the proposed method specifically fits ultrasound imaging and provides an estimated envelope. Moreover, an expression that links the theoretical image resolution to both the image acquisition features (such as the point spread function) and a postprocessing feature (the AR model) order is derived. The overall contribution of this work is threefold. First, it allows for automatic resolution improvement. Through a simple model and without any specific manual algorithmic parameter tuning, as is used in common methods, the proposed technique simply and exclusively uses the ultrasound RF signal as input and provides the improved B-mode as output. Second, it allows for the a priori prediction of the improvement in resolution via the knowledge of the parametric model order before actual processing. Finally, to achieve the

  10. Unmanned Aerial Vehicles for Photogrammetry: Analysis of Orthophoto Images over the Territory of Lithuania

    Directory of Open Access Journals (Sweden)

    J. Suziedelyte Visockiene

    2016-01-01

    Full Text Available It has been recently observed that aircrafts tend to be replaced by light, simple structure unmanned aerial vehicles (UAV or mini unmanned aerial vehicles (MUAV with the purpose of updating the field of aerial photogrammetry. The built-in digital photo camera takes images of the Earth’s surface. To satisfy the photogrammetric requirements of the photographic images, it is necessary to carry out the terrestrial project planning of the flight path before the flight, to select the appropriate flying height, the time for acquiring images, the speed of the UAV, and other parameters. The paper presents the results of project calculations concerning the UAV flights and the analysis of the terrestrial images acquired during the field-testing flights. The experience carried out so far in the Lithuanian landscape is shown. The taken images have been processed by PhotoMod photogrammetric system. The paper presents the results of calculation of the project values of the UAV flights taking the images by digital camera Canon S100 and the analysis of the possibilities of the UAV orthophoto images’ mode.

  11. Application of machine learning for the evaluation of turfgrass plots using aerial images

    Science.gov (United States)

    Ding, Ke; Raheja, Amar; Bhandari, Subodh; Green, Robert L.

    2016-05-01

    Historically, investigation of turfgrass characteristics have been limited to visual ratings. Although relevant information may result from such evaluations, final inferences may be questionable because of the subjective nature in which the data is collected. Recent advances in computer vision techniques allow researchers to objectively measure turfgrass characteristics such as percent ground cover, turf color, and turf quality from the digital images. This paper focuses on developing a methodology for automated assessment of turfgrass quality from aerial images. Images of several turfgrass plots of varying quality were gathered using a camera mounted on an unmanned aerial vehicle. The quality of these plots were also evaluated based on visual ratings. The goal was to use the aerial images to generate quality evaluations on a regular basis for the optimization of water treatment. Aerial images are used to train a neural network so that appropriate features such as intensity, color, and texture of the turfgrass are extracted from these images. Neural network is a nonlinear classifier commonly used in machine learning. The output of the neural network trained model is the ratings of the grass, which is compared to the visual ratings. Currently, the quality and the color of turfgrass, measured as the greenness of the grass, are evaluated. The textures are calculated using the Gabor filter and co-occurrence matrix. Other classifiers such as support vector machines and simpler linear regression models such as Ridge regression and LARS regression are also used. The performance of each model is compared. The results show encouraging potential for using machine learning techniques for the evaluation of turfgrass quality and color.

  12. A Backward Pyramid Oriented Optical Flow Field Computing Method for Aerial Image

    Directory of Open Access Journals (Sweden)

    LI Jiatian

    2016-09-01

    Full Text Available Aerial image optical flow field is the foundation for detecting moving objects at low altitude and obtaining change information. In general,the image pyramid structure is embedded in numerical procedure in order to enhance the convergence globally. However,more often than not,the pyramid structure is constructed using a bottom-up approach progressively,ignoring the geometry imaging process.In particular,when the ground objects moving it will lead to miss optical flow or the optical flow too small that could hardly sustain the subsequent modeling and analyzing issues. So a backward pyramid structure is proposed on the foundation of top-level standard image. Firstly,down sampled factors of top-level image are calculated quantitatively through central projection,which making the optical flow in top-level image represent the shifting threshold of the set ground target. Secondly,combining top-level image with its original,the down sampled factors in middle layer are confirmed in a constant proportion way. Finally,the image of middle layer is achieved by Gaussian smoothing and image interpolation,and meanwhile the pyramid is formed. The comparative experiments and analysis illustrate that the backward pyramid can calculate the optic flow field in aerial image accurately,and it has advantages in restraining small ground displacement.

  13. Oblique aerial images and their use in cultural heritage documentation

    DEFF Research Database (Denmark)

    Höhle, Joachim

    2013-01-01

    on automatically derived point clouds of high density. Each point will be supplemented with colour and other attributes. The problems experienced in these processes and the solutions to these problems are presented. The applied tools are a combination of professional tools, free software, and of own software...... developments. Special attention is given to the quality of input images. Investigations are carried out on edges in the images. The combination of oblique and nadir images enables new possibilities in the processing. The use of the near-infrared channel besides the red, green, and blue channel of the applied...

  14. Detection of High-Density Crowds in Aerial Images Using Texture Classification

    Directory of Open Access Journals (Sweden)

    Oliver Meynberg

    2016-06-01

    Full Text Available Automatic crowd detection in aerial images is certainly a useful source of information to prevent crowd disasters in large complex scenarios of mass events. A number of publications employ regression-based methods for crowd counting and crowd density estimation. However, these methods work only when a correct manual count is available to serve as a reference. Therefore, it is the objective of this paper to detect high-density crowds in aerial images, where counting– or regression–based approaches would fail. We compare two texture–classification methodologies on a dataset of aerial image patches which are grouped into ranges of different crowd density. These methodologies are: (1 a Bag–of–words (BoW model with two alternative local features encoded as Improved Fisher Vectors and (2 features based on a Gabor filter bank. Our results show that a classifier using either BoW or Gabor features can detect crowded image regions with 97% classification accuracy. In our tests of four classes of different crowd-density ranges, BoW–based features have a 5%–12% better accuracy than Gabor.

  15. Assessing the performance of aerial image point cloud and spectral metrics in predicting boreal forest canopy cover

    Science.gov (United States)

    Melin, M.; Korhonen, L.; Kukkonen, M.; Packalen, P.

    2017-07-01

    Canopy cover (CC) is a variable used to describe the status of forests and forested habitats, but also the variable used primarily to define what counts as a forest. The estimation of CC has relied heavily on remote sensing with past studies focusing on satellite imagery as well as Airborne Laser Scanning (ALS) using light detection and ranging (lidar). Of these, ALS has been proven highly accurate, because the fraction of pulses penetrating the canopy represents a direct measurement of canopy gap percentage. However, the methods of photogrammetry can be applied to produce point clouds fairly similar to airborne lidar data from aerial images. Currently there is little information about how well such point clouds measure canopy density and gaps. The aim of this study was to assess the suitability of aerial image point clouds for CC estimation and compare the results with those obtained using spectral data from aerial images and Landsat 5. First, we modeled CC for n = 1149 lidar plots using field-measured CCs and lidar data. Next, this data was split into five subsets in north-south direction (y-coordinate). Finally, four CC models (AerialSpectral, AerialPointcloud, AerialCombi (spectral + pointcloud) and Landsat) were created and they were used to predict new CC values to the lidar plots, subset by subset, using five-fold cross validation. The Landsat and AerialSpectral models performed with RMSEs of 13.8% and 12.4%, respectively. AerialPointcloud model reached an RMSE of 10.3%, which was further improved by the inclusion of spectral data; RMSE of the AerialCombi model was 9.3%. We noticed that the aerial image point clouds managed to describe only the outermost layer of the canopy and missed the details in lower canopy, which was resulted in weak characterization of the total CC variation, especially in the tails of the data.

  16. Counter Unmanned Aerial Systems Testing: Evaluation of VIS SWIR MWIR and LWIR passive imagers.

    Energy Technology Data Exchange (ETDEWEB)

    Birch, Gabriel Carlisle [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Woo, Bryana Lynn [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-01-01

    This report contains analysis of unmanned aerial systems as imaged by visible, short-wave infrared, mid-wave infrared, and long-wave infrared passive devices. Testing was conducted at the Nevada National Security Site (NNSS) during the week of August 15, 2016. Target images in all spectral bands are shown and contrast versus background is reported. Calculations are performed to determine estimated pixels-on-target for detection and assessment levels, and the number of pixels needed to cover a hemisphere for detection or assessment at defined distances. Background clutter challenges are qualitatively discussed for different spectral bands, and low contrast scenarios are highlighted for long-wave infrared imagers.

  17. Detection and Segmentation of Vine Canopy in Ultra-High Spatial Resolution RGB Imagery Obtained from Unmanned Aerial Vehicle (UAV: A Case Study in a Commercial Vineyard

    Directory of Open Access Journals (Sweden)

    Carlos Poblete-Echeverría

    2017-03-01

    Full Text Available The use of Unmanned Aerial Vehicles (UAVs in viticulture permits the capture of aerial Red-Green-Blue (RGB images with an ultra-high spatial resolution. Recent studies have demonstrated that RGB images can be used to monitor spatial variability of vine biophysical parameters. However, for estimating these parameters, accurate and automated segmentation methods are required to extract relevant information from RGB images. Manual segmentation of aerial images is a laborious and time-consuming process. Traditional classification methods have shown satisfactory results in the segmentation of RGB images for diverse applications and surfaces, however, in the case of commercial vineyards, it is necessary to consider some particularities inherent to canopy size in the vertical trellis systems (VSP such as shadow effect and different soil conditions in inter-rows (mixed information of soil and weeds. Therefore, the objective of this study was to compare the performance of four classification methods (K-means, Artificial Neural Networks (ANN, Random Forest (RForest and Spectral Indices (SI to detect canopy in a vineyard trained on VSP. Six flights were carried out from post-flowering to harvest in a commercial vineyard cv. Carménère using a low-cost UAV equipped with a conventional RGB camera. The results show that the ANN and the simple SI method complemented with the Otsu method for thresholding presented the best performance for the detection of the vine canopy with high overall accuracy values for all study days. Spectral indices presented the best performance in the detection of Plant class (Vine canopy with an overall accuracy of around 0.99. However, considering the performance pixel by pixel, the Spectral indices are not able to discriminate between Soil and Shadow class. The best performance in the classification of three classes (Plant, Soil, and Shadow of vineyard RGB images, was obtained when the SI values were used as input data in trained

  18. Autonomous Conflict Detection and Resolution for Unmanned Aerial Vehicles : On integration into the Airspace System

    NARCIS (Netherlands)

    Jenie, Y.I.

    2017-01-01

    In the last decade, the commercial values of Unmanned Aerial Vehicles (UAV), defined as devices that are capable of sustainable flights in the atmosphere that do not require to have a human (pilot) on-board, become widely recognized thanks to the advancement of technology in materials, sensors,

  19. Multi-temporal high resolution monitoring of debris-covered glaciers using unmanned aerial vehicles

    NARCIS (Netherlands)

    Kraaijenbrink, P.D.A.; Immerzeel, W.W.; de Jong, S.M.; Shea, Joseph M.; Pellicciotti, Francesca; Meijer, Sander W.; Shresta, A.B.

    Debris-covered glaciers in the Himalayas are relatively unstudied due to the difficulties in fieldwork caused by the inaccessible terrain and the presence of debris layers, which complicate in situ measurements. To overcome these difficulties an unmanned aerial vehicle (UAV) has been deployed

  20. ORIENTATION AND DENSE RECONSTRUCTION OF UNORDERED TERRESTRIAL AND AERIAL WIDE BASELINE IMAGE SETS

    Directory of Open Access Journals (Sweden)

    J. Bartelsen

    2012-07-01

    Full Text Available In this paper we present an approach for detailed and precise automatic dense 3D reconstruction using images from consumer cameras. The major difference between our approach and many others is that we focus on wide-baseline image sets. We have combined and improved several methods, particularly, least squares matching, RANSAC, scale-space maxima and bundle adjustment, for robust matching and parameter estimation. Point correspondences and the five-point algorithm lead to relative orientation. Due to our robust matching method it is possible to orient images under much more unfavorable conditions, for instance concerning illumination changes or scale differences, than for often used operators such as SIFT. For dense reconstruction, we use our orientation as input for Semiglobal Matching (SGM resulting into dense depth images. The latter can be fused into a 2.5D model for eliminating the redundancy of the highly overlapping depth images. However, some applications require full 3D models. A solution to this problem is part of our current work, for which preliminary results are presented in this paper. With very small unmanned aerial systems (Micro UAS it is possible to acquire images which have a perspective similar to terrestrial images and can thus be combined with them. Such a combination is useful for an almost complete 3D reconstruction of urban scenes. We have applied our approach to several hundred aerial and terrestrial images and have generated detailed 2.5D and 3D models of urban areas.

  1. Application of aerial image based information for coastal habitat research

    DEFF Research Database (Denmark)

    Juel, Anders

    2014-01-01

    and research in coastal terrestrial habitats. It further presents new insight into the mechanisms determining the spatial patterns of vegetation across coastal landscapes. These topics are investigated by combining fine-scale vegetation information from a comprehensive field programme with object-based image...

  2. Operational Data Augmentation in Classifying Single Aerial Images of Animals

    NARCIS (Netherlands)

    Okafor, Emmanuel; Smit, Rik; Schomaker, Lambertus; Wiering, Marco

    2017-01-01

    In deep learning, data augmentation is important to increase the amount of training images to obtain higher classification accuracies. Most data-augmentation methods adopt the use of the following techniques: cropping, mirroring, color casting, scaling and rotation for creating additional training

  3. Neural understanding of low-resolution images

    NARCIS (Netherlands)

    Spaanenburg, L; DeGraaf, J; Nijhuis, JAG; Stevens, [No Value; Wichers, W

    1998-01-01

    Neural networks can be applied for a number of innovative applications in a production environment, ranging from security & safety in the environmental conditions to the product control & diagnosis. For visual monitoring the use of low-resolution images is promising to bridge the time elapse between

  4. Smartphone microendoscopy for high resolution fluorescence imaging

    Directory of Open Access Journals (Sweden)

    Xiangqian Hong

    2016-09-01

    Full Text Available High resolution optical endoscopes are increasingly used in diagnosis of various medical conditions of internal organs, such as the cervix and gastrointestinal (GI tracts, but they are too expensive for use in resource-poor settings. On the other hand, smartphones with high resolution cameras and Internet access have become more affordable, enabling them to diffuse into most rural areas and developing countries in the past decade. In this paper, we describe a smartphone microendoscope that can take fluorescence images with a spatial resolution of 3.1 μm. Images collected from ex vivo, in vitro and in vivo samples using the device are also presented. The compact and cost-effective smartphone microendoscope may be envisaged as a powerful tool for detecting pre-cancerous lesions of internal organs in low and middle-income countries (LMICs.

  5. Moving object detection using dynamic motion modelling from UAV aerial images.

    Science.gov (United States)

    Saif, A F M Saifuddin; Prabuwono, Anton Satria; Mahayuddin, Zainal Rasyid

    2014-01-01

    Motion analysis based moving object detection from UAV aerial image is still an unsolved issue due to inconsideration of proper motion estimation. Existing moving object detection approaches from UAV aerial images did not deal with motion based pixel intensity measurement to detect moving object robustly. Besides current research on moving object detection from UAV aerial images mostly depends on either frame difference or segmentation approach separately. There are two main purposes for this research: firstly to develop a new motion model called DMM (dynamic motion model) and secondly to apply the proposed segmentation approach SUED (segmentation using edge based dilation) using frame difference embedded together with DMM model. The proposed DMM model provides effective search windows based on the highest pixel intensity to segment only specific area for moving object rather than searching the whole area of the frame using SUED. At each stage of the proposed scheme, experimental fusion of the DMM and SUED produces extracted moving objects faithfully. Experimental result reveals that the proposed DMM and SUED have successfully demonstrated the validity of the proposed methodology.

  6. Lateral resolution of eddy current imaging

    International Nuclear Information System (INIS)

    Hassan, W.; Blodgett, M.; Nagy, P.B.

    2002-01-01

    Analytical, finite element simulation, and experimental methods were used to investigate the lateral resolution of eddy current microscopy. It was found that the lateral resolution of eddy current imaging is ultimately limited by the probe-coil geometry and dimensions, but both the inspection frequency and the phase angle can be used to optimize the resolution, to some degree, at the expense of sensitivity. Electric anisotropy exhibited by noncubic crystallographic classes of materials such as titanium alloys can play a very similar role in electromagnetic materials characterization of polycrystalline metals to that of elastic anisotropy in ultrasonic materials characterization. Our results demonstrate that eddy current microscopy can be enhanced via a high-resolution, small diameter probe-coil which delivers a unique materials characterization tool well suited for the evaluation of Ti alloys

  7. Monitoring Active Volcanos Using Aerial Images and the Orthoview Tool

    Directory of Open Access Journals (Sweden)

    Maria Marsella

    2014-12-01

    Full Text Available In volcanic areas, where it can be difficult to perform direct surveys, digital photogrammetry techniques are rarely adopted for routine volcano monitoring. Nevertheless, they have remarkable potentialities for observing active volcanic features (e.g., fissures, lava flows and the connected deformation processes. The ability to obtain accurate quantitative data of definite accuracy in short time spans makes digital photogrammetry a suitable method for controlling the evolution of rapidly changing large-area volcanic phenomena. The systematic acquisition of airborne photogrammetric datasets can be adopted for implementing a more effective procedure aimed at long-term volcano monitoring and hazard assessment. In addition, during the volcanic crisis, the frequent acquisition of oblique digital images from helicopter allows for quasi-real-time monitoring to support mitigation actions by civil protection. These images are commonly used to update existing maps through a photo-interpretation approach that provide data of unknown accuracy. This work presents a scientific tool (Orthoview that implements a straightforward photogrammetric approach to generate digital orthophotos from single-view oblique images provided that at least four Ground Control Points (GCP and current Digital Elevation Models (DEM are available. The influence of the view geometry, of sparse and not-signalized GCP and DEM inaccuracies is analyzed for evaluating the performance of the developed tool in comparison with other remote sensing techniques. Results obtained with datasets from Etna and Stromboli volcanoes demonstrate that 2D features measured on the produced orthophotos can reach sub-meter-level accuracy.

  8. Dynamic high resolution imaging of rats

    International Nuclear Information System (INIS)

    Miyaoka, R.S.; Lewellen, T.K.; Bice, A.N.

    1990-01-01

    A positron emission tomography with the sensitivity and resolution to do dynamic imaging of rats would be an invaluable tool for biological researchers. In this paper, the authors determine the biological criteria for dynamic positron emission imaging of rats. To be useful, 3 mm isotropic resolution and 2-3 second time binning were necessary characteristics for such a dedicated tomograph. A single plane in which two objects of interest could be imaged simultaneously was considered acceptable. Multi-layered detector designs were evaluated as a possible solution to the dynamic imaging and high resolution imaging requirements. The University of Washington photon history generator was used to generate data to investigate a tomograph's sensitivity to true, scattered and random coincidences for varying detector ring diameters. Intrinsic spatial uniformity advantages of multi-layered detector designs over conventional detector designs were investigated using a Monte Carlo program. As a result, a modular three layered detector prototype is being developed. A module will consist of a layer of five 3.5 mm wide crystals and two layers of six 2.5 mm wide crystals. The authors believe adequate sampling can be achieved with a stationary detector system using these modules. Economical crystal decoding strategies have been investigated and simulations have been run to investigate optimum light channeling methods for block decoding strategies. An analog block decoding method has been proposed and will be experimentally evaluated to determine whether it can provide the desired performance

  9. An Automated Technique for Generating Georectified Mosaics from Ultra-High Resolution Unmanned Aerial Vehicle (UAV Imagery, Based on Structure from Motion (SfM Point Clouds

    Directory of Open Access Journals (Sweden)

    Christopher Watson

    2012-05-01

    Full Text Available Unmanned Aerial Vehicles (UAVs are an exciting new remote sensing tool capable of acquiring high resolution spatial data. Remote sensing with UAVs has the potential to provide imagery at an unprecedented spatial and temporal resolution. The small footprint of UAV imagery, however, makes it necessary to develop automated techniques to geometrically rectify and mosaic the imagery such that larger areas can be monitored. In this paper, we present a technique for geometric correction and mosaicking of UAV photography using feature matching and Structure from Motion (SfM photogrammetric techniques. Images are processed to create three dimensional point clouds, initially in an arbitrary model space. The point clouds are transformed into a real-world coordinate system using either a direct georeferencing technique that uses estimated camera positions or via a Ground Control Point (GCP technique that uses automatically identified GCPs within the point cloud. The point cloud is then used to generate a Digital Terrain Model (DTM required for rectification of the images. Subsequent georeferenced images are then joined together to form a mosaic of the study area. The absolute spatial accuracy of the direct technique was found to be 65–120 cm whilst the GCP technique achieves an accuracy of approximately 10–15 cm.

  10. Very high resolution satellite data: New challenges in image analysis

    Digital Repository Service at National Institute of Oceanography (India)

    Sathe, P.V.; Muraleedharan, P.M.

    with the exception that a ground-based view covers the entire optical range from 400 to 700 nm while satellite images will be wavelength-specific. Although the images will not surpass details observed by a human eye, they will, in principle, be comparable with aerial...

  11. Geomorphic evidence for ancient seas in west Deuteronilus Mensae, Mars-2: From very high resolution Viking Orbiter images

    Science.gov (United States)

    Parker, Timothy J.; Schneeberger, Dale M.; Pieri, David C.; Saunders, R. Stephen

    1987-01-01

    Very high resolution Viking Orbiter images of the Martian surface, though rare, make it possible to examine specific areas at image scales approaching those of high altitude terrestrial aerial photographs. Twenty three clear images lie within west Deuteronilus Mensae. The northernmost images which constitute an almost unbroken mosaic of the west wall of a long fingerlike canyon are examined. Morphological details on the plateau surface within zone B, not detectable at low resolution, make it possible to divide the zone into two distinct subzones separated by an east-west escarpment. The morphology of the canyon floor is described in detail.

  12. Monitoring tropical debris-covered glacier dynamics from high-resolution unmanned aerial vehicle photogrammetry, Cordillera Blanca, Peru

    Directory of Open Access Journals (Sweden)

    O. Wigmore

    2017-11-01

    Full Text Available The glaciers of the Cordillera Blanca, Peru, are rapidly retreating and thinning as a result of climate change, altering the timing, quantity and quality of water available to downstream users. Furthermore, increases in the number and size of proglacial lakes associated with these melting glaciers is increasing potential exposure to glacier lake outburst floods (GLOFs. Understanding how these glaciers are changing and their connection to proglacial lake systems is thus of critical importance. Most satellite data are too coarse for studying small mountain glaciers and are often affected by cloud cover, while traditional airborne photogrammetry and lidar are costly. Recent developments have made unmanned aerial vehicles (UAVs a viable and potentially transformative method for studying glacier change at high spatial resolution, on demand and at relatively low cost.Using a custom designed hexacopter built for high-altitude (4000–6000 m a. s. l.  operation, we completed repeat aerial surveys (2014 and 2015 of the debris-covered Llaca Glacier tongue and proglacial lake system. High-resolution orthomosaics (5 cm and digital elevation models (DEMs (10 cm were produced and their accuracy assessed. Analysis of these datasets reveals highly heterogeneous patterns of glacier change. The most rapid areas of ice loss were associated with exposed ice cliffs and meltwater ponds on the glacier surface. Considerable subsidence and low surface velocities were also measured on the sediments within the pro-glacial lake, indicating the presence of extensive regions of buried ice and continued connection to the glacier tongue. Only limited horizontal retreat of the glacier tongue was observed, indicating that measurements of changes in aerial extent alone are inadequate for monitoring changes in glacier ice quantity.

  13. Autonomous Conflict Detection and Resolution for Unmanned Aerial Vehicles: On integration into the Airspace System

    OpenAIRE

    Jenie, Y.I.

    2017-01-01

    In the last decade, the commercial values of Unmanned Aerial Vehicles (UAV), defined as devices that are capable of sustainable flights in the atmosphere that do not require to have a human (pilot) on-board, become widely recognized thanks to the advancement of technology in materials, sensors, computation, and telemetry. As UAVs are becoming cheaper and more user-friendly, many companies are motivated to incorporate them in their everyday business, such as for delivery services, journalisms,...

  14. Digital image integration technique of multi-geoscience information dominated by aerial radiometric measurements

    International Nuclear Information System (INIS)

    Liu Dechang; Sun Maorong; Zhu Deling; Zhang Jingbo; He Jianguo; Dong Xiuzhen

    1992-02-01

    The geologic metallogenetic environment of uranium at Lian Shan Guan region has been studied by using digital image integration technique of multi-geoscience information with aerial radiometric measurements. It includes the classification of uranium-bearing rock, recognizing patterns of ore-forming and geologic mapping in ore field. Some new tectonic structure was found in this region that gives significant information for further exploring of uranium ore. After multi-parameters screening of aerial radiometric data, patterns recognizing and multi-geoscience information integration analysis, four prospective metallogenetic zones were predicted, and the predication was proved by further geologic survey. Three of the four zones are very encouraging, where ore-forming structures, hydrothermal deposits, wall-rock alteration, primary and secondary uranium ore and rich uranium mineralization are discovered. The department of geologic exploring has decided that these zones will enjoy priority in the examination for further prospecting of uranium ores

  15. Isotope specific resolution recovery image reconstruction in high resolution PET imaging

    OpenAIRE

    Kotasidis Fotis A.; Kotasidis Fotis A.; Angelis Georgios I.; Anton-Rodriguez Jose; Matthews Julian C.; Reader Andrew J.; Reader Andrew J.; Zaidi Habib; Zaidi Habib; Zaidi Habib

    2014-01-01

    Purpose: Measuring and incorporating a scanner specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However due to the short half life of clinically used isotopes other long lived isotopes not used in clinical practice are used to perform the PSF measurements. As such non optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction usuall...

  16. Comparison of two aerial imaging platforms for identification of Huanglongbing-infected citrus trees

    DEFF Research Database (Denmark)

    Garcia Ruiz, Francisco Jose; Sankaran, Sindhuja; Maja, Joe Mari

    2013-01-01

    and HLB-infected trees. During classification studies, accuracies in the range of 67–85% and false negatives from 7% to 32% were acquired from UAV-based data; while corresponding values were 61–74% and 28–45% with aircraft-based data. Among the tested classification algorithms, support vector machine (SVM......) with kernel resulted in better performance than other methods such as SVM (linear), linear discriminant analysis and quadratic discriminant analysis. Thus, high-resolution aerial sensing has good prospect for the detection of HLB-infected trees....

  17. High-Resolution Monitoring of Himalayan Glacier Dynamics Using Unmanned Aerial Vehicles

    Science.gov (United States)

    Immerzeel, W.; Kraaijenbrink, P. D. A.; Shea, J.; Shrestha, A. B.; Pellicciotti, F.; Bierkens, M. F.; de Jong, S. M.

    2014-12-01

    Himalayan glacier tongues are commonly debris covered and play an important role in modulating the glacier response to climate . However, they remain relatively unstudied because of the inaccessibility of the terrain and the difficulties in field work caused by the thick debris mantles. Observations of debris-covered glaciers are therefore limited to point locations and airborne remote sensing may bridge the gap between scarce, point field observations and coarse resolution space-borne remote sensing. In this study we deploy an Unmanned Airborne Vehicle (UAV) on two debris covered glaciers in the Nepalese Himalayas: the Lirung and Langtang glacier during four field campaigns in 2013 and 2014. Based on stereo-imaging and the structure for motion algorithm we derive highly detailed ortho-mosaics and digital elevation models (DEMs), which we geometrically correct using differential GPS observations collected in the field. Based on DEM differencing and manual feature tracking we derive the mass loss and the surface velocity of the glacier at a high spatial resolution and accuracy. We also assess spatiotemporal changes in supra-glacial lakes and ice cliffs based on the imagery. On average, mass loss is limited and the surface velocity is very small. However, the spatial variability of melt rates is very high, and ice cliffs and supra-glacial ponds show mass losses that can be an order of magnitude higher than the average. We suggest that future research should focus on the interaction between supra-glacial ponds, ice cliffs and englacial hydrology to further understand the dynamics of debris-covered glaciers. Finally, we conclude that UAV deployment has large potential in glaciology and it represents a substantial advancement over methods currently applied in studying glacier surface features.

  18. High resolution transmission imaging without lenses

    International Nuclear Information System (INIS)

    Rodenburg, J M; Hurst, A C; Maiden, A

    2010-01-01

    The whole history of transmission imaging has been dominated by the lens, whether used in visible-light optics, electron optics or X-ray optics. Lenses can be thought of as a very efficient method of processing a wave front scattered from an object into an image of that object. An alternative approach is to undertake this image-formation process using a computational technique. The crudest scattering experiment is to simply record the intensity of a diffraction pattern. Recent progress in so-called diffractive imaging has shown that it is possible to recover the phase of a scattered wavefield from its diffraction pattern alone, as long as the object (or the illumination on the object) is of finite extent. In this paper we present results from a very efficient phase retrieval method which can image infinitely large fields of view. It may have important applications in improving resolution in electron microscopy, or at least allowing low specification microscopes to achieve resolution comparable to state-of-the-art machines.

  19. Mapping rock forming minerals at Boundary Canyon, Death Valey National Park, California, using aerial SEBASS thermal infrared hyperspectral image data

    Science.gov (United States)

    Aslett, Zan; Taranik, James V.; Riley, Dean N.

    2018-02-01

    Aerial spatially enhanced broadband array spectrograph system (SEBASS) long-wave infrared (LWIR) hyperspectral image data were used to map the distribution of rock-forming minerals indicative of sedimentary and meta-sedimentary lithologies around Boundary Canyon, Death Valley, California, USA. Collection of data over the Boundary Canyon detachment fault (BCDF) facilitated measurement of numerous lithologies representing a contact between the relatively unmetamorphosed Grapevine Mountains allochthon and the metamorphosed core complex of the Funeral Mountains autochthon. These included quartz-rich sandstone, quartzite, conglomerate, and alluvium; muscovite-rich schist, siltstone, and slate; and carbonate-rich dolomite, limestone, and marble, ranging in age from late Precambrian to Quaternary. Hyperspectral data were reduced in dimensionality and processed to statistically identify and map unique emissivity spectra endmembers. Some minerals (e.g., quartz and muscovite) dominate multiple lithologies, resulting in a limited ability to differentiate them. Abrupt variations in image data emissivity amongst pelitic schists corresponded to amphibolite; these rocks represent gradation from greenschist- to amphibolite-metamorphic facies lithologies. Although the full potential of LWIR hyperspectral image data may not be fully utilized within this study area due to lack of measurable spectral distinction between rocks of similar bulk mineralogy, the high spectral resolution of the image data was useful in characterizing silicate- and carbonate-based sedimentary and meta-sedimentary rocks in proximity to fault contacts, as well as for interpreting some mineral mixtures.

  20. Analysis of Unmanned Aerial System-Based CIR Images in Forestry—A New Perspective to Monitor Pest Infestation Levels

    Directory of Open Access Journals (Sweden)

    Jan Rudolf Karl Lehmann

    2015-03-01

    Full Text Available The detection of pest infestation is an important aspect of forest management. In the case of the oak splendour beetle (Agrilus biguttatus infestation, the affected oaks (Quercus sp. show high levels of defoliation and altered canopy reflection signature. These critical features can be identified in high-resolution colour infrared (CIR images of the tree crown and branches level captured by Unmanned Aerial Systems (UAS. In this study, we used a small UAS equipped with a compact digital camera which has been calibrated and modified to record not only the visual but also the near infrared reflection (NIR of possibly infested oaks. The flight campaigns were realized in August 2013, covering two study sites which are located in a rural area in western Germany. Both locations represent small-scale, privately managed commercial forests in which oaks are economically valuable species. Our workflow includes the CIR/NIR image acquisition, mosaicking, georeferencing and pixel-based image enhancement followed by object-based image classification techniques. A modified Normalized Difference Vegetation Index (NDVImod derived classification was used to distinguish between five vegetation health classes, i.e., infested, healthy or dead branches, other vegetation and canopy gaps. We achieved an overall Kappa Index of Agreement (KIA   of 0.81 and 0.77 for each study site, respectively. This approach offers a low-cost alternative to private forest owners who pursue a sustainable management strategy.

  1. Heuristic optimization in penumbral image for high resolution reconstructed image

    International Nuclear Information System (INIS)

    Azuma, R.; Nozaki, S.; Fujioka, S.; Chen, Y. W.; Namihira, Y.

    2010-01-01

    Penumbral imaging is a technique which uses the fact that spatial information can be recovered from the shadow or penumbra that an unknown source casts through a simple large circular aperture. The size of the penumbral image on the detector can be mathematically determined as its aperture size, object size, and magnification. Conventional reconstruction methods are very sensitive to noise. On the other hand, the heuristic reconstruction method is very tolerant of noise. However, the aperture size influences the accuracy and resolution of the reconstructed image. In this article, we propose the optimization of the aperture size for the neutron penumbral imaging.

  2. Computed tomography with selectable image resolution

    International Nuclear Information System (INIS)

    Dibianca, F.A.; Dallapiazza, D.G.

    1981-01-01

    A computed tomography system x-ray detector has a central group of half-width detector elements and groups of full-width elements on each side of the central group. To obtain x-ray attenuation data for whole body layers, the half-width elements are switched effectively into paralleled pairs so all elements act like full-width elements and an image of normal resolution is obtained. For narrower head layers, the elements in the central group are used as half-width elements so resolution which is twice as great as normal is obtained. The central group is also used in the half-width mode and the outside groups are used in the full-width mode to obtain a high resolution image of a body zone within a full body layer. In one embodiment data signals from the detector are switched by electronic multiplexing and in another embodiment a processor chooses the signals for the various kinds of images that are to be reconstructed. (author)

  3. Resolution limits for wave equation imaging

    KAUST Repository

    Huang, Yunsong

    2014-08-01

    Formulas are derived for the resolution limits of migration-data kernels associated with diving waves, primary reflections, diffractions, and multiple reflections. They are applicable to images formed by reverse time migration (RTM), least squares migration (LSM), and full waveform inversion (FWI), and suggest a multiscale approach to iterative FWI based on multiscale physics. That is, at the early stages of the inversion, events that only generate low-wavenumber resolution should be emphasized relative to the high-wavenumber resolution events. As the iterations proceed, the higher-resolution events should be emphasized. The formulas also suggest that inverting multiples can provide some low- and intermediate-wavenumber components of the velocity model not available in the primaries. Finally, diffractions can provide twice or better the resolution than specular reflections for comparable depths of the reflector and diffractor. The width of the diffraction-transmission wavepath is approximately λ at the diffractor location for the diffraction-transmission wavepath. © 2014 Elsevier B.V.

  4. Registration of airborne LiDAR data and aerial images based on straight lines and POS data

    Science.gov (United States)

    Du, Quanye; Xu, Biao; Cao, Hui

    2009-10-01

    This paper presents a registration method which based on straight lines primitive. Firstly, 2D straight lines are extracted from aerial images using Canny operator and straight line fitting. In the similar way, 3D straight lines are extracted from LiDAR range images which derive from laser scanning point cloud. Secondly, 3D straight lines are projected to aerial images using collinearity equations and Position and Orientation System (POS) data. Then the corresponding lines are determined by straight line error. At last, each image's new exterior orientation elements are calculated by generalized point (straight line) photogrammetry.

  5. High-resolution CCD imaging alternatives

    Science.gov (United States)

    Brown, D. L.; Acker, D. E.

    1992-08-01

    High resolution CCD color cameras have recently stimulated the interest of a large number of potential end-users for a wide range of practical applications. Real-time High Definition Television (HDTV) systems are now being used or considered for use in applications ranging from entertainment program origination through digital image storage to medical and scientific research. HDTV generation of electronic images offers significant cost and time-saving advantages over the use of film in such applications. Further in still image systems electronic image capture is faster and more efficient than conventional image scanners. The CCD still camera can capture 3-dimensional objects into the computing environment directly without having to shoot a picture on film develop it and then scan the image into a computer. 2. EXTENDING CCD TECHNOLOGY BEYOND BROADCAST Most standard production CCD sensor chips are made for broadcast-compatible systems. One popular CCD and the basis for this discussion offers arrays of roughly 750 x 580 picture elements (pixels) or a total array of approximately 435 pixels (see Fig. 1). FOR. A has developed a technique to increase the number of available pixels for a given image compared to that produced by the standard CCD itself. Using an inter-lined CCD with an overall spatial structure several times larger than the photo-sensitive sensor areas each of the CCD sensors is shifted in two dimensions in order to fill in spatial gaps between adjacent sensors.

  6. Registration of Urban Aerial Image and LiDAR Based on Line Vectors

    Directory of Open Access Journals (Sweden)

    Qinghong Sheng

    2017-09-01

    Full Text Available In a traditional registration of a single aerial image with airborne light detection and ranging (LiDAR data using linear features that regard line direction as a control or linear features as constraints in the solution, lacking the constraint of linear position leads to the error propagation of the adjustment model. To solve this problem, this paper presents a line vector-based registration mode (LVR in which image rays and LiDAR lines are expressed by a line vector that integrates the line direction and the line position. A registration equation of line vector is set up by coplanar imaging rays and corresponding control lines. Three types of datasets consisting of synthetic, theInternational Society for Photogrammetry and Remote Sensing (ISPRS test project, and real aerial data are used. A group of progressive experiments is undertaken to evaluate the robustness of the LVR. Experimental results demonstrate that the integrated line direction and the line position contributes a great deal to the theoretical and real accuracies of the unknowns, as well as the stability of the adjustment model. This paper provides a new suggestion that, for a single image and LiDAR data, registration in urban areas can be accomplished by accommodating rich line features.

  7. Isotope specific resolution recovery image reconstruction in high resolution PET imaging

    Energy Technology Data Exchange (ETDEWEB)

    Kotasidis, Fotis A. [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva, Switzerland and Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, M20 3LJ, Manchester (United Kingdom); Angelis, Georgios I. [Faculty of Health Sciences, Brain and Mind Research Institute, University of Sydney, NSW 2006, Sydney (Australia); Anton-Rodriguez, Jose; Matthews, Julian C. [Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, Manchester M20 3LJ (United Kingdom); Reader, Andrew J. [Montreal Neurological Institute, McGill University, Montreal QC H3A 2B4, Canada and Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King' s College London, St. Thomas’ Hospital, London SE1 7EH (United Kingdom); Zaidi, Habib [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva (Switzerland); Geneva Neuroscience Centre, Geneva University, CH-1205 Geneva (Switzerland); Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, PO Box 30 001, Groningen 9700 RB (Netherlands)

    2014-05-15

    Purpose: Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to perform the PSF measurements. As such, non-optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction, usually underestimating the true PSF owing to the difference in positron range. In high resolution brain and preclinical imaging, this effect is of particular importance since the PSFs become more positron range limited and isotope-specific PSFs can help maximize the performance benefit from using resolution recovery image reconstruction algorithms. Methods: In this work, the authors used a printing technique to simultaneously measure multiple point sources on the High Resolution Research Tomograph (HRRT), and the authors demonstrated the feasibility of deriving isotope-dependent system matrices from fluorine-18 and carbon-11 point sources. Furthermore, the authors evaluated the impact of incorporating them within RM image reconstruction, using carbon-11 phantom and clinical datasets on the HRRT. Results: The results obtained using these two isotopes illustrate that even small differences in positron range can result in different PSF maps, leading to further improvements in contrast recovery when used in image reconstruction. The difference is more pronounced in the centre of the field-of-view where the full width at half maximum (FWHM) from the positron range has a larger contribution to the overall FWHM compared to the edge where the parallax error dominates the overall FWHM. Conclusions: Based on the proposed methodology, measured isotope-specific and spatially variant PSFs can be reliably derived and used for improved spatial resolution and variance performance in resolution

  8. Isotope specific resolution recovery image reconstruction in high resolution PET imaging

    International Nuclear Information System (INIS)

    Kotasidis, Fotis A.; Angelis, Georgios I.; Anton-Rodriguez, Jose; Matthews, Julian C.; Reader, Andrew J.; Zaidi, Habib

    2014-01-01

    Purpose: Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to perform the PSF measurements. As such, non-optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction, usually underestimating the true PSF owing to the difference in positron range. In high resolution brain and preclinical imaging, this effect is of particular importance since the PSFs become more positron range limited and isotope-specific PSFs can help maximize the performance benefit from using resolution recovery image reconstruction algorithms. Methods: In this work, the authors used a printing technique to simultaneously measure multiple point sources on the High Resolution Research Tomograph (HRRT), and the authors demonstrated the feasibility of deriving isotope-dependent system matrices from fluorine-18 and carbon-11 point sources. Furthermore, the authors evaluated the impact of incorporating them within RM image reconstruction, using carbon-11 phantom and clinical datasets on the HRRT. Results: The results obtained using these two isotopes illustrate that even small differences in positron range can result in different PSF maps, leading to further improvements in contrast recovery when used in image reconstruction. The difference is more pronounced in the centre of the field-of-view where the full width at half maximum (FWHM) from the positron range has a larger contribution to the overall FWHM compared to the edge where the parallax error dominates the overall FWHM. Conclusions: Based on the proposed methodology, measured isotope-specific and spatially variant PSFs can be reliably derived and used for improved spatial resolution and variance performance in resolution

  9. Isotope specific resolution recovery image reconstruction in high resolution PET imaging.

    Science.gov (United States)

    Kotasidis, Fotis A; Angelis, Georgios I; Anton-Rodriguez, Jose; Matthews, Julian C; Reader, Andrew J; Zaidi, Habib

    2014-05-01

    Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to perform the PSF measurements. As such, non-optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction, usually underestimating the true PSF owing to the difference in positron range. In high resolution brain and preclinical imaging, this effect is of particular importance since the PSFs become more positron range limited and isotope-specific PSFs can help maximize the performance benefit from using resolution recovery image reconstruction algorithms. In this work, the authors used a printing technique to simultaneously measure multiple point sources on the High Resolution Research Tomograph (HRRT), and the authors demonstrated the feasibility of deriving isotope-dependent system matrices from fluorine-18 and carbon-11 point sources. Furthermore, the authors evaluated the impact of incorporating them within RM image reconstruction, using carbon-11 phantom and clinical datasets on the HRRT. The results obtained using these two isotopes illustrate that even small differences in positron range can result in different PSF maps, leading to further improvements in contrast recovery when used in image reconstruction. The difference is more pronounced in the centre of the field-of-view where the full width at half maximum (FWHM) from the positron range has a larger contribution to the overall FWHM compared to the edge where the parallax error dominates the overall FWHM. Based on the proposed methodology, measured isotope-specific and spatially variant PSFs can be reliably derived and used for improved spatial resolution and variance performance in resolution recovery image reconstruction. The

  10. GRANULOMETRIC MAPS FROM HIGH RESOLUTION SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    Catherine Mering

    2011-05-01

    Full Text Available A new method of land cover mapping from satellite images using granulometric analysis is presented here. Discontinuous landscapes such as steppian bushes of semi arid regions and recently growing urban settlements are especially concerned by this study. Spatial organisations of the land cover are quantified by means of the size distribution analysis of the land cover units extracted from high resolution remotely sensed images. A granulometric map is built by automatic classification of every pixel of the image according to the granulometric density inside a sliding neighbourhood. Granulometric mapping brings some advantages over traditional thematic mapping by remote sensing by focusing on fine spatial events and small changes in one peculiar category of the landscape.

  11. Algorithm for automatic image dodging of unmanned aerial vehicle images using two-dimensional radiometric spatial attributes

    Science.gov (United States)

    Li, Wenzhuo; Sun, Kaimin; Li, Deren; Bai, Ting

    2016-07-01

    Unmanned aerial vehicle (UAV) remote sensing technology has come into wide use in recent years. The poor stability of the UAV platform, however, produces more inconsistencies in hue and illumination among UAV images than other more stable platforms. Image dodging is a process used to reduce these inconsistencies caused by different imaging conditions. We propose an algorithm for automatic image dodging of UAV images using two-dimensional radiometric spatial attributes. We use object-level image smoothing to smooth foreground objects in images and acquire an overall reference background image by relative radiometric correction. We apply the Contourlet transform to separate high- and low-frequency sections for every single image, and replace the low-frequency section with the low-frequency section extracted from the corresponding region in the overall reference background image. We apply the inverse Contourlet transform to reconstruct the final dodged images. In this process, a single image must be split into reasonable block sizes with overlaps due to large pixel size. Experimental mosaic results show that our proposed method reduces the uneven distribution of hue and illumination. Moreover, it effectively eliminates dark-bright interstrip effects caused by shadows and vignetting in UAV images while maximally protecting image texture information.

  12. Extracting Buildings from True Color Stereo Aerial Images Using a Decision Making Strategy

    Directory of Open Access Journals (Sweden)

    Eufemia Tarantino

    2011-07-01

    Full Text Available The automatic extraction of buildings from true color stereo aerial imagery in a dense built-up area is the main focus of this paper. Our approach strategy aimed at reducing the complexity of the image content by means of a three-step procedure combining reliable geospatial image analysis techniques. Even if it is a rudimentary first step towards a more general approach, the method presented proved useful in urban sprawl studies for rapid map production in flat area by retrieving indispensable information on buildings from scanned historic aerial photography. After the preliminary creation of a photogrammetric model to manage Digital Surface Model and orthophotos, five intermediate mask-layers data (Elevation, Slope, Vegetation, Shadow, Canny, Shadow, Edges were processed through the combined use of remote sensing image processing and GIS software environments. Lastly, a rectangular building block model without roof structures (Level of Detail, LoD1 was automatically generated. System performance was evaluated with objective criteria, showing good results in a complex urban area featuring various types of building objects.

  13. Limiting liability via high resolution image processing

    Energy Technology Data Exchange (ETDEWEB)

    Greenwade, L.E.; Overlin, T.K.

    1996-12-31

    The utilization of high resolution image processing allows forensic analysts and visualization scientists to assist detectives by enhancing field photographs, and by providing the tools and training to increase the quality and usability of field photos. Through the use of digitized photographs and computerized enhancement software, field evidence can be obtained and processed as `evidence ready`, even in poor lighting and shadowed conditions or darkened rooms. These images, which are most often unusable when taken with standard camera equipment, can be shot in the worst of photographic condition and be processed as usable evidence. Visualization scientists have taken the use of digital photographic image processing and moved the process of crime scene photos into the technology age. The use of high resolution technology will assist law enforcement in making better use of crime scene photography and positive identification of prints. Valuable court room and investigation time can be saved and better served by this accurate, performance based process. Inconclusive evidence does not lead to convictions. Enhancement of the photographic capability helps solve one major problem with crime scene photos, that if taken with standard equipment and without the benefit of enhancement software would be inconclusive, thus allowing guilty parties to be set free due to lack of evidence.

  14. Near Real-Time Georeference of Umanned Aerial Vehicle Images for Post-Earthquake Response

    Science.gov (United States)

    Wang, S.; Wang, X.; Dou, A.; Yuan, X.; Ding, L.; Ding, X.

    2018-04-01

    The rapid collection of Unmanned Aerial Vehicle (UAV) remote sensing images plays an important role in the fast submitting disaster information and the monitored serious damaged objects after the earthquake. However, for hundreds of UAV images collected in one flight sortie, the traditional data processing methods are image stitching and three-dimensional reconstruction, which take one to several hours, and affect the speed of disaster response. If the manual searching method is employed, we will spend much more time to select the images and the find images do not have spatial reference. Therefore, a near-real-time rapid georeference method for UAV remote sensing disaster data is proposed in this paper. The UAV images are achieved georeference combined with the position and attitude data collected by UAV flight control system, and the georeferenced data is organized by means of world file which is developed by ESRI. The C # language is adopted to compile the UAV images rapid georeference software, combined with Geospatial Data Abstraction Library (GDAL). The result shows that it can realize rapid georeference of remote sensing disaster images for up to one thousand UAV images within one minute, and meets the demand of rapid disaster response, which is of great value in disaster emergency application.

  15. NEAR REAL-TIME GEOREFERENCE OF UMANNED AERIAL VEHICLE IMAGES FOR POST-EARTHQUAKE RESPONSE

    Directory of Open Access Journals (Sweden)

    S. Wang

    2018-04-01

    Full Text Available The rapid collection of Unmanned Aerial Vehicle (UAV remote sensing images plays an important role in the fast submitting disaster information and the monitored serious damaged objects after the earthquake. However, for hundreds of UAV images collected in one flight sortie, the traditional data processing methods are image stitching and three-dimensional reconstruction, which take one to several hours, and affect the speed of disaster response. If the manual searching method is employed, we will spend much more time to select the images and the find images do not have spatial reference. Therefore, a near-real-time rapid georeference method for UAV remote sensing disaster data is proposed in this paper. The UAV images are achieved georeference combined with the position and attitude data collected by UAV flight control system, and the georeferenced data is organized by means of world file which is developed by ESRI. The C # language is adopted to compile the UAV images rapid georeference software, combined with Geospatial Data Abstraction Library (GDAL. The result shows that it can realize rapid georeference of remote sensing disaster images for up to one thousand UAV images within one minute, and meets the demand of rapid disaster response, which is of great value in disaster emergency application.

  16. Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images.

    Science.gov (United States)

    Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

    2015-05-22

    In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures.

  17. High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision and hobbyist unmanned aerial vehicles

    Science.gov (United States)

    Dandois, J. P.; Ellis, E. C.

    2013-12-01

    High spatial resolution three-dimensional (3D) measurements of vegetation by remote sensing are advancing ecological research and environmental management. However, substantial economic and logistical costs limit this application, especially for observing phenological dynamics in ecosystem structure and spectral traits. Here we demonstrate a new aerial remote sensing system enabling routine and inexpensive aerial 3D measurements of canopy structure and spectral attributes, with properties similar to those of LIDAR, but with RGB (red-green-blue) spectral attributes for each point, enabling high frequency observations within a single growing season. This 'Ecosynth' methodology applies photogrammetric ''Structure from Motion'' computer vision algorithms to large sets of highly overlapping low altitude (USA. Ecosynth canopy height maps (CHMs) were strong predictors of field-measured tree heights (R2 0.63 to 0.84) and were highly correlated with a LIDAR CHM (R 0.87) acquired 4 days earlier, though Ecosynth-based estimates of aboveground biomass densities included significant errors (31 - 36% of field-based estimates). Repeated scanning of a 0.25 ha forested area at six different times across a 16 month period revealed ecologically significant dynamics in canopy color at different heights and a structural shift upward in canopy density, as demonstrated by changes in vertical height profiles of point density and relative RGB brightness. Changes in canopy relative greenness were highly correlated (R2 = 0.88) with MODIS NDVI time series for the same area and vertical differences in canopy color revealed the early green up of the dominant canopy species, Liriodendron tulipifera, strong evidence that Ecosynth time series measurements capture vegetation structural and spectral dynamics at the spatial scale of individual trees. Observing canopy phenology in 3D at high temporal resolutions represents a breakthrough in forest ecology. Inexpensive user-deployed technologies for

  18. Surface Temperature Mapping of the University of Northern Iowa Campus Using High Resolution Thermal Infrared Aerial Imageries

    Directory of Open Access Journals (Sweden)

    Ramanathan Sugumaran

    2008-08-01

    Full Text Available The goal of this project was to map the surface temperature of the University of Northern Iowa campus using high-resolution thermal infrared aerial imageries. A thermal camera with a spectral bandwidth of 3.0-5.0 μm was flown at the average altitude of 600 m, achieving ground resolution of 29 cm. Ground control data was used to construct the pixelto-temperature conversion model, which was later used to produce temperature maps of the entire campus and also for validation of the model. The temperature map then was used to assess the building rooftop conditions and steam line faults in the study area. Assessment of the temperature map revealed a number of building structures that may be subject to insulation improvement due to their high surface temperatures leaks. Several hot spots were also identified on the campus for steam pipelines faults. High-resolution thermal infrared imagery proved highly effective tool for precise heat anomaly detection on the campus, and it can be used by university facility services for effective future maintenance of buildings and grounds.

  19. Surface Temperature Mapping of the University of Northern Iowa Campus Using High Resolution Thermal Infrared Aerial Imageries

    Science.gov (United States)

    Savelyev, Alexander; Sugumaran, Ramanathan

    2008-01-01

    The goal of this project was to map the surface temperature of the University of Northern Iowa campus using high-resolution thermal infrared aerial imageries. A thermal camera with a spectral bandwidth of 3.0-5.0 μm was flown at the average altitude of 600 m, achieving ground resolution of 29 cm. Ground control data was used to construct the pixel- to-temperature conversion model, which was later used to produce temperature maps of the entire campus and also for validation of the model. The temperature map then was used to assess the building rooftop conditions and steam line faults in the study area. Assessment of the temperature map revealed a number of building structures that may be subject to insulation improvement due to their high surface temperatures leaks. Several hot spots were also identified on the campus for steam pipelines faults. High-resolution thermal infrared imagery proved highly effective tool for precise heat anomaly detection on the campus, and it can be used by university facility services for effective future maintenance of buildings and grounds. PMID:27873800

  20. Reconstructed Image Spatial Resolution of Multiple Coincidences Compton Imager

    Science.gov (United States)

    Andreyev, Andriy; Sitek, Arkadiusz; Celler, Anna

    2010-02-01

    We study the multiple coincidences Compton imager (MCCI) which is based on a simultaneous acquisition of several photons emitted in cascade from a single nuclear decay. Theoretically, this technique should provide a major improvement in localization of a single radioactive source as compared to a standard Compton camera. In this work, we investigated the performance and limitations of MCCI using Monte Carlo computer simulations. Spatial resolutions of the reconstructed point source have been studied as a function of the MCCI parameters, including geometrical dimensions and detector characteristics such as materials, energy and spatial resolutions.

  1. Implementation of an IMU Aided Image Stacking Algorithm in a Digital Camera for Unmanned Aerial Vehicles.

    Science.gov (United States)

    Audi, Ahmad; Pierrot-Deseilligny, Marc; Meynard, Christophe; Thom, Christian

    2017-07-18

    Images acquired with a long exposure time using a camera embedded on UAVs (Unmanned Aerial Vehicles) exhibit motion blur due to the erratic movements of the UAV. The aim of the present work is to be able to acquire several images with a short exposure time and use an image processing algorithm to produce a stacked image with an equivalent long exposure time. Our method is based on the feature point image registration technique. The algorithm is implemented on the light-weight IGN (Institut national de l'information géographique) camera, which has an IMU (Inertial Measurement Unit) sensor and an SoC (System on Chip)/FPGA (Field-Programmable Gate Array). To obtain the correct parameters for the resampling of the images, the proposed method accurately estimates the geometrical transformation between the first and the N -th images. Feature points are detected in the first image using the FAST (Features from Accelerated Segment Test) detector, then homologous points on other images are obtained by template matching using an initial position benefiting greatly from the presence of the IMU sensor. The SoC/FPGA in the camera is used to speed up some parts of the algorithm in order to achieve real-time performance as our ultimate objective is to exclusively write the resulting image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images and block diagrams of the described architecture. The resulting stacked image obtained for real surveys does not seem visually impaired. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real time the gyrometers of the IMU. Timing results demonstrate that the image resampling part of this algorithm is the most demanding processing task and should also be accelerated in the FPGA in future work.

  2. Implementation of an IMU Aided Image Stacking Algorithm in a Digital Camera for Unmanned Aerial Vehicles

    Directory of Open Access Journals (Sweden)

    Ahmad Audi

    2017-07-01

    Full Text Available Images acquired with a long exposure time using a camera embedded on UAVs (Unmanned Aerial Vehicles exhibit motion blur due to the erratic movements of the UAV. The aim of the present work is to be able to acquire several images with a short exposure time and use an image processing algorithm to produce a stacked image with an equivalent long exposure time. Our method is based on the feature point image registration technique. The algorithm is implemented on the light-weight IGN (Institut national de l’information géographique camera, which has an IMU (Inertial Measurement Unit sensor and an SoC (System on Chip/FPGA (Field-Programmable Gate Array. To obtain the correct parameters for the resampling of the images, the proposed method accurately estimates the geometrical transformation between the first and the N-th images. Feature points are detected in the first image using the FAST (Features from Accelerated Segment Test detector, then homologous points on other images are obtained by template matching using an initial position benefiting greatly from the presence of the IMU sensor. The SoC/FPGA in the camera is used to speed up some parts of the algorithm in order to achieve real-time performance as our ultimate objective is to exclusively write the resulting image to save bandwidth on the storage device. The paper includes a detailed description of the implemented algorithm, resource usage summary, resulting processing time, resulting images and block diagrams of the described architecture. The resulting stacked image obtained for real surveys does not seem visually impaired. An interesting by-product of this algorithm is the 3D rotation estimated by a photogrammetric method between poses, which can be used to recalibrate in real time the gyrometers of the IMU. Timing results demonstrate that the image resampling part of this algorithm is the most demanding processing task and should also be accelerated in the FPGA in future work.

  3. Archaeological Feature Detection from Archive Aerial Photography with a Sfm-Mvs and Image Enhancement Pipeline

    Science.gov (United States)

    Peppa, M. V.; Mills, J. P.; Fieber, K. D.; Haynes, I.; Turner, S.; Turner, A.; Douglas, M.; Bryan, P. G.

    2018-05-01

    Understanding and protecting cultural heritage involves the detection and long-term documentation of archaeological remains alongside the spatio-temporal analysis of their landscape evolution. Archive aerial photography can illuminate traces of ancient features which typically appear with different brightness values from their surrounding environment, but are not always well defined. This research investigates the implementation of the Structure-from-Motion - Multi-View Stereo image matching approach with an image enhancement algorithm to derive three epochs of orthomosaics and digital surface models from visible and near infrared historic aerial photography. The enhancement algorithm uses decorrelation stretching to improve the contrast of the orthomosaics so as archaeological features are better detected. Results include 2D / 3D locations of detected archaeological traces stored into a geodatabase for further archaeological interpretation and correlation with benchmark observations. The study also discusses the merits and difficulties of the process involved. This research is based on a European-wide project, entitled "Cultural Heritage Through Time", and the case study research was carried out as a component of the project in the UK.

  4. Neural-network classifiers for automatic real-world aerial image recognition

    Science.gov (United States)

    Greenberg, Shlomo; Guterman, Hugo

    1996-08-01

    We describe the application of the multilayer perceptron (MLP) network and a version of the adaptive resonance theory version 2-A (ART 2-A) network to the problem of automatic aerial image recognition (AAIR). The classification of aerial images, independent of their positions and orientations, is required for automatic tracking and target recognition. Invariance is achieved by the use of different invariant feature spaces in combination with supervised and unsupervised neural networks. The performance of neural-network-based classifiers in conjunction with several types of invariant AAIR global features, such as the Fourier-transform space, Zernike moments, central moments, and polar transforms, are examined. The advantages of this approach are discussed. The performance of the MLP network is compared with that of a classical correlator. The MLP neural-network correlator outperformed the binary phase-only filter (BPOF) correlator. It was found that the ART 2-A distinguished itself with its speed and its low number of required training vectors. However, only the MLP classifier was able to deal with a combination of shift and rotation geometric distortions.

  5. Building Change Detection from Bi-Temporal Dense-Matching Point Clouds and Aerial Images.

    Science.gov (United States)

    Pang, Shiyan; Hu, Xiangyun; Cai, Zhongliang; Gong, Jinqi; Zhang, Mi

    2018-03-24

    In this work, a novel building change detection method from bi-temporal dense-matching point clouds and aerial images is proposed to address two major problems, namely, the robust acquisition of the changed objects above ground and the automatic classification of changed objects into buildings or non-buildings. For the acquisition of changed objects above ground, the change detection problem is converted into a binary classification, in which the changed area above ground is regarded as the foreground and the other area as the background. For the gridded points of each period, the graph cuts algorithm is adopted to classify the points into foreground and background, followed by the region-growing algorithm to form candidate changed building objects. A novel structural feature that was extracted from aerial images is constructed to classify the candidate changed building objects into buildings and non-buildings. The changed building objects are further classified as "newly built", "taller", "demolished", and "lower" by combining the classification and the digital surface models of two periods. Finally, three typical areas from a large dataset are used to validate the proposed method. Numerous experiments demonstrate the effectiveness of the proposed algorithm.

  6. Reproducible high-resolution multispectral image acquisition in dermatology

    Science.gov (United States)

    Duliu, Alexandru; Gardiazabal, José; Lasser, Tobias; Navab, Nassir

    2015-07-01

    Multispectral image acquisitions are increasingly popular in dermatology, due to their improved spectral resolution which enables better tissue discrimination. Most applications however focus on restricted regions of interest, imaging only small lesions. In this work we present and discuss an imaging framework for high-resolution multispectral imaging on large regions of interest.

  7. Investigation of an Autofocusing Method for Visible Aerial Cameras Based on Image Processing Techniques

    Directory of Open Access Journals (Sweden)

    Zhichao Chen

    2016-01-01

    Full Text Available In order to realize the autofocusing in aerial camera, an autofocusing system is established and its characteristics such as working principle and optical-mechanical structure and focus evaluation function are investigated. The reason for defocusing in aviation camera is analyzed and several autofocusing methods along with appropriate focus evaluation functions are introduced based on the image processing techniques. The proposed autofocusing system is designed and implemented using two CMOS detectors. The experiment results showed that the proposed method met the aviation camera focusing accuracy requirement, and a maximum focusing error of less than half of the focus depth is achieved. The system designed in this paper can find the optical imaging focal plane in real-time; as such, this novel design has great potential in practical engineering, especially aerospace applications.

  8. Preliminary analysis of the forest health state based on multispectral images acquired by Unmanned Aerial Vehicle

    Directory of Open Access Journals (Sweden)

    Czapski Paweł

    2015-09-01

    Full Text Available The main purpose of this publication is to present the current progress of the work associated with the use of a lightweight unmanned platforms for various environmental studies. Current development in information technology, electronics and sensors miniaturisation allows mounting multispectral cameras and scanners on unmanned aerial vehicle (UAV that could only be used on board aircraft and satellites. Remote Sensing Division in the Institute of Aviation carries out innovative researches using multisensory platform and lightweight unmanned vehicle to evaluate the health state of forests in Wielkopolska province. In this paper, applicability of multispectral images analysis acquired several times during the growing season from low altitude (up to 800m is presented. We present remote sensing indicators computed by our software and common methods for assessing state of trees health. The correctness of applied methods is verified using analysis of satellite scenes acquired by Landsat 8 OLI instrument (Operational Land Imager.

  9. Cooperative conflict detection and resolution of civil unmanned aerial vehicles in metropolis

    Directory of Open Access Journals (Sweden)

    Jian Yang

    2016-06-01

    Full Text Available Unmanned air vehicles have recently attracted attention of many researchers because of their potential civil applications. A systematic integration of unmanned air vehicles in non-segregated airspace is required that allows safe operation of unmanned air vehicles along with other manned aircrafts. One of the critical issues is conflict detection and resolution. This article proposes to solve unmanned air vehicles’ conflict detection and resolution problem in metropolis airspace. First, the structure of metropolis airspace in the coming future is studied, and the airspace conflict problem between different unmanned air vehicles is analyzed by velocity obstacle theory. Second, a conflict detection and resolution framework in metropolis is proposed, and factors that have influences on conflict-free solutions are discussed. Third, the multi-unmanned air vehicle conflict resolution problem is formalized as a nonlinear optimization problem with the aim of minimizing overall conflict resolution consumption. The safe separation constraint is further discussed to improve the computation efficiency. When the speeds of conflict-involved unmanned air vehicles are equal, the nonlinear safe separation constraint is transformed into linear constraints. The problem is solved by mixed integer convex programming. When unmanned air vehicles are with unequal speeds, we propose to solve the nonlinear optimization problem by stochastic parallel gradient descent–based method. Our approaches are demonstrated in computational examples.

  10. Isotope specific resolution recovery image reconstruction in high resolution PET imaging

    NARCIS (Netherlands)

    Kotasidis, Fotis A.; Angelis, Georgios I.; Anton-Rodriguez, Jose; Matthews, Julian C.; Reader, Andrew J.; Zaidi, Habib

    Purpose: Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to

  11. Application of Super-Resolution Convolutional Neural Network for Enhancing Image Resolution in Chest CT.

    Science.gov (United States)

    Umehara, Kensuke; Ota, Junko; Ishida, Takayuki

    2017-10-18

    In this study, the super-resolution convolutional neural network (SRCNN) scheme, which is the emerging deep-learning-based super-resolution method for enhancing image resolution in chest CT images, was applied and evaluated using the post-processing approach. For evaluation, 89 chest CT cases were sampled from The Cancer Imaging Archive. The 89 CT cases were divided randomly into 45 training cases and 44 external test cases. The SRCNN was trained using the training dataset. With the trained SRCNN, a high-resolution image was reconstructed from a low-resolution image, which was down-sampled from an original test image. For quantitative evaluation, two image quality metrics were measured and compared to those of the conventional linear interpolation methods. The image restoration quality of the SRCNN scheme was significantly higher than that of the linear interpolation methods (p < 0.001 or p < 0.05). The high-resolution image reconstructed by the SRCNN scheme was highly restored and comparable to the original reference image, in particular, for a ×2 magnification. These results indicate that the SRCNN scheme significantly outperforms the linear interpolation methods for enhancing image resolution in chest CT images. The results also suggest that SRCNN may become a potential solution for generating high-resolution CT images from standard CT images.

  12. CLASSIFICATION OF CROP-SHELTER COVERAGE BY RGB AERIAL IMAGES: A COMPENDIUM OF EXPERIENCES AND FINDINGS

    Directory of Open Access Journals (Sweden)

    Claudia Arcidiacono

    2010-09-01

    Full Text Available Image processing is a powerful tool apt to perform selective data extraction from high-content images. In agricultural studies, image processing has been applied to different scopes, among them the classification of crop shelters has been recently considered especially in areas where there is a lack of public control in the building activity. The application of image processing to crop-shelter feature recognition make it possible to automatically produce thematic maps that constitute a basic knowledge for local authorities to cope with environmental problems and for technicians to be used in their planning activity. This paper reviews the authors’ experience in the definition of methodologies, based on the main image processing methods, for crop-shelter feature extraction from aerial digital images. Some experiences of pixel-based and object-oriented methods are described and discussed. The results show that the methodology based on object-oriented methods improves crop-shelter classification and reduces computational time, compared to pixel-based methodologies.

  13. Atomic resolution imaging of ferroelectric domains

    International Nuclear Information System (INIS)

    Bursill, L.A.

    1997-01-01

    Electron optical principles involved in obtaining atomic resolution images of ferroelectric domains are reviewed, including the methods available to obtain meaningful interpretation and analysis of the image detail in terms of the atomic structures. Recent work is concerned with establishing the relationship between the essentially static chemical nanodomains and the spatial and temporal fluctuations of the nanoscale polar domains present in the relaxor class of materials, including lead scandium tantalate (PST) and lead magnesium niobate (PMN). Correct interpretation of the images required use of Next Nearest Neighbour Ising model simulations for the chemical domain textures upon which we must superimpose the polar domain textures; an introduction to this work is presented. A thorough analysis of the atomic scale chemical inhomogeneities, based upon the HRTEM results, has lead to an improved formulation of the theory of the dielectric response of PMN and PST, which is capable to predict the observed temperature and frequency dependence. HRTEM may be combined with solid state and statistical physics principles to provide a deeper understanding of structure/property relationships. 15 refs., 6 figs

  14. Far-field super-resolution imaging of resonant multiples

    KAUST Repository

    Guo, Bowen

    2016-05-20

    We demonstrate for the first time that seismic resonant multiples, usually considered as noise, can be used for super-resolution imaging in the far-field region of sources and receivers. Tests with both synthetic data and field data show that resonant multiples can image reflector boundaries with resolutions more than twice the classical resolution limit. Resolution increases with the order of the resonant multiples. This procedure has important applications in earthquake and exploration seismology, radar, sonar, LIDAR (light detection and ranging), and ultrasound imaging, where the multiples can be used to make high-resolution images.

  15. High resolution imaging detectors and applications

    CERN Document Server

    Saha, Swapan K

    2015-01-01

    Interferometric observations need snapshots of very high time resolution of the order of (i) frame integration of about 100 Hz or (ii) photon-recording rates of several megahertz (MHz). Detectors play a key role in astronomical observations, and since the explanation of the photoelectric effect by Albert Einstein, the technology has evolved rather fast. The present-day technology has made it possible to develop large-format complementary metal oxide–semiconductor (CMOS) and charge-coupled device (CCD) array mosaics, orthogonal transfer CCDs, electron-multiplication CCDs, electron-avalanche photodiode arrays, and quantum-well infrared (IR) photon detectors. The requirements to develop artifact-free photon shot noise-limited images are higher sensitivity and quantum efficiency, reduced noise that includes dark current, read-out and amplifier noise, smaller point-spread functions, and higher spectral bandwidth. This book aims to address such systems, technologies and design, evaluation and calibration, control...

  16. Vehicle Detection in Aerial Images Based on Region Convolutional Neural Networks and Hard Negative Example Mining.

    Science.gov (United States)

    Tang, Tianyu; Zhou, Shilin; Deng, Zhipeng; Zou, Huanxin; Lei, Lin

    2017-02-10

    Detecting vehicles in aerial imagery plays an important role in a wide range of applications. The current vehicle detection methods are mostly based on sliding-window search and handcrafted or shallow-learning-based features, having limited description capability and heavy computational costs. Recently, due to the powerful feature representations, region convolutional neural networks (CNN) based detection methods have achieved state-of-the-art performance in computer vision, especially Faster R-CNN. However, directly using it for vehicle detection in aerial images has many limitations: (1) region proposal network (RPN) in Faster R-CNN has poor performance for accurately locating small-sized vehicles, due to the relatively coarse feature maps; and (2) the classifier after RPN cannot distinguish vehicles and complex backgrounds well. In this study, an improved detection method based on Faster R-CNN is proposed in order to accomplish the two challenges mentioned above. Firstly, to improve the recall, we employ a hyper region proposal network (HRPN) to extract vehicle-like targets with a combination of hierarchical feature maps. Then, we replace the classifier after RPN by a cascade of boosted classifiers to verify the candidate regions, aiming at reducing false detection by negative example mining. We evaluate our method on the Munich vehicle dataset and the collected vehicle dataset, with improvements in accuracy and robustness compared to existing methods.

  17. Aerial image measurement technique for automated reticle defect disposition (ARDD) in wafer fabs

    Science.gov (United States)

    Zibold, Axel M.; Schmid, Rainer M.; Stegemann, B.; Scheruebl, Thomas; Harnisch, Wolfgang; Kobiyama, Yuji

    2004-08-01

    The Aerial Image Measurement System (AIMS)* for 193 nm lithography emulation has been brought into operation successfully worldwide. A second generation system comprising 193 nm AIMS capability, mini-environment and SMIF, the AIMS fab 193 plus is currently introduced into the market. By adjustment of numerical aperture (NA), illumination type and partial illumination coherence to match the conditions in 193 nm steppers or scanners, it can emulate the exposure tool for any type of reticles like binary, OPC and PSM down to the 65 nm node. The system allows a rapid prediction of wafer printability of defects or defect repairs, and critical features, like dense patterns or contacts on the masks without the need to perform expensive image qualification consisting of test wafer exposures followed by SEM measurements. Therefore, AIMS is a mask quality verification standard for high-end photo masks and established in mask shops worldwide. The progress on the AIMS technology described in this paper will highlight that besides mask shops there will be a very beneficial use of the AIMS in the wafer fab and we propose an Automated Reticle Defect Disposition (ARDD) process. With smaller nodes, where design rules are 65 nm or less, it is expected that smaller defects on reticles will occur in increasing numbers in the wafer fab. These smaller mask defects will matter more and more and become a serious yield limiting factor. With increasing mask prices and increasing number of defects and severability on reticles it will become cost beneficial to perform defect disposition on the reticles in wafer production. Currently ongoing studies demonstrate AIMS benefits for wafer fab applications. An outlook will be given for extension of 193 nm aerial imaging down to the 45 nm node based on emulation of immersion scanners.

  18. Detection of laurel wilt disease in avocado using low altitude aerial imaging.

    Science.gov (United States)

    de Castro, Ana I; Ehsani, Reza; Ploetz, Randy C; Crane, Jonathan H; Buchanon, Sherrie

    2015-01-01

    Laurel wilt is a lethal disease of plants in the Lauraceae plant family, including avocado (Persea americana). This devastating disease has spread rapidly along the southeastern seaboard of the United States and has begun to affect commercial avocado production in Florida. The main objective of this study was to evaluate the potential to discriminate laurel wilt-affected avocado trees using aerial images taken with a modified camera during helicopter surveys at low-altitude in the commercial avocado production area. The ability to distinguish laurel wilt-affected trees from other factors that produce similar external symptoms was also studied. RmodGB digital values of healthy trees and laurel wilt-affected trees, as well as fruit stress and vines covering trees were used to calculate several vegetation indices (VIs), band ratios, and VI combinations. These indices were subjected to analysis of variance (ANOVA) and an M-statistic was performed in order to quantify the separability of those classes. Significant differences in spectral values among laurel wilt affected and healthy trees were observed in all vegetation indices calculated, although the best results were achieved with Excess Red (ExR), (Red-Green) and Combination 1 (COMB1) in all locations. B/G showed a very good potential for separate the other factors with symptoms similar to laurel wilt-affected trees, such as fruit stress and vines covering trees, from laurel wilt-affected trees. These consistent results prove the usefulness of using a modified camera (RmodGB) to discriminate laurel wilt-affected avocado trees from healthy trees, as well as from other factors that cause the same symptoms and suggest performing the classification in further research. According to our results, ExR and B/G should be utilized to develop an algorithm or decision rules to classify aerial images, since they showed the highest capacity to discriminate laurel wilt-affected trees. This methodology may allow the rapid detection

  19. Detection of laurel wilt disease in avocado using low altitude aerial imaging.

    Directory of Open Access Journals (Sweden)

    Ana I de Castro

    Full Text Available Laurel wilt is a lethal disease of plants in the Lauraceae plant family, including avocado (Persea americana. This devastating disease has spread rapidly along the southeastern seaboard of the United States and has begun to affect commercial avocado production in Florida. The main objective of this study was to evaluate the potential to discriminate laurel wilt-affected avocado trees using aerial images taken with a modified camera during helicopter surveys at low-altitude in the commercial avocado production area. The ability to distinguish laurel wilt-affected trees from other factors that produce similar external symptoms was also studied. RmodGB digital values of healthy trees and laurel wilt-affected trees, as well as fruit stress and vines covering trees were used to calculate several vegetation indices (VIs, band ratios, and VI combinations. These indices were subjected to analysis of variance (ANOVA and an M-statistic was performed in order to quantify the separability of those classes. Significant differences in spectral values among laurel wilt affected and healthy trees were observed in all vegetation indices calculated, although the best results were achieved with Excess Red (ExR, (Red-Green and Combination 1 (COMB1 in all locations. B/G showed a very good potential for separate the other factors with symptoms similar to laurel wilt-affected trees, such as fruit stress and vines covering trees, from laurel wilt-affected trees. These consistent results prove the usefulness of using a modified camera (RmodGB to discriminate laurel wilt-affected avocado trees from healthy trees, as well as from other factors that cause the same symptoms and suggest performing the classification in further research. According to our results, ExR and B/G should be utilized to develop an algorithm or decision rules to classify aerial images, since they showed the highest capacity to discriminate laurel wilt-affected trees. This methodology may allow the

  20. Estimating Discharge in Low-Order Rivers With High-Resolution Aerial Imagery

    OpenAIRE

    King, Tyler V.; Neilson, Bethany T.; Rasmussen, Mitchell T.

    2018-01-01

    Remote sensing of river discharge promises to augment in situ gauging stations, but the majority of research in this field focuses on large rivers (>50 m wide). We present a method for estimating volumetric river discharge in low-order (wide) rivers from remotely sensed data by coupling high-resolution imagery with one-dimensional hydraulic modeling at so-called virtual gauging stations. These locations were identified as locations where the river contracted under low flows, exposing a substa...

  1. Re-examining data-intensive surface water models with high-resolution topography derived from unmanned aerial system photogrammetry

    Science.gov (United States)

    Pai, H.; Tyler, S.

    2017-12-01

    Small, unmanned aerial systems (sUAS) are quickly becoming a cost-effective and easily deployable tool for high spatial resolution environmental sensing. Land surface studies from sUAS imagery have largely focused on accurate topographic mapping, quantifying geomorphologic changes, and classification/identification of vegetation, sediment, and water quality tracers. In this work, we explore a further application of sUAS-derived topographic mapping to a two-dimensional (2-d), depth-averaged river hydraulic model (Flow and Sediment Transport with Morphological Evolution of Channels, FaSTMECH) along a short, meandering reach of East River, Colorado. On August 8, 2016, we flew a sUAS as part of the Center for Transformative Environmental Monitoring Programs with a consumer-grade visible camera and created a digital elevation map ( 1.5 cm resolution; 5 cm accuracy; 500 m long river corridor) with Agisoft Photoscan software. With the elevation map, we created a longitudinal water surface elevation (WSE) profile by manually delineating the bank-water interface and river bathymetry by applying refraction corrections for more accurate water depth estimates, an area of ongoing research for shallow and clear river systems. We tested both uncorrected and refraction-corrected bathymetries with the steady-state, 2-d model, applying sensitivities for dissipation parameters (bed roughness and eddy characteristics). Model performance was judged from the WSE data and measured stream velocities. While the models converged, performance and insights from model output could be improved with better bed roughness characterization and additional water depth cross-validation for refraction corrections. Overall, this work shows the applicability of sUAS-derived products to a multidimensional river model, where bathymetric data of high resolution and accuracy are key model input requirements.

  2. Generation of Land Cover Maps Using High-Resolution Multispectral Aerial Cameras

    DEFF Research Database (Denmark)

    Höhle, Joachim

    2013-01-01

    . The classification had an overall accuracy of 79%. Suggestions for the improvements in the applied methodology are made. The potential of land cover maps lies in updating of topographic databases, quality control of maps, studies of town development, and other geo-spatial domain applications. The automatic...... for classification of land cover. A high degree of automation can be achieved. The obtained results of a practical example are checked with reference values derived from ortho-images in natural colour and from colour images using stereo-vision. An error matrix is applied in the evaluation of the results...

  3. USGS High Resolution Orthoimagery Collection - Historical - National Geospatial Data Asset (NGDA) High Resolution Orthoimagery

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — USGS high resolution orthorectified images from The National Map combine the image characteristics of an aerial photograph with the geometric qualities of a map. An...

  4. The orthorectified technology for UAV aerial remote sensing image based on the Programmable GPU

    International Nuclear Information System (INIS)

    Jin, Liu; Ying-cheng, Li; De-long, Li; Chang-sheng, Teng; Wen-hao, Zhang

    2014-01-01

    Considering the time requirements of the disaster emergency aerial remote sensing data acquisition and processing, this paper introduced the GPU parallel processing in orthorectification algorithm. Meanwhile, our experiments verified the correctness and feasibility of CUDA parallel processing algorithm, and the algorithm can effectively solve the problem of calculation large, time-consuming for ortho rectification process, realized fast processing of UAV airborne remote sensing image orthorectification based on GPU. The experimental results indicate that using the assumption of same accuracy of proposed method with CPU, the processing time is reduced obviously, maximum acceleration can reach more than 12 times, which greatly enhances the emergency surveying and mapping processing of rapid reaction rate, and has a broad application

  5. Evaluation of Different Irrigation Methods for an Apple Orchard Using an Aerial Imaging System

    Directory of Open Access Journals (Sweden)

    Duke M. Bulanon

    2016-06-01

    Full Text Available Regular monitoring and assessment of crops is one of the keys to optimal crop production. This research presents the development of a monitoring system called the Crop Monitoring and Assessment Platform (C-MAP. The C-MAP is composed of an image acquisition unit which is an off-the-shelf unmanned aerial vehicle (UAV equipped with a multispectral camera (near-infrared, green, blue, and an image processing and analysis component. The experimental apple orchard at the Parma Research and Extension Center of the University of Idaho was used as the target for monitoring and evaluation. Five experimental rows of the orchard were randomly treated with five different irrigation methods. An image processing algorithm to detect individual trees was developed to facilitate the analysis of the rows and it was able to detect over 90% of the trees. The image analysis of the experimental rows was based on vegetation indices and results showed that there was a significant difference in the Enhanced Normalized Difference Vegetation Index (ENDVI among the five different irrigation methods. This demonstrates that the C-MAP has very good potential as a monitoring tool for orchard management.

  6. Automated Snow Extent Mapping Based on Orthophoto Images from Unmanned Aerial Vehicles

    Science.gov (United States)

    Niedzielski, Tomasz; Spallek, Waldemar; Witek-Kasprzak, Matylda

    2018-04-01

    The paper presents the application of the k-means clustering in the process of automated snow extent mapping using orthophoto images generated using the Structure-from-Motion (SfM) algorithm from oblique aerial photographs taken by unmanned aerial vehicle (UAV). A simple classification approach has been implemented to discriminate between snow-free and snow-covered terrain. The procedure uses the k-means clustering and classifies orthophoto images based on the three-dimensional space of red-green-blue (RGB) or near-infrared-red-green (NIRRG) or near-infrared-green-blue (NIRGB) bands. To test the method, several field experiments have been carried out, both in situations when snow cover was continuous and when it was patchy. The experiments have been conducted using three fixed-wing UAVs (swinglet CAM by senseFly, eBee by senseFly, and Birdie by FlyTech UAV) on 10/04/2015, 23/03/2016, and 16/03/2017 within three test sites in the Izerskie Mountains in southwestern Poland. The resulting snow extent maps, produced automatically using the classification method, have been validated against real snow extents delineated through a visual analysis and interpretation offered by human analysts. For the simplest classification setup, which assumes two classes in the k-means clustering, the extent of snow patches was estimated accurately, with areal underestimation of 4.6% (RGB) and overestimation of 5.5% (NIRGB). For continuous snow cover with sparse discontinuities at places where trees or bushes protruded from snow, the agreement between automatically produced snow extent maps and observations was better, i.e. 1.5% (underestimation with RGB) and 0.7-0.9% (overestimation, either with RGB or with NIRRG). Shadows on snow were found to be mainly responsible for the misclassification.

  7. Some results on the investigation of earth resources by aerial and polygon methods

    Energy Technology Data Exchange (ETDEWEB)

    Vinnichenko, N K; Tishchenko, A P

    1980-01-01

    Papers are presented on integrated aerial-satellite remote sensing systems, the resolution of TV scanning systems, the transfer of spectral contrasts in multispectral photography, and pseudocolor representation of multispectral aerial images. Consideration is also given to the use of spectral and physical-geographic characteristics of natural objects on the earth's surface for the interpretation of multispectral satellite photographs, the determination of the types and state of crops from multispectral aerial images, and the automated classification of agricultural objects from their multispectral aerial images.

  8. Woodland Mapping at Single-Tree Levels Using Object-Oriented Classification of Unmanned Aerial Vehicle (uav) Images

    Science.gov (United States)

    Chenari, A.; Erfanifard, Y.; Dehghani, M.; Pourghasemi, H. R.

    2017-09-01

    Remotely sensed datasets offer a reliable means to precisely estimate biophysical characteristics of individual species sparsely distributed in open woodlands. Moreover, object-oriented classification has exhibited significant advantages over different classification methods for delineation of tree crowns and recognition of species in various types of ecosystems. However, it still is unclear if this widely-used classification method can have its advantages on unmanned aerial vehicle (UAV) digital images for mapping vegetation cover at single-tree levels. In this study, UAV orthoimagery was classified using object-oriented classification method for mapping a part of wild pistachio nature reserve in Zagros open woodlands, Fars Province, Iran. This research focused on recognizing two main species of the study area (i.e., wild pistachio and wild almond) and estimating their mean crown area. The orthoimage of study area was consisted of 1,076 images with spatial resolution of 3.47 cm which was georeferenced using 12 ground control points (RMSE=8 cm) gathered by real-time kinematic (RTK) method. The results showed that the UAV orthoimagery classified by object-oriented method efficiently estimated mean crown area of wild pistachios (52.09±24.67 m2) and wild almonds (3.97±1.69 m2) with no significant difference with their observed values (α=0.05). In addition, the results showed that wild pistachios (accuracy of 0.90 and precision of 0.92) and wild almonds (accuracy of 0.90 and precision of 0.89) were well recognized by image segmentation. In general, we concluded that UAV orthoimagery can efficiently produce precise biophysical data of vegetation stands at single-tree levels, which therefore is suitable for assessment and monitoring open woodlands.

  9. WOODLAND MAPPING AT SINGLE-TREE LEVELS USING OBJECT-ORIENTED CLASSIFICATION OF UNMANNED AERIAL VEHICLE (UAV IMAGES

    Directory of Open Access Journals (Sweden)

    A. Chenari

    2017-09-01

    Full Text Available Remotely sensed datasets offer a reliable means to precisely estimate biophysical characteristics of individual species sparsely distributed in open woodlands. Moreover, object-oriented classification has exhibited significant advantages over different classification methods for delineation of tree crowns and recognition of species in various types of ecosystems. However, it still is unclear if this widely-used classification method can have its advantages on unmanned aerial vehicle (UAV digital images for mapping vegetation cover at single-tree levels. In this study, UAV orthoimagery was classified using object-oriented classification method for mapping a part of wild pistachio nature reserve in Zagros open woodlands, Fars Province, Iran. This research focused on recognizing two main species of the study area (i.e., wild pistachio and wild almond and estimating their mean crown area. The orthoimage of study area was consisted of 1,076 images with spatial resolution of 3.47 cm which was georeferenced using 12 ground control points (RMSE=8 cm gathered by real-time kinematic (RTK method. The results showed that the UAV orthoimagery classified by object-oriented method efficiently estimated mean crown area of wild pistachios (52.09±24.67 m2 and wild almonds (3.97±1.69 m2 with no significant difference with their observed values (α=0.05. In addition, the results showed that wild pistachios (accuracy of 0.90 and precision of 0.92 and wild almonds (accuracy of 0.90 and precision of 0.89 were well recognized by image segmentation. In general, we concluded that UAV orthoimagery can efficiently produce precise biophysical data of vegetation stands at single-tree levels, which therefore is suitable for assessment and monitoring open woodlands.

  10. Automatic urban debris zone extraction from post-hurricane very high-resolution satellite and aerial imagery

    Directory of Open Access Journals (Sweden)

    Shasha Jiang

    2016-05-01

    Full Text Available Automated remote sensing methods have not gained widespread usage for damage assessment after hurricane events, especially for low-rise buildings, such as individual houses and small businesses. Hurricane wind, storm surge with waves, and inland flooding have unique damage signatures, further complicating the development of robust automated assessment methodologies. As a step toward realizing automated damage assessment for multi-hazard hurricane events, this paper presents a mono-temporal image classification methodology that quickly and accurately differentiates urban debris from non-debris areas using post-event images. Three classification approaches are presented: spectral, textural, and combined spectral–textural. The methodology is demonstrated for Gulfport, Mississippi, using IKONOS panchromatic satellite and NOAA aerial colour imagery collected after 2005 Hurricane Katrina. The results show that multivariate texture information significantly improves debris class detection performance by decreasing the confusion between debris and other land cover types, and the extracted debris zone accurately captures debris distribution. Additionally, the extracted debris boundary is approximately equivalent regardless of imagery type, demonstrating the flexibility and robustness of the debris mapping methodology. While the test case presents results for hurricane hazards, the proposed methodology is generally developed and expected to be effective in delineating debris zones for other natural hazards, including tsunamis, tornadoes, and earthquakes.

  11. Issues in bridge deck damage evaluation using aerial photos

    Science.gov (United States)

    Natarajan, M.; Chen, S. E.; Boyle, C.; Martin, E.; Hauser, E.

    2012-04-01

    Small format aerial photography (SFAP) with low flying technique is proposed for damage evaluation of bridge decks. High resolution images obtained using under-belly photography can be used to quantify the various bridge deck problems. The conventional truck-mount or vehicle-mount deck imaging technologies require a large number of image samples. Hence the physical scanning is time consuming and it is also challenging consider the size and location of a bridge. Aerial imaging overcomes these issues, but they face different kinds of challenges that are posed by obstacles such as shadow from trees, power lines and vehicles, signs and luminaries structures. The image resolution uncertainty, which is a function of the pilot skills and flying conditions, may also add additional challenges to aerial imaging technique. Hence different image processing tools have to be integrated into a single package to achieve the desired task. This paper summarizes the challenges faced and the preliminary results are presented and discussed.

  12. An Effective Method for Detecting Potential Woodland Vernal Pools Using High-Resolution LiDAR Data and Aerial Imagery

    Directory of Open Access Journals (Sweden)

    Qiusheng Wu

    2014-11-01

    Full Text Available Effective conservation of woodland vernal pools—important components of regional amphibian diversity and ecosystem services—depends on locating and mapping these pools accurately. Current methods for identifying potential vernal pools are primarily based on visual interpretation and digitization of aerial photographs, with variable accuracy and low repeatability. In this paper, we present an effective and efficient method for detecting and mapping potential vernal pools using stochastic depression analysis with additional geospatial analysis. Our method was designed to take advantage of high-resolution light detection and ranging (LiDAR data, which are becoming increasingly available, though not yet frequently employed in vernal pool studies. We successfully detected more than 2000 potential vernal pools in a ~150 km2 study area in eastern Massachusetts. The accuracy assessment in our study indicated that the commission rates ranged from 2.5% to 6.0%, while the proxy omission rate was 8.2%, rates that are much lower than reported errors of previous vernal pool studies conducted in the northeastern United States. One significant advantage of our semi-automated approach for vernal pool identification is that it may reduce inconsistencies and alleviate repeatability concerns associated with manual photointerpretation methods. Another strength of our strategy is that, in addition to detecting the point-based vernal pool locations for the inventory, the boundaries of vernal pools can be extracted as polygon features to characterize their geometric properties, which are not available in the current statewide vernal pool databases in Massachusetts.

  13. COMPARISON OF POINT CLOUDS DERIVED FROM AERIAL IMAGE MATCHING WITH DATA FROM AIRBORNE LASER SCANNING

    Directory of Open Access Journals (Sweden)

    Dominik Wojciech

    2017-04-01

    Full Text Available The aim of this study was to invest igate the properties of point clouds derived from aerial image matching and to compare them with point clouds from airborne laser scanning. A set of aerial images acquired in years 2010 - 2013 over the city of Elblag were used for the analysis. Images were acquired with the use of three digital cameras: DMC II 230, DMC I and DigiCAM60 with a GSD varying from 4.5 cm to 15 cm. Eight sets of images that were used in the study were acquired at different stages of the growing season – from March to December. Two L iDAR point clouds were used for the comparison – one with a density of 1.3 p/m 2 and a second with a density of 10 p/m 2 . Based on the input images point clouds were created with the use of the semi - global matching method. The properties of the obtained poi nt clouds were analyzed in three ways: – b y the comparison of the vertical accuracy of point clouds with reference to a terrain profile surveyed on bare ground with GPS - RTK method – b y visual assessment of point cloud profiles generated both from SGM and LiDAR point clouds – b y visual assessment of a digital surface model generated from a SGM point cloud with reference to a digital surface model generated from a LiDAR point cloud. The conducted studies allowed a number of observations about the quality o f SGM point clouds to be formulated with respect to different factors. The main factors having influence on the quality of SGM point clouds are GSD and base/height ratio. The essential problem related to SGM point clouds are areas covered with vegetation w here SGM point clouds are visibly worse in terms of both accuracy and the representation of terrain surface. It is difficult to expect that in these areas SG M point clouds could replace LiDAR point clouds. This leads to a general conclusion that SGM point clouds are less reliable, more unpredictable and are dependent on more factors than LiDAR point clouds. Nevertheless, SGM point

  14. Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations.

    Science.gov (United States)

    Huang, Rongyong; Zheng, Shunyi; Hu, Kun

    2018-06-01

    Registration of large-scale optical images with airborne LiDAR data is the basis of the integration of photogrammetry and LiDAR. However, geometric misalignments still exist between some aerial optical images and airborne LiDAR point clouds. To eliminate such misalignments, we extended a method for registering close-range optical images with terrestrial LiDAR data to a variety of large-scale aerial optical images and airborne LiDAR data. The fundamental principle is to minimize the distances from the photogrammetric matching points to the terrestrial LiDAR data surface. Except for the satisfactory efficiency of about 79 s per 6732 × 8984 image, the experimental results also show that the unit weighted root mean square (RMS) of the image points is able to reach a sub-pixel level (0.45 to 0.62 pixel), and the actual horizontal and vertical accuracy can be greatly improved to a high level of 1/4⁻1/2 (0.17⁻0.27 m) and 1/8⁻1/4 (0.10⁻0.15 m) of the average LiDAR point distance respectively. Finally, the method is proved to be more accurate, feasible, efficient, and practical in variety of large-scale aerial optical image and LiDAR data.

  15. Earth analog image digitization of field, aerial, and lab experiment studies for Planetary Data System archiving.

    Science.gov (United States)

    Williams, D. A.; Nelson, D. M.

    2017-12-01

    A portion of the earth analog image archive at the Ronald Greeley Center for Planetary Studies (RGCPS)-the NASA Regional Planetary Information Facility at Arizona State University-is being digitized and will be added to the Planetary Data System (PDS) for public use. This will be a first addition of terrestrial data to the PDS specifically for comparative planetology studies. Digitization is separated into four tasks. First is the scanning of aerial photographs of volcanic and aeolian structures and flows. The second task is to scan field site images taken from ground and low-altitude aircraft of volcanic structures, lava flows, lava tubes, dunes, and wind streaks. The third image set to be scanned includes photographs of lab experiments from the NASA Planetary Aeolian Laboratory wind tunnels, vortex generator, and of wax models. Finally, rare NASA documents are being scanned and formatted as PDF files. Thousands of images are to be scanned for this project. Archiving of the data will follow the PDS4 standard, where the entire project is classified as a single bundle, with individual subjects (i.e., the Amboy Crater volcanic structure in the Mojave Desert of California) as collections. Within the collections, each image is considered a product, with a unique ID and associated XML document. Documents describing the image data, including the subject and context, will be included with each collection. Once complete, the data will be hosted by a PDS data node and available for public search and download. As one of the first earth analog datasets to be archived by the PDS, this project could prompt the digitizing and making available of historic datasets from other facilities for the scientific community.

  16. L-band HIgh Spatial Resolution Soil Moisture Mapping using SMALL UnManned Aerial Systems

    Science.gov (United States)

    Dai, E.; Venkitasubramony, A.; Gasiewski, A. J.; Stachura, M.; Elston, J. S.; Walter, B.; Lankford, D.; Corey, C.

    2017-12-01

    Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 provided new passive global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions of 36 km. However, there exists a need for measurements of soil moisture on much smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters. Compared with other methods of validation based on either in-situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed ( km scale) coverage at very high spatial resolution ( 15 m) suitable for scaling studies, and at comparatively low operator cost. To demonstrate the LDCR several flights had been performed during field experiments at the Canton Oklahoma Soilscape site and Yuma Colorado Irrigation Research Foundation (IRF) site in 2015 and 2016, respectively, using LDCR Revision A and Tempest sUAS. The scientific intercomparisons of LDCR retrieved soil moisture and in-situ measurements will be presented. LDCR Revision B has been built and integrated into SuperSwift sUAS and additional field experiments will be performed at IRF in 2017. In Revision B the IF signal is sampled at 80 MS/s to enable digital correlation and RFI mitigation capabilities, in addition to analog correlation. [1] McIntyre, E.M., A.J. Gasiewski, and D. Manda D, "Near Real-Time Passive C

  17. AN AERIAL-IMAGE DENSE MATCHING APPROACH BASED ON OPTICAL FLOW FIELD

    Directory of Open Access Journals (Sweden)

    W. Yuan

    2016-06-01

    Full Text Available Dense matching plays an important role in many fields, such as DEM (digital evaluation model producing, robot navigation and 3D environment reconstruction. Traditional approaches may meet the demand of accuracy. But the calculation time and out puts density is hardly be accepted. Focus on the matching efficiency and complex terrain surface matching feasibility an aerial image dense matching method based on optical flow field is proposed in this paper. First, some high accurate and uniformed control points are extracted by using the feature based matching method. Then the optical flow is calculated by using these control points, so as to determine the similar region between two images. Second, the optical flow field is interpolated by using the multi-level B-spline interpolation in the similar region and accomplished the pixel by pixel coarse matching. Final, the results related to the coarse matching refinement based on the combined constraint, which recognizes the same points between images. The experimental results have shown that our method can achieve per-pixel dense matching points, the matching accuracy achieves sub-pixel level, and fully meet the three-dimensional reconstruction and automatic generation of DSM-intensive matching’s requirements. The comparison experiments demonstrated that our approach’s matching efficiency is higher than semi-global matching (SGM and Patch-based multi-view stereo matching (PMVS which verifies the feasibility and effectiveness of the algorithm.

  18. Aerial image geolocalization by matching its line structure with route map

    Science.gov (United States)

    Kunina, I. A.; Terekhin, A. P.; Khanipov, T. M.; Kuznetsova, E. G.; Nikolaev, D. P.

    2017-03-01

    The classic way of aerial photographs geolocation is to bind their local coordinates to a geographic coordinate system using GPS and IMU data. At the same time the possibility of geolocation in a jammed navigation field is also of interest for practical purposes. In this paper we consider one approach to visual localization relatively to a vector road map without GPS. We suggest a geolocalization algorithm which detects image line segments and looks for a geometrical transformation which provides the best mapping between the obtained segments set and line segments in the road map. We consider IMU and altimeter data still known which allows to work with orthorectified images. The problem is hence reduced to a search for a transformation which contains an arbitrary shift and bounded rotation and scaling relatively to the vector map. These parameters are estimated using RANSAC by matching straight line segments from the image to vector map segments. We also investigate how the proposed algorithm's stability is influenced by segment coordinates (two spatial and one angular).

  19. FUNCTIONALITY ASSESSMENT OF ALGORITHMS FOR THE COLORING OF IMAGES IN TERMS OF INCREASING RADIOMETRIC VALUES OF AERIAL PHOTOGRAPHS ARCHIVES

    Directory of Open Access Journals (Sweden)

    Ewiak Ireneusz

    2016-12-01

    Full Text Available Available on the commercial market are a number of algorithms that enable assigning to pixels of a monochrome digital image suitable colors according to a strictly defined schedule. These algorithms have been recently used by professional film studios involved in the coloring of archival productions. This article provides an overview on the functionality of coloring algorithms in terms of their use to improve the interpretation quality of historical, black - and - white aerial photographs. The analysis covered intuitive (Recolored programs, as well as more advanced (Adobe After Effect, DaVinci Resolve programs. The use of their full functionality was limited by the too large information capacity of aerial photograph images. Black - and - white historical aerial photographs, which interpretation quality in many cases does not meet the criteria posed on photogrammetric developments, require an increase of their readability. The solution in this regard may be the process of coloring images. The authors of this article conducted studies aimed to determine to what extent the tested coloring algorithms enable an automatic detection of land cover elements on historical aerial photographs and provide color close to the natural. Used in the studies were archival black - and - white aerial photographs of the western part of Warsaw district made available by the Main Centre of Geodetic and Cartographic Documentation , the selection of which was associated with the presence in this area of various elements of land cover, such as water, forests, crops, exposed soils and also anthropogenic objects. In the analysis of different algorithms are included: format and size of the image, degree of automation of the process, degree of compliance of the result and processing time. The accuracy of the coloring process was different for each class of objects mapped on the photograph. The main limitation of the coloring process created shadows of anthropogenic objects

  20. Estimation of mean tree stand volume using high-resolution aerial RGB imagery and digital surface model, obtained from sUAV and Trestima mobile application

    Directory of Open Access Journals (Sweden)

    G. K. Rybakov

    2017-06-01

    Full Text Available This study considers a remote sensing technique for mean volume estimation based on a very high-resolution (VHR aerial RGB imagery obtained using a small-sized unmanned aerial vehicle (sUAV and a high-resolution photogrammetric digital surface model (DSM as well as an innovative technology for field measurements (Trestima. The study area covers approx. 220 ha of forestland in Finland. The work concerns the entire process from remote sensing and field data acquisition to statistical analysis and forest volume wall-to-wall mapping. The study showed that the VHR aerial imagery and the high-resolution DSM produced based on the application of the sUAV have good prospects for forest inventory. For the sUAV based estimation of forest variables such as Height, Basal Area and mean Volume, Root Mean Square Error constituted 6.6 %, 22.6 % and 26.7 %, respectively. Application of Trestima for estimation of the mean volume of the standing forest showed minor difference over the existing Forest Management Plan at all the selected forest compartments. Simultaneously, the results of the study confirmed that the technologies and the tools applied at this work could be a reliable and potentially cost-effective means of forest data acquisition with high potential of operational use.

  1. Kite aerial photography for low-cost, ultra-high spatial resolution multi-spectral mapping of intertidal landscapes.

    Directory of Open Access Journals (Sweden)

    Mitch Bryson

    Full Text Available Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae and animal (e.g. gastropods assemblages at multiple spatial and temporal scales.

  2. Kite aerial photography for low-cost, ultra-high spatial resolution multi-spectral mapping of intertidal landscapes.

    Science.gov (United States)

    Bryson, Mitch; Johnson-Roberson, Matthew; Murphy, Richard J; Bongiorno, Daniel

    2013-01-01

    Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales.

  3. A CNN-Based Method of Vehicle Detection from Aerial Images Using Hard Example Mining

    Directory of Open Access Journals (Sweden)

    Yohei Koga

    2018-01-01

    Full Text Available Recently, deep learning techniques have had a practical role in vehicle detection. While much effort has been spent on applying deep learning to vehicle detection, the effective use of training data has not been thoroughly studied, although it has great potential for improving training results, especially in cases where the training data are sparse. In this paper, we proposed using hard example mining (HEM in the training process of a convolutional neural network (CNN for vehicle detection in aerial images. We applied HEM to stochastic gradient descent (SGD to choose the most informative training data by calculating the loss values in each batch and employing the examples with the largest losses. We picked 100 out of both 500 and 1000 examples for training in one iteration, and we tested different ratios of positive to negative examples in the training data to evaluate how the balance of positive and negative examples would affect the performance. In any case, our method always outperformed the plain SGD. The experimental results for images from New York showed improved performance over a CNN trained in plain SGD where the F1 score of our method was 0.02 higher.

  4. Generating Impact Maps from Automatically Detected Bomb Craters in Aerial Wartime Images Using Marked Point Processes

    Science.gov (United States)

    Kruse, Christian; Rottensteiner, Franz; Hoberg, Thorsten; Ziems, Marcel; Rebke, Julia; Heipke, Christian

    2018-04-01

    The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.

  5. Aerial Photography and Imagery, Ortho-Corrected, Washington County, NC true color orthophotography - 1 foot resolution in the remainder of the county, Published in 2009, 1:4800 (1in=400ft) scale, Washington County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2009. Washington County, NC true color orthophotography - 1 foot resolution in the remainder of...

  6. Aerial Photography and Imagery, Ortho-Corrected, Washington County, NC true color orthophotography - 1/4 foot resolution over selected areas, Published in 2009, 1:1200 (1in=100ft) scale, Washington County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2009. Washington County, NC true color orthophotography - 1/4 foot resolution over selected...

  7. Aerial Photography and Imagery, Ortho-Corrected, Washington County, NC true color orhophotography - 1/2 foot resolution over selected areas, Published in 2009, 1:2400 (1in=200ft) scale, Washington County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2009. Washington County, NC true color orhophotography - 1/2 foot resolution over selected areas.

  8. High Resolution Aerial Photography of Puerto Rico and the U.S. Virgin Islands, 1965-1999

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Aerial photographs were acquired for the Puerto Rico and U.S. Virgin Islands Benthic Mapping Project in 1999 by NOAA Aircraft Operation Centers aircraft and National...

  9. Intra- and interspecific variation in tropical tree and liana phenology derived from Unmanned Aerial Vehicle images

    Science.gov (United States)

    Bohlman, S.; Park, J.; Muller-Landau, H. C.; Rifai, S. W.; Dandois, J. P.

    2017-12-01

    Phenology is a critical driver of ecosystem processes. There is strong evidence that phenology is shifting in temperate ecosystems in response to climate change, but tropical tree and liana phenology remains poorly quantified and understood. A key challenge is that tropical forests contain hundreds of plant species with a wide variety of phenological patterns. Satellite-based observations, an important source of phenology data in northern latitudes, are hindered by frequent cloud cover in the tropics. To quantify phenology over a large number of individuals and species, we collected bi-weekly images from unmanned aerial vehicles (UAVs) in the well-studied 50-ha forest inventory plot on Barro Colorado Island, Panama. Between October 2014 and December 2015 and again in May 2015, we collected a total of 35 sets of UAV images, each with continuous coverage of the 50-ha plot, where every tree ≥ 1 cm DBH is mapped. Spectral, texture, and image information was extracted from the UAV images for individual tree crowns, which was then used as inputs for a machine learning algorithm to predict percent leaf and branch cover. We obtained the species identities of 2000 crowns in the images via field mapping. The objectives of this study are to (1) determined if machine learning algorithms, applied to UAV images, can effectively quantify changes in leaf cover, which we term "deciduousness; (2) determine how liana cover effects deciduousness and (3) test how well UAV-derived deciduousness patterns match satellite-derived temporal patterns. Machine learning algorithms trained on a variety of image parameters could effectively determine leaf cover, despite variation in lighting and viewing angles. Crowns with higher liana cover have less overall deciduousness (tree + liana together) than crowns with lower liana cover. Individual crown deciduousness, summed over all crowns measured in the 50-ha plot, showed a similar seasonal pattern as MODIS EVI composited over 10 years. However

  10. Super-resolution thermographic imaging using blind structured illumination

    Science.gov (United States)

    Burgholzer, Peter; Berer, Thomas; Gruber, Jürgen; Mayr, Günther

    2017-07-01

    Using an infrared camera for thermographic imaging allows the contactless temperature measurement of many surface pixels simultaneously. From the measured surface data, the structure below the surface, embedded inside a sample or tissue, can be reconstructed and imaged, if heated by an excitation light pulse. The main drawback in active thermographic imaging is the degradation of the spatial resolution with the imaging depth, which results in blurred images for deeper lying structures. We circumvent this degradation by using blind structured illumination combined with a non-linear joint sparsity reconstruction algorithm. We demonstrate imaging of a line pattern and a star-shaped structure through a 3 mm thick steel sheet with a resolution four times better than the width of the thermal point-spread-function. The structured illumination is realized by parallel slits cut in an aluminum foil, where the excitation coming from a flashlight can penetrate. This realization of super-resolution thermographic imaging demonstrates that blind structured illumination allows thermographic imaging without high degradation of the spatial resolution for deeper lying structures. The groundbreaking concept of super-resolution can be transferred from optics to diffusive imaging by defining a thermal point-spread-function, which gives the principle resolution limit for a certain signal-to-noise ratio, similar to the Abbe limit for a certain optical wavelength. In future work, the unknown illumination pattern could be the speckle pattern generated by a short laser pulse inside a light scattering sample or tissue.

  11. Resolution limits for wave equation imaging

    KAUST Repository

    Huang, Yunsong; Schuster, Gerard T.

    2014-01-01

    migration (LSM), and full waveform inversion (FWI), and suggest a multiscale approach to iterative FWI based on multiscale physics. That is, at the early stages of the inversion, events that only generate low-wavenumber resolution should be emphasized

  12. Localization-based super-resolution imaging of cellular structures.

    Science.gov (United States)

    Kanchanawong, Pakorn; Waterman, Clare M

    2013-01-01

    Fluorescence microscopy allows direct visualization of fluorescently tagged proteins within cells. However, the spatial resolution of conventional fluorescence microscopes is limited by diffraction to ~250 nm, prompting the development of super-resolution microscopy which offers resolution approaching the scale of single proteins, i.e., ~20 nm. Here, we describe protocols for single molecule localization-based super-resolution imaging, using focal adhesion proteins as an example and employing either photoswitchable fluorophores or photoactivatable fluorescent proteins. These protocols should also be easily adaptable to imaging a broad array of macromolecular assemblies in cells whose components can be fluorescently tagged and assemble into high density structures.

  13. Fundamental limits to imaging resolution for focused ion beams

    International Nuclear Information System (INIS)

    Orloff, J.; Swanson, L.W.; Utlaut, M.

    1996-01-01

    This article investigates the limitations on the formation of focused ion beam images from secondary electrons. We use the notion of the information content of an image to account for the effects of resolution, contrast, and signal-to-noise ratio and show that there is a competition between the rate at which small features are sputtered away by the primary beam and the rate of collection of secondary electrons. We find that for small features, sputtering is the limit to imaging resolution, and that for extended small features (e.g., layered structures), rearrangement, redeposition, and differential sputtering rates may limit the resolution in some cases. copyright 1996 American Vacuum Society

  14. Super-resolution imaging applied to moving object tracking

    Science.gov (United States)

    Swalaganata, Galandaru; Ratna Sulistyaningrum, Dwi; Setiyono, Budi

    2017-10-01

    Moving object tracking in a video is a method used to detect and analyze changes that occur in an object that being observed. Visual quality and the precision of the tracked target are highly wished in modern tracking system. The fact that the tracked object does not always seem clear causes the tracking result less precise. The reasons are low quality video, system noise, small object, and other factors. In order to improve the precision of the tracked object especially for small object, we propose a two step solution that integrates a super-resolution technique into tracking approach. First step is super-resolution imaging applied into frame sequences. This step was done by cropping the frame in several frame or all of frame. Second step is tracking the result of super-resolution images. Super-resolution image is a technique to obtain high-resolution images from low-resolution images. In this research single frame super-resolution technique is proposed for tracking approach. Single frame super-resolution was a kind of super-resolution that it has the advantage of fast computation time. The method used for tracking is Camshift. The advantages of Camshift was simple calculation based on HSV color that use its histogram for some condition and color of the object varies. The computational complexity and large memory requirements required for the implementation of super-resolution and tracking were reduced and the precision of the tracked target was good. Experiment showed that integrate a super-resolution imaging into tracking technique can track the object precisely with various background, shape changes of the object, and in a good light conditions.

  15. Geodetic glacier mass balances at the push of a button: application of Structure from Motion technology on aerial images in mountain regions

    Science.gov (United States)

    Bolch, T.; Mölg, N.

    2017-12-01

    The application of Structure-from-Motion (SfM) to generate digital terrain models (DTMs) derived out of images from various kinds of sources has strongly increased in recent years. The major reason for this is its easy-to-use handling in comparison to conventional photogrammetry. In glaciology, DTMs are intensely used, among others, to calculate the geodetic mass balances. Few studies investigated the application of SfM to aerial images in mountainous terrain and results look promising. We tested this technique in a demanding environment in the Swiss Alps including very steep slopes, snow and ice covered terrain. SfM (using the commercial software packages of Agisoft Photoscan and Pix4DMapper) and conventional photogrammetry (ERDAS Photogrammetry) were applied on archival aerial images for nine dates between 1946 and 2005 the results were compared regarding bundle adjustment and final DTM quality. The overall precision of the DTMs could be defined with the use of a modern, high-quality reference DTM by Swisstopo. Results suggest a high performance of SfM to produce DTMs of similar quality as conventional photogrammetry. A ground resolution of high quality (little noise and artefacts) can be up to 50% higher, with 3-6 times less user effort. However, the controls on the commercial SfM software packages are limited in comparison to ERDAS Photogrammetry. SfM performs less reliably when few images with little overlap are processed. Overall, the uncertainty of DTMs from the different software are comparable and mostly within the uncertainty range of the reference DTM, making them highly valuable for glaciological purposes. Even though SfM facilitates the largely automated production of high quality DTMs, the user is not exempt from a thorough quality check, at best with reference data where available.

  16. REGISTRATION OF LASER SCANNING POINT CLOUDS AND AERIAL IMAGES USING EITHER ARTIFICIAL OR NATURAL TIE FEATURES

    Directory of Open Access Journals (Sweden)

    P. Rönnholm

    2012-07-01

    Full Text Available Integration of laser scanning data and photographs is an excellent combination regarding both redundancy and complementary. Applications of integration vary from sensor and data calibration to advanced classification and scene understanding. In this research, only airborne laser scanning and aerial images are considered. Currently, the initial registration is solved using direct orientation sensors GPS and inertial measurements. However, the accuracy is not usually sufficient for reliable integration of data sets, and thus the initial registration needs to be improved. A registration of data from different sources requires searching and measuring of accurate tie features. Usually, points, lines or planes are preferred as tie features. Therefore, the majority of resent methods rely highly on artificial objects, such as buildings, targets or road paintings. However, in many areas no such objects are available. For example in forestry areas, it would be advantageous to be able to improve registration between laser data and images without making additional ground measurements. Therefore, there is a need to solve registration using only natural features, such as vegetation and ground surfaces. Using vegetation as tie features is challenging, because the shape and even location of vegetation can change because of wind, for example. The aim of this article was to compare registration accuracies derived by using either artificial or natural tie features. The test area included urban objects as well as trees and other vegetation. In this area, two registrations were performed, firstly, using mainly built objects and, secondly, using only vegetation and ground surface. The registrations were solved applying the interactive orientation method. As a result, using artificial tie features leaded to a successful registration in all directions of the coordinate system axes. In the case of using natural tie features, however, the detection of correct heights was

  17. Image resolution influence on determination of resin injection rock mass

    Science.gov (United States)

    Wang, Weixing; Hakami, Eva

    2006-01-01

    In the context of nuclear waste repositories, an important approach to understanding brittle rock mass behavior to integrate new and powerful observational and numerical methods with multi-functional 3-D imaging and visualization techniques. Since 1994, Swedish Nuclear Fuel and Waste Management Company (SKB) have identified the need for a better understanding of radionuclide transport and retention processes in fractured rock. As a cooperation project between Sweden and China, we sampled a number of rock specimens for analyze rock fracture network by optical image technique. The samples are resin injected, in which way; opened fractures can be seen clearly by means of UV (Ultraviolet) light illumination. In the study period, we used different optical focuses to obtain the images from the same samples; we found that Image resolution influences on porosity determination of resin injected rock mass. This paper presents and discusses the six issues based on our research results: (1) Fracture porosity increases as camera focus distance decreases; (2) Porosity increases as illumination increases in resin injected fracture images; (3) To roughly estimate the porosity, the low resolution image can be used; (4) To collect more details of fracture information, the high resolution image is needed; (5) The resolution of image should be determined based on the aim of fracture analysis; (6) To acquire high resolution image, constructing a special illumination (standard) box maybe helpful to avoid light reflection and diffusion.

  18. Single image super-resolution based on convolutional neural networks

    Science.gov (United States)

    Zou, Lamei; Luo, Ming; Yang, Weidong; Li, Peng; Jin, Liujia

    2018-03-01

    We present a deep learning method for single image super-resolution (SISR). The proposed approach learns end-to-end mapping between low-resolution (LR) images and high-resolution (HR) images. The mapping is represented as a deep convolutional neural network which inputs the LR image and outputs the HR image. Our network uses 5 convolution layers, which kernels size include 5×5, 3×3 and 1×1. In our proposed network, we use residual-learning and combine different sizes of convolution kernels at the same layer. The experiment results show that our proposed method performs better than the existing methods in reconstructing quality index and human visual effects on benchmarked images.

  19. Application of Super-Resolution Image Reconstruction to Digital Holography

    Directory of Open Access Journals (Sweden)

    Zhang Shuqun

    2006-01-01

    Full Text Available We describe a new application of super-resolution image reconstruction to digital holography which is a technique for three-dimensional information recording and reconstruction. Digital holography has suffered from the low resolution of CCD sensors, which significantly limits the size of objects that can be recorded. The existing solution to this problem is to use optics to bandlimit the object to be recorded, which can cause the loss of details. Here super-resolution image reconstruction is proposed to be applied in enhancing the spatial resolution of digital holograms. By introducing a global camera translation before sampling, a high-resolution hologram can be reconstructed from a set of undersampled hologram images. This permits the recording of larger objects and reduces the distance between the object and the hologram. Practical results from real and simulated holograms are presented to demonstrate the feasibility of the proposed technique.

  20. Resolution enhancement of tri-stereo remote sensing images by super resolution methods

    Science.gov (United States)

    Tuna, Caglayan; Akoguz, Alper; Unal, Gozde; Sertel, Elif

    2016-10-01

    Super resolution (SR) refers to generation of a High Resolution (HR) image from a decimated, blurred, low-resolution (LR) image set, which can be either a single frame or multi-frame that contains a collection of several images acquired from slightly different views of the same observation area. In this study, we propose a novel application of tri-stereo Remote Sensing (RS) satellite images to the super resolution problem. Since the tri-stereo RS images of the same observation area are acquired from three different viewing angles along the flight path of the satellite, these RS images are properly suited to a SR application. We first estimate registration between the chosen reference LR image and other LR images to calculate the sub pixel shifts among the LR images. Then, the warping, blurring and down sampling matrix operators are created as sparse matrices to avoid high memory and computational requirements, which would otherwise make the RS-SR solution impractical. Finally, the overall system matrix, which is constructed based on the obtained operator matrices is used to obtain the estimate HR image in one step in each iteration of the SR algorithm. Both the Laplacian and total variation regularizers are incorporated separately into our algorithm and the results are presented to demonstrate an improved quantitative performance against the standard interpolation method as well as improved qualitative results due expert evaluations.

  1. High angular resolution diffusion imaging : processing & visualization

    NARCIS (Netherlands)

    Prckovska, V.

    2010-01-01

    Diffusion tensor imaging (DTI) is a recent magnetic resonance imaging (MRI) technique that can map the orientation architecture of neural tissues in a completely non-invasive way by measuring the directional specificity (anisotropy) of the local water diffusion. However, in areas of complex fiber

  2. THE USE OF MOBILE LASER SCANNING DATA AND UNMANNED AERIAL VEHICLE IMAGES FOR 3D MODEL RECONSTRUCTION

    Directory of Open Access Journals (Sweden)

    L. Zhu

    2013-08-01

    Full Text Available The increasing availability in multiple data sources acquired by different sensor platforms has provided the great advantages for desired result achievement. This paper proposes the use of both mobile laser scanning (MLS data and Unmanned Aerial Vehicle (UAV images for 3D model reconstruction. Due to no available exterior orientation parameters for UAV images, the first task is to georeference these images to 3D points. In order to fast and accurate acquire 3D points which are also easy to be found the corresponding locations on UAV images, automated pole extraction from MLS was developed. After georeferencing UAV images, building roofs are acquired from those images and building walls are extracted from MLS data. The roofs and the walls are combined to achieve the complete building models.

  3. Super-resolution for everybody: An image processing workflow to obtain high-resolution images with a standard confocal microscope.

    Science.gov (United States)

    Lam, France; Cladière, Damien; Guillaume, Cyndélia; Wassmann, Katja; Bolte, Susanne

    2017-02-15

    In the presented work we aimed at improving confocal imaging to obtain highest possible resolution in thick biological samples, such as the mouse oocyte. We therefore developed an image processing workflow that allows improving the lateral and axial resolution of a standard confocal microscope. Our workflow comprises refractive index matching, the optimization of microscope hardware parameters and image restoration by deconvolution. We compare two different deconvolution algorithms, evaluate the necessity of denoising and establish the optimal image restoration procedure. We validate our workflow by imaging sub resolution fluorescent beads and measuring the maximum lateral and axial resolution of the confocal system. Subsequently, we apply the parameters to the imaging and data restoration of fluorescently labelled meiotic spindles of mouse oocytes. We measure a resolution increase of approximately 2-fold in the lateral and 3-fold in the axial direction throughout a depth of 60μm. This demonstrates that with our optimized workflow we reach a resolution that is comparable to 3D-SIM-imaging, but with better depth penetration for confocal images of beads and the biological sample. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Satellite Images and Aerial Photographs of the Effects of Hurricanes Katrina and Rita on Coastal Louisiana

    Science.gov (United States)

    Barras, John A.

    2007-01-01

    -water datasets derived from the Landsat TM satellite imagery were combined with 2001 marsh vegetative communities (Chabreck and others, unpub. data, 2001) to identify land-water configurations by marsh community before and after the hurricanes. Links to the Landsat TM images and aerial photographs are given below (figs. 1-29). Comparison of land area before the storms to land area after the storms is made possible by the inclusion of Landsat TM images and aerial photographs taken in the years and months before the storms. The figures are arranged geographically from east to west to follow the chronology of the effects of the storms. For a more detailed analysis of the changes wrought by these storms, see 'Land Area Changes in Coastal Louisiana After Hurricanes Katrina and Rita' (Barras, in press).

  5. Resolution revival technique for subwavelength imaging

    DEFF Research Database (Denmark)

    Novitsky, Andrey; Repän, Taavi; Zhukovsky, Sergei

    2017-01-01

    The method to achieve a high resolution of subwavelength features (to improve the contrast function) for a dark-field hyperlens—hyperbolic metamaterial slab possessing metallic properties at the interface — is developed. The technique requires the introduction of the phase difference between the o...

  6. Medium resolution image fusion, does it enhance forest structure assessment

    CSIR Research Space (South Africa)

    Roberts, JW

    2008-07-01

    Full Text Available This research explored the potential benefits of fusing optical and Synthetic Aperture Radar (SAR) medium resolution satellite-borne sensor data for forest structural assessment. Image fusion was applied as a means of retaining disparate data...

  7. Influences of image resolution on herbaceous root morphological parameters

    Directory of Open Access Journals (Sweden)

    ZHANG Zeyou

    2014-06-01

    Full Text Available Root images of four herbaceous species (including Plantago virginica,Solidago canadensis,Conyza canadensis and Erigeron philadelphicus were obtained by using EPSON V7000 scanner with different resolutions.Root morphological parameters including root length,diameter,volume and area were determined by using a WinRhizo root analyzing software.The results show a distinct influence of image resolution on root morphological parameter.For different herbaceous species,the optimal resolutions of root images,which would produce an acceptable precision with relative short time,vary with different species.For example,a resolution of 200 dpi was recommended for the root images of Plantago virginica and S.Canadensis, while 400 dpi for Conyza canadensis and Erigeron philadelphicus.

  8. Sparsity-Based Super Resolution for SEM Images.

    Science.gov (United States)

    Tsiper, Shahar; Dicker, Or; Kaizerman, Idan; Zohar, Zeev; Segev, Mordechai; Eldar, Yonina C

    2017-09-13

    The scanning electron microscope (SEM) is an electron microscope that produces an image of a sample by scanning it with a focused beam of electrons. The electrons interact with the atoms in the sample, which emit secondary electrons that contain information about the surface topography and composition. The sample is scanned by the electron beam point by point, until an image of the surface is formed. Since its invention in 1942, the capabilities of SEMs have become paramount in the discovery and understanding of the nanometer world, and today it is extensively used for both research and in industry. In principle, SEMs can achieve resolution better than one nanometer. However, for many applications, working at subnanometer resolution implies an exceedingly large number of scanning points. For exactly this reason, the SEM diagnostics of microelectronic chips is performed either at high resolution (HR) over a small area or at low resolution (LR) while capturing a larger portion of the chip. Here, we employ sparse coding and dictionary learning to algorithmically enhance low-resolution SEM images of microelectronic chips-up to the level of the HR images acquired by slow SEM scans, while considerably reducing the noise. Our methodology consists of two steps: an offline stage of learning a joint dictionary from a sequence of LR and HR images of the same region in the chip, followed by a fast-online super-resolution step where the resolution of a new LR image is enhanced. We provide several examples with typical chips used in the microelectronics industry, as well as a statistical study on arbitrary images with characteristic structural features. Conceptually, our method works well when the images have similar characteristics, as microelectronics chips do. This work demonstrates that employing sparsity concepts can greatly improve the performance of SEM, thereby considerably increasing the scanning throughput without compromising on analysis quality and resolution.

  9. Image processor for high resolution video

    International Nuclear Information System (INIS)

    Pessoa, P.P.; Assis, J.T.; Cardoso, S.B.; Lopes, R.T.

    1989-01-01

    In this paper, we discuss an image presentation and processing system developed in Turbo Pascal 5.0 Language. Our system allows the visualization and processing of images in 16 different colors, taken at a time from a set of 64 possible ones. Digital filters of the mean, mediam Laplacian, gradient and histograms equalization type have been implemented, so as to allow a better image quality. Possible applications of our system are also discussed e.g., satellites, computerized tomography, medicine, microscopes. (author) [pt

  10. High resolution imaging of boron carbide microstructures

    International Nuclear Information System (INIS)

    MacKinnon, I.D.R.; Aselage, T.; Van Deusen, S.B.

    1986-01-01

    Two samples of boron carbide have been examined using high resolution transmission electron microscopy (HRTEM). A hot-pressed B 13 C 2 sample shows a high density of variable width twins normal to (10*1). Subtle shifts or offsets of lattice fringes along the twin plane and normal to approx.(10*5) were also observed. A B 4 C powder showed little evidence of stacking disorder in crystalline regions

  11. Quantifying and containing the curse of high resolution coronal imaging

    Directory of Open Access Journals (Sweden)

    V. Delouille

    2008-10-01

    Full Text Available Future missions such as Solar Orbiter (SO, InterHelioprobe, or Solar Probe aim at approaching the Sun closer than ever before, with on board some high resolution imagers (HRI having a subsecond cadence and a pixel area of about (80 km2 at the Sun during perihelion. In order to guarantee their scientific success, it is necessary to evaluate if the photon counts available at these resolution and cadence will provide a sufficient signal-to-noise ratio (SNR. For example, if the inhomogeneities in the Quiet Sun emission prevail at higher resolution, one may hope to locally have more photon counts than in the case of a uniform source. It is relevant to quantify how inhomogeneous the quiet corona will be for a pixel pitch that is about 20 times smaller than in the case of SoHO/EIT, and 5 times smaller than TRACE. We perform a first step in this direction by analyzing and characterizing the spatial intermittency of Quiet Sun images thanks to a multifractal analysis. We identify the parameters that specify the scale-invariance behavior. This identification allows next to select a family of multifractal processes, namely the Compound Poisson Cascades, that can synthesize artificial images having some of the scale-invariance properties observed on the recorded images. The prevalence of self-similarity in Quiet Sun coronal images makes it relevant to study the ratio between the SNR present at SoHO/EIT images and in coarsened images. SoHO/EIT images thus play the role of "high resolution" images, whereas the "low-resolution" coarsened images are rebinned so as to simulate a smaller angular resolution and/or a larger distance to the Sun. For a fixed difference in angular resolution and in Spacecraft-Sun distance, we determine the proportion of pixels having a SNR preserved at high resolution given a particular increase in effective area. If scale-invariance continues to prevail at smaller scales, the conclusion reached with SoHO/EIT images can be transposed

  12. High resolution multiplexed functional imaging in live embryos (Conference Presentation)

    Science.gov (United States)

    Xu, Dongli; Zhou, Weibin; Peng, Leilei

    2017-02-01

    Fourier multiplexed fluorescence lifetime imaging (FmFLIM) scanning laser optical tomography (FmFLIM-SLOT) combines FmFLIM and Scanning laser optical tomography (SLOT) to perform multiplexed 3D FLIM imaging of live embryos. The system had demonstrate multiplexed functional imaging of zebrafish embryos genetically express Foster Resonant Energy Transfer (FRET) sensors. However, previous system has a 20 micron resolution because the focused Gaussian beam diverges quickly from the focused plane, makes it difficult to achieve high resolution imaging over a long projection depth. Here, we present a high-resolution FmFLIM-SLOT system with achromatic Bessel beam, which achieves 3 micron resolution in 3D deep tissue imaging. In Bessel-FmFLIM-SLOT, multiple laser excitation lines are firstly intensity modulated by a Michelson interferometer with a spinning polygon mirror optical delay line, which enables Fourier multiplexed multi-channel lifetime measurements. Then, a spatial light modulator and a prism are used to transform the modulated Gaussian laser beam to an achromatic Bessel beam. The achromatic Bessel beam scans across the whole specimen with equal angular intervals as sample rotated. After tomography reconstruction and the frequency domain lifetime analysis method, both the 3D intensity and lifetime image of multiple excitation-emission can be obtained. Using Bessel-FmFLIM-SLOT system, we performed cellular-resolution FLIM tomography imaging of live zebrafish embryo. Genetically expressed FRET sensors in these embryo will allow non-invasive observation of multiple biochemical processes in vivo.

  13. SINGLE FRAME SUPER RESOLUTION OF NONCOOPERATIVE IRIS IMAGES

    Directory of Open Access Journals (Sweden)

    Anand Deshpande

    2016-11-01

    Full Text Available Image super-resolution, a process to enhance image resolution, has important applications in biometrics, satellite imaging, high definition television, medical imaging, etc. The long range captured iris identification systems often suffer from low resolution and meager focus of the captured iris images. These degrade the iris recognition performance. This paper proposes enhanced iterated back projection (EIBP method to super resolute the long range captured iris polar images. The performance of proposed method is tested and analyzed on CASIA long range iris database by comparing peak signal to noise ratio (PSNR and structural similarity index (SSIM with state-of-the-art super resolution (SR algorithms. It is further analyzed by increasing the up-sampling factor. Performance analysis shows that the proposed method is superior to state-of-the-art algorithms, the peak signal-to-noise ratio improved about 0.1-1.5 dB. The results demonstrate that the proposed method is well suited to super resolve the iris polar images captured at a long distance

  14. Automated hotspot analysis with aerial image CD metrology for advanced logic devices

    Science.gov (United States)

    Buttgereit, Ute; Trautzsch, Thomas; Kim, Min-ho; Seo, Jung-Uk; Yoon, Young-Keun; Han, Hak-Seung; Chung, Dong Hoon; Jeon, Chan-Uk; Meyers, Gary

    2014-09-01

    Continuously shrinking designs by further extension of 193nm technology lead to a much higher probability of hotspots especially for the manufacturing of advanced logic devices. The CD of these potential hotspots needs to be precisely controlled and measured on the mask. On top of that, the feature complexity increases due to high OPC load in the logic mask design which is an additional challenge for CD metrology. Therefore the hotspot measurements have been performed on WLCD from ZEISS, which provides the benefit of reduced complexity by measuring the CD in the aerial image and qualifying the printing relevant CD. This is especially of advantage for complex 2D feature measurements. Additionally, the data preparation for CD measurement becomes more critical due to the larger amount of CD measurements and the increasing feature diversity. For the data preparation this means to identify these hotspots and mark them automatically with the correct marker required to make the feature specific CD measurement successful. Currently available methods can address generic pattern but cannot deal with the pattern diversity of the hotspots. The paper will explore a method how to overcome those limitations and to enhance the time-to-result in the marking process dramatically. For the marking process the Synopsys WLCD Output Module was utilized, which is an interface between the CATS mask data prep software and the WLCD metrology tool. It translates the CATS marking directly into an executable WLCD measurement job including CD analysis. The paper will describe the utilized method and flow for the hotspot measurement. Additionally, the achieved results on hotspot measurements utilizing this method will be presented.

  15. A method for generating high resolution satellite image time series

    Science.gov (United States)

    Guo, Tao

    2014-10-01

    There is an increasing demand for satellite remote sensing data with both high spatial and temporal resolution in many applications. But it still is a challenge to simultaneously improve spatial resolution and temporal frequency due to the technical limits of current satellite observation systems. To this end, much R&D efforts have been ongoing for years and lead to some successes roughly in two aspects, one includes super resolution, pan-sharpen etc. methods which can effectively enhance the spatial resolution and generate good visual effects, but hardly preserve spectral signatures and result in inadequate analytical value, on the other hand, time interpolation is a straight forward method to increase temporal frequency, however it increase little informative contents in fact. In this paper we presented a novel method to simulate high resolution time series data by combing low resolution time series data and a very small number of high resolution data only. Our method starts with a pair of high and low resolution data set, and then a spatial registration is done by introducing LDA model to map high and low resolution pixels correspondingly. Afterwards, temporal change information is captured through a comparison of low resolution time series data, and then projected onto the high resolution data plane and assigned to each high resolution pixel according to the predefined temporal change patterns of each type of ground objects. Finally the simulated high resolution data is generated. A preliminary experiment shows that our method can simulate a high resolution data with a reasonable accuracy. The contribution of our method is to enable timely monitoring of temporal changes through analysis of time sequence of low resolution images only, and usage of costly high resolution data can be reduces as much as possible, and it presents a highly effective way to build up an economically operational monitoring solution for agriculture, forest, land use investigation

  16. HIGH RESOLUTION AIRBORNE LASER SCANNING AND HYPERSPECTRAL IMAGING WITH A SMALL UAV PLATFORM

    Directory of Open Access Journals (Sweden)

    M. Gallay

    2016-06-01

    Full Text Available The capabilities of unmanned airborne systems (UAS have become diverse with the recent development of lightweight remote sensing instruments. In this paper, we demonstrate our custom integration of the state-of-the-art technologies within an unmanned aerial platform capable of high-resolution and high-accuracy laser scanning, hyperspectral imaging, and photographic imaging. The technological solution comprises the latest development of a completely autonomous, unmanned helicopter by Aeroscout, the Scout B1-100 UAV helicopter. The helicopter is powered by a gasoline two-stroke engine and it allows for integrating 18 kg of a customized payload unit. The whole system is modular providing flexibility of payload options, which comprises the main advantage of the UAS. The UAS integrates two kinds of payloads which can be altered. Both payloads integrate a GPS/IMU with a dual GPS antenna configuration provided by OXTS for accurate navigation and position measurements during the data acquisition. The first payload comprises a VUX-1 laser scanner by RIEGL and a Sony A6000 E-Mount photo camera. The second payload for hyperspectral scanning integrates a push-broom imager AISA KESTREL 10 by SPECIM. The UAS was designed for research of various aspects of landscape dynamics (landslides, erosion, flooding, or phenology in high spectral and spatial resolution.

  17. HRTEM imaging of atoms at sub-Angstroem resolution

    International Nuclear Information System (INIS)

    O'Keefe, Michael A.; Allard, Lawrence F.; Blom, Douglas A.

    2005-01-01

    John Cowley and his group at Arizona State University pioneered the use of transmission electron microscopy for high-resolution imaging. Images were achieved three decades ago showing the crystal unit cell content at better than 4 A resolution. This achievement enabled researchers to pinpoint the positions of heavy atom columns within the unit cell. Lighter atoms appear as resolution is improved to sub-Angstroem levels. Currently, advanced microscopes can image the columns of the light atoms (carbon, oxygen, nitrogen) that are present in many complex structures, and even the lithium atoms present in some battery materials. Sub-Angstroem imaging, initially achieved by focal-series reconstruction of the specimen exit surface wave, will become commonplace for next-generation electron microscopes with C s -corrected lenses and monochromated electron beams. Resolution can be quantified in terms of peak separation and inter-peak minimum, but the limits imposed on the attainable resolution by the properties of the microscope specimen need to be considered. At extreme resolution the 'size' of atoms can mean that they will not be resolved even when spaced farther apart than the resolution of the microscope. (author)

  18. HRTEM Imaging of Atoms at Sub-Angstrom Resolution

    Energy Technology Data Exchange (ETDEWEB)

    O' Keefe, Michael A.; Allard, Lawrence F.; Blom, Douglas A.

    2005-04-06

    John Cowley and his group at Arizona State University pioneered the use of transmission electron microscopy (TEM) for high-resolution imaging. Images were achieved three decades ago showing the crystal unit cell content at better than 4 Angstrom resolution. This achievement enabled researchers to pinpoint the positions of heavy atom columns within the unit cell. Lighter atoms appear as resolution is improved to sub-Angstrom levels. Currently, advanced microscopes can image the columns of the light atoms (carbon, oxygen, nitrogen) that are present in many complex structures, and even the lithium atoms present in some battery materials. Sub-Angstrom imaging, initially achieved by focal-series reconstruction of the specimen exit surface wave, will become common place for next-generation electron microscopes with CS-corrected lenses and monochromated electron beams. Resolution can be quantified in terms of peak separation and inter-peak minimum, but the limits imposed on the attainable resolution by the properties of the micro-scope specimen need to be considered. At extreme resolution the ''size'' of atoms can mean that they will not be resolved even when spaced farther apart than the resolution of the microscope.

  19. Multitemporal field-based plant height estimation using 3D point clouds generated from small unmanned aerial systems high-resolution imagery

    Science.gov (United States)

    Malambo, L.; Popescu, S. C.; Murray, S. C.; Putman, E.; Pugh, N. A.; Horne, D. W.; Richardson, G.; Sheridan, R.; Rooney, W. L.; Avant, R.; Vidrine, M.; McCutchen, B.; Baltensperger, D.; Bishop, M.

    2018-02-01

    Plant breeders and agronomists are increasingly interested in repeated plant height measurements over large experimental fields to study critical aspects of plant physiology, genetics and environmental conditions during plant growth. However, collecting such measurements using commonly used manual field measurements is inefficient. 3D point clouds generated from unmanned aerial systems (UAS) images using Structure from Motion (SfM) techniques offer a new option for efficiently deriving in-field crop height data. This study evaluated UAS/SfM for multitemporal 3D crop modelling and developed and assessed a methodology for estimating plant height data from point clouds generated using SfM. High-resolution images in visible spectrum were collected weekly across 12 dates from April (planting) to July (harvest) 2016 over 288 maize (Zea mays L.) and 460 sorghum (Sorghum bicolor L.) plots using a DJI Phantom 3 Professional UAS. The study compared SfM point clouds with terrestrial lidar (TLS) at two dates to evaluate the ability of SfM point clouds to accurately capture ground surfaces and crop canopies, both of which are critical for plant height estimation. Extended plant height comparisons were carried out between SfM plant height (the 90th, 95th, 99th percentiles and maximum height) per plot and field plant height measurements at six dates throughout the growing season to test the repeatability and consistency of SfM estimates. High correlations were observed between SfM and TLS data (R2 = 0.88-0.97, RMSE = 0.01-0.02 m and R2 = 0.60-0.77 RMSE = 0.12-0.16 m for the ground surface and canopy comparison, respectively). Extended height comparisons also showed strong correlations (R2 = 0.42-0.91, RMSE = 0.11-0.19 m for maize and R2 = 0.61-0.85, RMSE = 0.12-0.24 m for sorghum). In general, the 90th, 95th and 99th percentile height metrics had higher correlations to field measurements than the maximum metric though differences among them were not statistically significant. The

  20. Optimal image resolution for digital storage of radiotherapy-planning images

    International Nuclear Information System (INIS)

    Baba, Yuji; Furusawa, Mitsuhiro; Murakami, Ryuji; Baba, Takashi; Yokoyama, Toshimi; Nishimura, Ryuichi; Takahashi, Mutsumasa

    1998-01-01

    Purpose: To evaluate the quality of digitized radiation-planning images at different resolution and to determine the optimal resolution for digital storage. Methods and Materials: Twenty-five planning films were scanned and digitized using a film scanner at a resolution of 72 dots per inch (dpi) with 8-bit depth. The resolution of scanned images was reduced to 48, 36, 24, and 18 dpi using computer software. Image qualities of these five images (72, 48, 36, 24, and 18 dpi) were evaluated and given scores (4 = excellent; 3 = good; 2 = fair; and 1 = poor) by three radiation oncologists. An image data compression algorithm by the Joint Photographic Experts Group (JPEG) (not reversible and some information will be lost) was also evaluated. Results: The scores of digitized images with 72, 48, 36, 24, and 17 dpi resolution were 3.8 ± 0.3, 3.5 ± 0.3, 3.3 ± 0.5, 2.7 ± 0.5, and 1.6 ± 0.3, respectively. The quality of 36-dpi images were definitely worse compared to 72-dpi images, but were good enough as planning films. Digitized planning images with 72- and 36-dpi resolution requires about 800 and 200 KBytes, respectively. The JPEG compression algorithm produces little degradation in 36-dpi images at compression ratios of 5:1. Conclusion: The quality of digitized images with 36-dpi resolution was good enough as radiation-planning images and required 200 KBytes/image

  1. Towards sub-{Angstrom} resolution through incoherent imaging

    Energy Technology Data Exchange (ETDEWEB)

    Pennycook, S.J.; Chisholm, M.F. [Oak Ridge National Lab., TN (United States); Nellist, P.D. [Cavendish Lab., Cambridge, (United Kingdom)

    1997-04-01

    As first pointed out by Lord Rayleigh a century ago, incoherent imaging offers a substantial resolution enhancement compared to coherent imaging, together with freedom from phase contrast interference effects and contrast oscillations. In the STEM configuration, with a high angle annular detector to provide the transverse incoherence, the image also shows strong Z-contrast, sufficient in the case of a 300 kV STEM to image single Pt and Rh atoms on a {gamma}-alumina support. The annular detector provides complementarity to a bright field detector of the same size. For weakly scattering specimens, it shows greater contrast than the incoherent bright field image, and also facilitates EELS analysis at atomic resolution, using the Z-contrast image to locate the probe with sub-{angstrom} precision. The inner radius of the annular detector can be chosen to reduce the transverse coherence length to well below the spacings needed to resolve the object, a significant advantage compared to light microscopy.

  2. High-resolution axial MR imaging of tibial stress injuries

    Directory of Open Access Journals (Sweden)

    Mammoto Takeo

    2012-05-01

    Full Text Available Abstract Purpose To evaluate the relative involvement of tibial stress injuries using high-resolution axial MR imaging and the correlation with MR and radiographic images. Methods A total of 33 patients with exercise-induced tibial pain were evaluated. All patients underwent radiograph and high-resolution axial MR imaging. Radiographs were taken at initial presentation and 4 weeks later. High-resolution MR axial images were obtained using a microscopy surface coil with 60 × 60 mm field of view on a 1.5T MR unit. All images were evaluated for abnormal signals of the periosteum, cortex and bone marrow. Results Nineteen patients showed no periosteal reaction at initial and follow-up radiographs. MR imaging showed abnormal signals in the periosteal tissue and partially abnormal signals in the bone marrow. In 7 patients, periosteal reaction was not seen at initial radiograph, but was detected at follow-up radiograph. MR imaging showed abnormal signals in the periosteal tissue and entire bone marrow. Abnormal signals in the cortex were found in 6 patients. The remaining 7 showed periosteal reactions at initial radiograph. MR imaging showed abnormal signals in the periosteal tissue in 6 patients. Abnormal signals were seen in the partial and entire bone marrow in 4 and 3 patients, respectively. Conclusions Bone marrow abnormalities in high-resolution axial MR imaging were related to periosteal reactions at follow-up radiograph. Bone marrow abnormalities might predict later periosteal reactions, suggesting shin splints or stress fractures. High-resolution axial MR imaging is useful in early discrimination of tibial stress injuries.

  3. High-resolution axial MR imaging of tibial stress injuries

    Science.gov (United States)

    2012-01-01

    Purpose To evaluate the relative involvement of tibial stress injuries using high-resolution axial MR imaging and the correlation with MR and radiographic images. Methods A total of 33 patients with exercise-induced tibial pain were evaluated. All patients underwent radiograph and high-resolution axial MR imaging. Radiographs were taken at initial presentation and 4 weeks later. High-resolution MR axial images were obtained using a microscopy surface coil with 60 × 60 mm field of view on a 1.5T MR unit. All images were evaluated for abnormal signals of the periosteum, cortex and bone marrow. Results Nineteen patients showed no periosteal reaction at initial and follow-up radiographs. MR imaging showed abnormal signals in the periosteal tissue and partially abnormal signals in the bone marrow. In 7 patients, periosteal reaction was not seen at initial radiograph, but was detected at follow-up radiograph. MR imaging showed abnormal signals in the periosteal tissue and entire bone marrow. Abnormal signals in the cortex were found in 6 patients. The remaining 7 showed periosteal reactions at initial radiograph. MR imaging showed abnormal signals in the periosteal tissue in 6 patients. Abnormal signals were seen in the partial and entire bone marrow in 4 and 3 patients, respectively. Conclusions Bone marrow abnormalities in high-resolution axial MR imaging were related to periosteal reactions at follow-up radiograph. Bone marrow abnormalities might predict later periosteal reactions, suggesting shin splints or stress fractures. High-resolution axial MR imaging is useful in early discrimination of tibial stress injuries. PMID:22574840

  4. Super-resolution of facial images in forensics scenarios

    DEFF Research Database (Denmark)

    Satiro, Joao; Nasrollahi, Kamal; Correia, Paulo

    2015-01-01

    -resolution (SR) algorithms might be used. But, the problem with these algorithms is that they mostly require motion estimation between LR and low-quality images which is not always practical. To deal with this, we first simply interpolate the LR input images and then perform motion estimation. The estimated...... motion parameters are then used in a non-local mean-based SR algorithm to produce a higher quality image. This image is further fused with the interpolated version of the reference image via an alpha-blending approach. The experimental results on benchmark datasets and locally collected videos from...

  5. High Resolution Imaging of the Sun with CORONAS-1

    Science.gov (United States)

    Karovska, Margarita

    1998-01-01

    We applied several image restoration and enhancement techniques, to CORONAS-I images. We carried out the characterization of the Point Spread Function (PSF) using the unique capability of the Blind Iterative Deconvolution (BID) technique, which recovers the real PSF at a given location and time of observation, when limited a priori information is available on its characteristics. We also applied image enhancement technique to extract the small scale structure imbeded in bright large scale structures on the disk and on the limb. The results demonstrate the capability of the image post-processing to substantially increase the yield from the space observations by improving the resolution and reducing noise in the images.

  6. Registration of Aerial Image with Airborne LiDAR Data Based on Plücker Line

    Directory of Open Access Journals (Sweden)

    SHENG Qinghong

    2015-07-01

    Full Text Available Registration of aerial image with airborne LiDAR data is a key to feature extraction. A registration model based on Plücker line is proposed. The relative position and attitude relationship between the conjugate lines in LiDAR and image is determined based on Plücker linear equation, which describes line transformation in space, then coplanarity condition equation is established. Finally, coordinate transformation between image point and corresponding LiDAR point is achieved by the spiral movement of Plücker lines in the image. The registration model of Plücker linear coplanarity condition equation is simple, and jointly describes the rotation and translation to avoid coupling error between them, so the accuracy is approved. This research provides technical support for high-quality earth spatial information acquisition.

  7. Imaging Lithium Atoms at Sub-Angstrom Resolution

    Energy Technology Data Exchange (ETDEWEB)

    O' Keefe, Michael A.; Shao-Horn, Yang

    2005-01-03

    John Cowley and his group at ASU were pioneers in the use of transmission electron microscopy (TEM) for high-resolution imaging. Three decades ago they achieved images showing the crystal unit cell content at better than 4A resolution. Over the years, this achievement has inspired improvements in resolution that have enabled researchers to pinpoint the positions of heavy atom columns within the cell. More recently, this ability has been extended to light atoms as resolution has improved. Sub-Angstrom resolution has enabled researchers to image the columns of light atoms (carbon, oxygen and nitrogen) that are present in many complex structures. By using sub-Angstrom focal-series reconstruction of the specimen exit surface wave to image columns of cobalt, oxygen, and lithium atoms in a transition metal oxide structure commonly used as positive electrodes in lithium rechargeable batteries, we show that the range of detectable light atoms extends to lithium. HRTEM at sub-Angstrom resolution will provide the essential role of experimental verification for the emergent nanotech revolution. Our results foreshadow those to be expected from next-generation TEMs with CS-corrected lenses and monochromated electron beams.

  8. Super-resolution for asymmetric resolution of FIB-SEM 3D imaging using AI with deep learning.

    Science.gov (United States)

    Hagita, Katsumi; Higuchi, Takeshi; Jinnai, Hiroshi

    2018-04-12

    Scanning electron microscopy equipped with a focused ion beam (FIB-SEM) is a promising three-dimensional (3D) imaging technique for nano- and meso-scale morphologies. In FIB-SEM, the specimen surface is stripped by an ion beam and imaged by an SEM installed orthogonally to the FIB. The lateral resolution is governed by the SEM, while the depth resolution, i.e., the FIB milling direction, is determined by the thickness of the stripped thin layer. In most cases, the lateral resolution is superior to the depth resolution; hence, asymmetric resolution is generated in the 3D image. Here, we propose a new approach based on an image-processing or deep-learning-based method for super-resolution of 3D images with such asymmetric resolution, so as to restore the depth resolution to achieve symmetric resolution. The deep-learning-based method learns from high-resolution sub-images obtained via SEM and recovers low-resolution sub-images parallel to the FIB milling direction. The 3D morphologies of polymeric nano-composites are used as test images, which are subjected to the deep-learning-based method as well as conventional methods. We find that the former yields superior restoration, particularly as the asymmetric resolution is increased. Our super-resolution approach for images having asymmetric resolution enables observation time reduction.

  9. Effect of exposure time and image resolution on fractal dimension

    International Nuclear Information System (INIS)

    An, Byung Mo; Heo, Min Suk; Lee, Seung Pyo; Lee, Sam Sun; Choi, Soon Chul; Park, Tae Won; Kim, Jong Dae

    2002-01-01

    To evaluate the effect of exposure time and image resolution on fractal dimension calculations for determining the optimal range of these two variances. Thirty-one radiographs of the mandibular angle area of sixteen human dry mandibles were taken at different exposure times (0.01, 0.08, 0.16, 0.25, 0.40, 0.64, and 0.80 s). Each radiograph was digitized at 1200 dpi, 8 bit, 256 gray level using a film scanner. We selected an Region of Interest (ROI) that corresponded to the same region as in each radiograph, but the resolution of ROI was degraded to 1000, 800, 600, 500, 400, 300, 200, and 100 dpi. The fractal dimension was calculated by using the tile-counting method for each image, and the calculated values were then compared statistically. As the exposure time and the image resolution increased, the mean value of the fractal dimension decreased, except the case where exposure time was set at 0.01 seconds (alpha = 0.05). The exposure time and image resolution affected the fractal dimension by interaction (p<0.001). When the exposure time was set to either 0.64 seconds or 0.80 seconds, the resulting fractal dimensions were lower, irrespective of image resolution, than at shorter exposure times (alpha = 0.05). The optimal range for exposure time and resolution was determined to be 0.08-0.40 seconds and from 400-1000 dpi, respectively. Adequate exposure time and image resolution is essential for acquiring the fractal dimension using tile-counting method for evaluation of the mandible.

  10. High Resolution Astrophysical Observations Using Speckle Imaging

    Science.gov (United States)

    1986-04-11

    reserved. Printed in U.S A . A NEW OPTICAL SOURCE ASSOCIATED WITH T TAURI P. NISENSON, R. V. STACHNIK, M. KAROVSKA , AND R. NOYES Harvard-Smithsonian Center...NISENSON, STACHNIK, KAROVSKA . AND NoYEs (see page L18) APPENDIX F ON THE a ORIONIS TRIPLE SYSTEM M. Karovska , P. Nisenson, R. Noyes Harvard-Smithsonian...3.5 and 4.0 at a wavelengtRh of 530 nm. In Addition, Karovska (1984) inferred the possible existence of a second companion from an image recon

  11. Optimization of super-resolution processing using incomplete image sets in PET imaging.

    Science.gov (United States)

    Chang, Guoping; Pan, Tinsu; Clark, John W; Mawlawi, Osama R

    2008-12-01

    Super-resolution (SR) techniques are used in PET imaging to generate a high-resolution image by combining multiple low-resolution images that have been acquired from different points of view (POVs). The number of low-resolution images used defines the processing time and memory storage necessary to generate the SR image. In this paper, the authors propose two optimized SR implementations (ISR-1 and ISR-2) that require only a subset of the low-resolution images (two sides and diagonal of the image matrix, respectively), thereby reducing the overall processing time and memory storage. In an N x N matrix of low-resolution images, ISR-1 would be generated using images from the two sides of the N x N matrix, while ISR-2 would be generated from images across the diagonal of the image matrix. The objective of this paper is to investigate whether the two proposed SR methods can achieve similar performance in contrast and signal-to-noise ratio (SNR) as the SR image generated from a complete set of low-resolution images (CSR) using simulation and experimental studies. A simulation, a point source, and a NEMA/IEC phantom study were conducted for this investigation. In each study, 4 (2 x 2) or 16 (4 x 4) low-resolution images were reconstructed from the same acquired data set while shifting the reconstruction grid to generate images from different POVs. SR processing was then applied in each study to combine all as well as two different subsets of the low-resolution images to generate the CSR, ISR-1, and ISR-2 images, respectively. For reference purpose, a native reconstruction (NR) image using the same matrix size as the three SR images was also generated. The resultant images (CSR, ISR-1, ISR-2, and NR) were then analyzed using visual inspection, line profiles, SNR plots, and background noise spectra. The simulation study showed that the contrast and the SNR difference between the two ISR images and the CSR image were on average 0.4% and 0.3%, respectively. Line profiles of

  12. High spectral resolution image of Barnacle Bill

    Science.gov (United States)

    1997-01-01

    The rover Sojourner's first target for measurement by the Alpha-Proton-Xray Spectrometer (APXS) was the rock named Barnacle Bill, located close to the ramp down which the rover made its egress from the lander. The full spectral capability of the Imager for Mars Pathfinder (IMP), consisting of 13 wavelength filters, was used to characterize the rock's surface. The measured area is relatively dark, and is shown in blue. Nearby on the rock surface, soil material is trapped in pits (shown in red).Mars Pathfinder is the second in NASA's Discovery program of low-cost spacecraft with highly focused science goals. The Jet Propulsion Laboratory, Pasadena, CA, developed and manages the Mars Pathfinder mission for NASA's Office of Space Science, Washington, D.C. The Imager for Mars Pathfinder (IMP) was developed by the University of Arizona Lunar and Planetary Laboratory under contract to JPL. Peter Smith is the Principal Investigator. JPL is an operating division of the California Institute of Technology (Caltech).

  13. 1024 matrix image reconstruction: usefulness in high resolution chest CT

    International Nuclear Information System (INIS)

    Jeong, Sun Young; Chung, Myung Jin; Chong, Se Min; Sung, Yon Mi; Lee, Kyung Soo

    2006-01-01

    We tried to evaluate whether high resolution chest CT with a 1,024 matrix has a significant advantage in image quality compared to a 512 matrix. Each set of 512 and 1024 matrix high resolution chest CT scans with both 0.625 mm and 1.25 mm slice thickness were obtained from 26 patients. Seventy locations that contained twenty-four low density lesions without sharp boundary such as emphysema, and forty-six sharp linear densities such as linear fibrosis were selected; these were randomly displayed on a five mega pixel LCD monitor. All the images were masked for information concerning the matrix size and slice thickness. Two chest radiologists scored the image quality of each ar rowed lesion as follows: (1) undistinguishable, (2) poorly distinguishable, (3) fairly distinguishable, (4) well visible and (5) excellently visible. The scores were compared from the aspects of matrix size, slice thickness and the different observers by using ANOVA tests. The average and standard deviation of image quality were 3.09 (± .92) for the 0.625 mm x 512 matrix, 3.16 (± .84) for the 0.625 mm x 1024 matrix, 2.49 (± 1.02) for the 1.25 mm x 512 matrix, and 2.35 (± 1.02) for the 1.25 mm x 1024 matrix, respectively. The image quality on both matrices of the high resolution chest CT scans with a 0.625 mm slice thickness was significantly better than that on the 1.25 mm slice thickness (ρ < 0.001). However, the image quality on the 1024 matrix high resolution chest CT scans was not significantly different from that on the 512 matrix high resolution chest CT scans (ρ = 0.678). The interobserver variation between the two observers was not significant (ρ = 0.691). We think that 1024 matrix image reconstruction for high resolution chest CT may not be clinical useful

  14. A subspace approach to high-resolution spectroscopic imaging.

    Science.gov (United States)

    Lam, Fan; Liang, Zhi-Pei

    2014-04-01

    To accelerate spectroscopic imaging using sparse sampling of (k,t)-space and subspace (or low-rank) modeling to enable high-resolution metabolic imaging with good signal-to-noise ratio. The proposed method, called SPectroscopic Imaging by exploiting spatiospectral CorrElation, exploits a unique property known as partial separability of spectroscopic signals. This property indicates that high-dimensional spectroscopic signals reside in a very low-dimensional subspace and enables special data acquisition and image reconstruction strategies to be used to obtain high-resolution spatiospectral distributions with good signal-to-noise ratio. More specifically, a hybrid chemical shift imaging/echo-planar spectroscopic imaging pulse sequence is proposed for sparse sampling of (k,t)-space, and a low-rank model-based algorithm is proposed for subspace estimation and image reconstruction from sparse data with the capability to incorporate prior information and field inhomogeneity correction. The performance of the proposed method has been evaluated using both computer simulations and phantom studies, which produced very encouraging results. For two-dimensional spectroscopic imaging experiments on a metabolite phantom, a factor of 10 acceleration was achieved with a minimal loss in signal-to-noise ratio compared to the long chemical shift imaging experiments and with a significant gain in signal-to-noise ratio compared to the accelerated echo-planar spectroscopic imaging experiments. The proposed method, SPectroscopic Imaging by exploiting spatiospectral CorrElation, is able to significantly accelerate spectroscopic imaging experiments, making high-resolution metabolic imaging possible. Copyright © 2014 Wiley Periodicals, Inc.

  15. High-resolution SPECT for small-animal imaging

    International Nuclear Information System (INIS)

    Qi Yujin

    2006-01-01

    This article presents a brief overview of the development of high-resolution SPECT for small-animal imaging. A pinhole collimator has been used for high-resolution animal SPECT to provide better spatial resolution and detection efficiency in comparison with a parallel-hole collimator. The theory of imaging characteristics of the pinhole collimator is presented and the designs of the pinhole aperture are discussed. The detector technologies used for the development of small-animal SPECT and the recent advances are presented. The evolving trend of small-animal SPECT is toward a multi-pinhole and a multi-detector system to obtain a high resolution and also a high detection efficiency. (authors)

  16. AUTOMATED DETECTION OF OIL DEPOTS FROM HIGH RESOLUTION IMAGES: A NEW PERSPECTIVE

    Directory of Open Access Journals (Sweden)

    A. O. Ok

    2015-03-01

    Full Text Available This paper presents an original approach to identify oil depots from single high resolution aerial/satellite images in an automated manner. The new approach considers the symmetric nature of circular oil depots, and it computes the radial symmetry in a unique way. An automated thresholding method to focus on circular regions and a new measure to verify circles are proposed. Experiments are performed on six GeoEye-1 test images. Besides, we perform tests on 16 Google Earth images of an industrial test site acquired in a time series manner (between the years 1995 and 2012. The results reveal that our approach is capable of detecting circle objects in very different/difficult images. We computed an overall performance of 95.8% for the GeoEye-1 dataset. The time series investigation reveals that our approach is robust enough to locate oil depots in industrial environments under varying illumination and environmental conditions. The overall performance is computed as 89.4% for the Google Earth dataset, and this result secures the success of our approach compared to a state-of-the-art approach.

  17. Estimating chlorophyll with thermal and broadband multispectral high resolution imagery from an unmanned aerial system using relevance vector machines for precision agriculture

    Science.gov (United States)

    Elarab, Manal; Ticlavilca, Andres M.; Torres-Rua, Alfonso F.; Maslova, Inga; McKee, Mac

    2015-12-01

    Precision agriculture requires high-resolution information to enable greater precision in the management of inputs to production. Actionable information about crop and field status must be acquired at high spatial resolution and at a temporal frequency appropriate for timely responses. In this study, high spatial resolution imagery was obtained through the use of a small, unmanned aerial system called AggieAirTM. Simultaneously with the AggieAir flights, intensive ground sampling for plant chlorophyll was conducted at precisely determined locations. This study reports the application of a relevance vector machine coupled with cross validation and backward elimination to a dataset composed of reflectance from high-resolution multi-spectral imagery (VIS-NIR), thermal infrared imagery, and vegetative indices, in conjunction with in situ SPAD measurements from which chlorophyll concentrations were derived, to estimate chlorophyll concentration from remotely sensed data at 15-cm resolution. The results indicate that a relevance vector machine with a thin plate spline kernel type and kernel width of 5.4, having LAI, NDVI, thermal and red bands as the selected set of inputs, can be used to spatially estimate chlorophyll concentration with a root-mean-squared-error of 5.31 μg cm-2, efficiency of 0.76, and 9 relevance vectors.

  18. Gamma-Ray Imager With High Spatial And Spectral Resolution

    Science.gov (United States)

    Callas, John L.; Varnell, Larry S.; Wheaton, William A.; Mahoney, William A.

    1996-01-01

    Gamma-ray instrument developed to enable both two-dimensional imaging at relatively high spatial resolution and spectroscopy at fractional-photon-energy resolution of about 10 to the negative 3rd power in photon-energy range from 10 keV to greater than 10 MeV. In its spectroscopic aspect, instrument enables identification of both narrow and weak gamma-ray spectral peaks.

  19. High-resolution investigations of edge effects in neutron imaging

    International Nuclear Information System (INIS)

    Strobl, M.; Kardjilov, N.; Hilger, A.; Kuehne, G.; Frei, G.; Manke, I.

    2009-01-01

    Edge enhancement is the main effect measured by the so-called inline or propagation-based neutron phase contrast imaging method. The effect has originally been explained by diffraction, and high spatial coherence has been claimed to be a necessary precondition. However, edge enhancement has also been found in conventional imaging with high resolution. In such cases the effects can produce artefacts and hinder quantification. In this letter the edge effects at cylindrical shaped samples and long straight edges have been studied in detail. The enhancement can be explained by refraction and total reflection. Using high-resolution imaging, where spatial resolutions better than 50 μm could be achieved, refraction and total reflection peaks - similar to diffraction patterns - could be separated and distinguished.

  20. Comparisons between high-resolution profiles of squared refractive index gradient M2 measured by the Middle and Upper Atmosphere Radar and unmanned aerial vehicles (UAVs during the Shigaraki UAV-Radar Experiment 2015 campaign

    Directory of Open Access Journals (Sweden)

    H. Luce

    2017-03-01

    Full Text Available New comparisons between the square of the generalized potential refractive index gradient M2, estimated from the very high-frequency (VHF Middle and Upper Atmosphere (MU Radar, located at Shigaraki, Japan, and unmanned aerial vehicle (UAV measurements are presented. These comparisons were performed at unprecedented temporal and range resolutions (1–4 min and  ∼  20 m, respectively in the altitude range  ∼  1.27–4.5 km from simultaneous and nearly collocated measurements made during the ShUREX (Shigaraki UAV-Radar Experiment 2015 campaign. Seven consecutive UAV flights made during daytime on 7 June 2015 were used for this purpose. The MU Radar was operated in range imaging mode for improving the range resolution at vertical incidence (typically a few tens of meters. The proportionality of the radar echo power to M2 is reported for the first time at such high time and range resolutions for stratified conditions for which Fresnel scatter or a reflection mechanism is expected. In more complex features obtained for a range of turbulent layers generated by shear instabilities or associated with convective cloud cells, M2 estimated from UAV data does not reproduce observed radar echo power profiles. Proposed interpretations of this discrepancy are presented.

  1. Tidal Flooding and Vegetation Patterns in a Salt Marsh Tidal Creek Imaged by Low-altitude Balloon Aerial Photography

    Science.gov (United States)

    White, S. M.; Madsen, E.

    2013-12-01

    Inundation of marsh surfaces by tidal creek flooding has implications for the headward erosion of salt marsh creeks, effect of rising sea levels, biological zonation, and marsh ecosystem services. The hydroperiod; as the frequency, duration, depth and flux of water across the marsh surface; is a key factor in salt marsh ecology, but remains poorly understood due to lack of data at spatial scales relevant to tracking the spatial movement of water across the marsh. This study examines how hydroperiod, drainage networks, and tidal creek geomorphology on the vegetation at Crab Haul Creek. Crab Haul Creek is the farthest landward tidal basin in North Inlet, a bar-built estuary in South Carolina. This study measures the hydroperiod in the headwaters Crab Haul Creek with normal and near-IR photos from a helium balloon Helikite at 75-100 m altitude. Photos provide detail necessary to resolve the waterline and delineate the hydroperiod during half tidal cycles by capturing the waterline hourly from the headwaters to a piezometer transect 260 meters north. The Helikite is an ideal instrument for local investigations of surface hydrology due to its maneuverability, low cost, ability to remain aloft for extended time over a fixed point, and ability to capture high-resolution images. Photographs taken from aircraft do not provide the detail necessary to determine the waterline on the marsh surface. The near-IR images make the waterline more distinct by increasing the difference between wet and dry ground. In the headwaters of Crab Haul Creek, individual crab burrows are detected by automated image classification and the number of crab burrows and their spatial density is tracked from January-August. Crab burrows are associated with the unvegetated region at the creek head, and we relate their change over time to the propagation of the creek farther into the tidal basin. Plant zonation is influenced by the hydroperiod, but also may be affected by salinity, water table depth, and

  2. Characterisation of a resolution enhancing image inversion interferometer.

    Science.gov (United States)

    Wicker, Kai; Sindbert, Simon; Heintzmann, Rainer

    2009-08-31

    Image inversion interferometers have the potential to significantly enhance the lateral resolution and light efficiency of scanning fluorescence microscopes. Self-interference of a point source's coherent point spread function with its inverted copy leads to a reduction in the integrated signal for off-axis sources compared to sources on the inversion axis. This can be used to enhance the resolution in a confocal laser scanning microscope. We present a simple image inversion interferometer relying solely on reflections off planar surfaces. Measurements of the detection point spread function for several types of light sources confirm the predicted performance and suggest its usability for scanning confocal fluorescence microscopy.

  3. High spatial resolution CT image reconstruction using parallel computing

    International Nuclear Information System (INIS)

    Yin Yin; Liu Li; Sun Gongxing

    2003-01-01

    Using the PC cluster system with 16 dual CPU nodes, we accelerate the FBP and OR-OSEM reconstruction of high spatial resolution image (2048 x 2048). Based on the number of projections, we rewrite the reconstruction algorithms into parallel format and dispatch the tasks to each CPU. By parallel computing, the speedup factor is roughly equal to the number of CPUs, which can be up to about 25 times when 25 CPUs used. This technique is very suitable for real-time high spatial resolution CT image reconstruction. (authors)

  4. An integral design strategy combining optical system and image processing to obtain high resolution images

    Science.gov (United States)

    Wang, Jiaoyang; Wang, Lin; Yang, Ying; Gong, Rui; Shao, Xiaopeng; Liang, Chao; Xu, Jun

    2016-05-01

    In this paper, an integral design that combines optical system with image processing is introduced to obtain high resolution images, and the performance is evaluated and demonstrated. Traditional imaging methods often separate the two technical procedures of optical system design and imaging processing, resulting in the failures in efficient cooperation between the optical and digital elements. Therefore, an innovative approach is presented to combine the merit function during optical design together with the constraint conditions of image processing algorithms. Specifically, an optical imaging system with low resolution is designed to collect the image signals which are indispensable for imaging processing, while the ultimate goal is to obtain high resolution images from the final system. In order to optimize the global performance, the optimization function of ZEMAX software is utilized and the number of optimization cycles is controlled. Then Wiener filter algorithm is adopted to process the image simulation and mean squared error (MSE) is taken as evaluation criterion. The results show that, although the optical figures of merit for the optical imaging systems is not the best, it can provide image signals that are more suitable for image processing. In conclusion. The integral design of optical system and image processing can search out the overall optimal solution which is missed by the traditional design methods. Especially, when designing some complex optical system, this integral design strategy has obvious advantages to simplify structure and reduce cost, as well as to gain high resolution images simultaneously, which has a promising perspective of industrial application.

  5. Combined Spectral and Spatial Modeling of Corn Yield Based on Aerial Images and Crop Surface Models Acquired with an Unmanned Aircraft System

    Directory of Open Access Journals (Sweden)

    Jakob Geipel

    2014-10-01

    Full Text Available Precision Farming (PF management strategies are commonly based on estimations of within-field yield potential, often derived from remotely-sensed products, e.g., Vegetation Index (VI maps. These well-established means, however, lack important information, like crop height. Combinations of VI-maps and detailed 3D Crop Surface Models (CSMs enable advanced methods for crop yield prediction. This work utilizes an Unmanned Aircraft System (UAS to capture standard RGB imagery datasets for corn grain yield prediction at three early- to mid-season growth stages. The imagery is processed into simple VI-orthoimages for crop/non-crop classification and 3D CSMs for crop height determination at different spatial resolutions. Three linear regression models are tested on their prediction ability using site-specific (i unclassified mean heights, (ii crop-classified mean heights and (iii a combination of crop-classified mean heights with according crop coverages. The models show determination coefficients \\({R}^{2}\\ of up to 0.74, whereas model (iii performs best with imagery captured at the end of stem elongation and intermediate spatial resolution (0.04m\\(\\cdot\\px\\(^{-1}\\.Following these results, combined spectral and spatial modeling, based on aerial images and CSMs, proves to be a suitable method for mid-season corn yield prediction.

  6. Towards an automatic tool for resolution evaluation of mammographic images

    Energy Technology Data Exchange (ETDEWEB)

    De Oliveira, J. E. E. [FUMEC, Av. Alfonso Pena 3880, CEP 30130-009 Belo Horizonte - MG (Brazil); Nogueira, M. S., E-mail: juliae@fumec.br [Centro de Desenvolvimento da Tecnologia Nuclear / CNEN, Pte. Antonio Carlos 6627, 31270-901, Belo Horizonte - MG (Brazil)

    2014-08-15

    Quality of Mammographies from the Public and Private Services of the State. With an essentially educational character, an evaluation of the image quality is monthly held from a breast phantom in each mammographic equipment. In face of this, this work proposes to develop a protocol for automatic evaluation of image quality of mammograms so that the radiological protection and image quality requirements are met in the early detection of breast cancer. Specifically, image resolution will be addressed and evaluated, as a part of the program of image quality evaluation. Results show that for the fourth resolution and using 28 phantom images with the ground truth settled, the computer analysis of the resolution is promising and may be used as a tool for the assessment of the image quality. (Author)

  7. Towards an automatic tool for resolution evaluation of mammographic images

    International Nuclear Information System (INIS)

    De Oliveira, J. E. E.; Nogueira, M. S.

    2014-08-01

    Quality of Mammographies from the Public and Private Services of the State. With an essentially educational character, an evaluation of the image quality is monthly held from a breast phantom in each mammographic equipment. In face of this, this work proposes to develop a protocol for automatic evaluation of image quality of mammograms so that the radiological protection and image quality requirements are met in the early detection of breast cancer. Specifically, image resolution will be addressed and evaluated, as a part of the program of image quality evaluation. Results show that for the fourth resolution and using 28 phantom images with the ground truth settled, the computer analysis of the resolution is promising and may be used as a tool for the assessment of the image quality. (Author)

  8. High resolution ultrasound and photoacoustic imaging of single cells

    Directory of Open Access Journals (Sweden)

    Eric M. Strohm

    2016-03-01

    Full Text Available High resolution ultrasound and photoacoustic images of stained neutrophils, lymphocytes and monocytes from a blood smear were acquired using a combined acoustic/photoacoustic microscope. Photoacoustic images were created using a pulsed 532 nm laser that was coupled to a single mode fiber to produce output wavelengths from 532 nm to 620 nm via stimulated Raman scattering. The excitation wavelength was selected using optical filters and focused onto the sample using a 20× objective. A 1000 MHz transducer was co-aligned with the laser spot and used for ultrasound and photoacoustic images, enabling micrometer resolution with both modalities. The different cell types could be easily identified due to variations in contrast within the acoustic and photoacoustic images. This technique provides a new way of probing leukocyte structure with potential applications towards detecting cellular abnormalities and diseased cells at the single cell level.

  9. 3D super-resolution imaging with blinking quantum dots

    Science.gov (United States)

    Wang, Yong; Fruhwirth, Gilbert; Cai, En; Ng, Tony; Selvin, Paul R.

    2013-01-01

    Quantum dots are promising candidates for single molecule imaging due to their exceptional photophysical properties, including their intense brightness and resistance to photobleaching. They are also notorious for their blinking. Here we report a novel way to take advantage of quantum dot blinking to develop an imaging technique in three-dimensions with nanometric resolution. We first applied this method to simulated images of quantum dots, and then to quantum dots immobilized on microspheres. We achieved imaging resolutions (FWHM) of 8–17 nm in the x-y plane and 58 nm (on coverslip) or 81 nm (deep in solution) in the z-direction, approximately 3–7 times better than what has been achieved previously with quantum dots. This approach was applied to resolve the 3D distribution of epidermal growth factor receptor (EGFR) molecules at, and inside of, the plasma membrane of resting basal breast cancer cells. PMID:24093439

  10. Aerial thermal images to assess irrigation efficiency in 'Vitis vinifera' cv. Albariño

    Science.gov (United States)

    Gonzalez, Xesús Pablo; Fandiño, María; Rey, Benjamín J.; José Cancela, Javier

    2017-04-01

    Canopy temperature was defined as key data to irrigation management and to detect crop water stress (Jackson, 1982). Recently, temperature camera was installed on board in a Unmanned Aerial Vehicle (UAV), thus heterogeneity within field could be determined. Pereira et al. (2012) have defined the conceptual and terminological study of crop water use indicators, mainly water use efficiency (WUE) and water productivity (WP). Actually, it is crucial achieve higher WP and WUE, where crop yield variability between years must be reduced with the smallest irrigation water, but with a correct management of crop water stress during the season. In this study, Albariño cultivar grapevine, priority in Galicia (Spain) in Designation of Origen 'Rías Baixas', was assessed in relation to water productivity index, focus on irrigation treatments aspects, during 2016. Albariño vineyard was planted in 1996 on 110-Richter at a spacing of 3 × 2 m (1667 vines ha-1) (41°57 6 N, 8°49 26 W, elevation 101 m). Vines were trained to a vertical trellis system on a Guyot oriented in the East-West direction. Three irrigation treatments were applied: irrigation from budburst to maturation (T1), from flowering to maturation (T2), and from veraison to maturation (T3), moreover a rain-fed treatment was implemented. All WP index was referred to farm yield level (kg ha-1); where the denominator applied to WP TWUfarm, introduced rainfall and irrigation depth; to WP Irrig, only irrigation depth applied; was used. Moreover, crop water stress index (CWSI) was used to determine homogenize areas within experimental plot, using an UAV with a thermal camera (ThermoMAP, senseFly, SW) to achieve a final map with 14 cm per pixel resolution. During August 11th, at the end of veraison, camera was installed in an 'eBee Ag' UAV (senseFly, SW) with a median flight altitude of 75 m over ground level. Yield per hectare were recorded and total irrigation depth per treatment during the growing season from March to

  11. Molecular-resolution imaging of pentacene on KCl(001

    Directory of Open Access Journals (Sweden)

    Julia L. Neff

    2012-02-01

    Full Text Available The growth of pentacene on KCl(001 at submonolayer coverage was studied by dynamic scanning force microscopy. At coverages below one monolayer pentacene was found to arrange in islands with an upright configuration. The molecular arrangement was resolved in high-resolution images. In these images two different types of patterns were observed, which switch repeatedly. In addition, defects were found, such as a molecular vacancy and domain boundaries.

  12. Fast iterative segmentation of high resolution medical images

    International Nuclear Information System (INIS)

    Hebert, T.J.

    1996-01-01

    Various applications in positron emission tomography (PET), single photon emission computed tomography (SPECT) and magnetic resonance imaging (MRI) require segmentation of 20 to 60 high resolution images of size 256x256 pixels in 3-9 seconds per image. This places particular constraints on the design of image segmentation algorithms. This paper examines the trade-offs in segmenting images based on fitting a density function to the pixel intensities using curve-fitting versus the maximum likelihood method. A quantized data representation is proposed and the EM algorithm for fitting a finite mixture density function to the quantized representation for an image is derived. A Monte Carlo evaluation of mean estimation error and classification error showed that the resulting quantized EM algorithm dramatically reduces the required computation time without loss of accuracy

  13. Nonlinear Optics Approaches Towards Subdiffraction Resolution in CARS Imaging

    NARCIS (Netherlands)

    Boller, Klaus J.; Beeker, W.P.; Cleff, C.; Kruse, K.; Lee, Christopher James; Gross, P.; Offerhaus, Herman L.; Fallnich, Carsten; Herek, Jennifer Lynn; Fornasiero, E.F.; Rizzoli, S.O.

    2014-01-01

    In theoretical investigations, we review several nonlinear optical approaches towards subdiffraction-limited resolution in label-free imaging via coherent anti-Stokes Raman scattering (CARS). Using a density matrix model and numerical integration, we investigate various level schemes and

  14. Structure Identification in High-Resolution Transmission Electron Microscopic Images

    DEFF Research Database (Denmark)

    Vestergaard, Jacob Schack; Kling, Jens; Dahl, Anders Bjorholm

    2014-01-01

    A connection between microscopic structure and macroscopic properties is expected for almost all material systems. High-resolution transmission electron microscopy is a technique offering insight into the atomic structure, but the analysis of large image series can be time consuming. The present ...

  15. An improved technique for the prediction of optimal image resolution ...

    African Journals Online (AJOL)

    user

    2010-10-04

    Oct 4, 2010 ... Available online at http://www.academicjournals.org/AJEST ... robust technique for predicting optimal image resolution for the mapping of savannah ecosystems was developed. .... whether to purchase multi-spectral imagery acquired by GeoEye-2 ..... Analysis of the spectral behaviour of the pasture class in.

  16. An improved technique for the prediction of optimal image resolution ...

    African Journals Online (AJOL)

    Past studies to predict optimal image resolution required for generating spatial information for savannah ecosystems have yielded different outcomes, hence providing a knowledge gap that was investigated in the present study. The postulation, for the present study, was that by graphically solving two simultaneous ...

  17. Effects of pose and image resolution on automatic face recognition

    NARCIS (Netherlands)

    Mahmood, Zahid; Ali, Tauseef; Khan, Samee U.

    The popularity of face recognition systems have increased due to their use in widespread applications. Driven by the enormous number of potential application domains, several algorithms have been proposed for face recognition. Face pose and image resolutions are among the two important factors that

  18. Super-resolution Microscopy in Plant Cell Imaging.

    Science.gov (United States)

    Komis, George; Šamajová, Olga; Ovečka, Miroslav; Šamaj, Jozef

    2015-12-01

    Although the development of super-resolution microscopy methods dates back to 1994, relevant applications in plant cell imaging only started to emerge in 2010. Since then, the principal super-resolution methods, including structured-illumination microscopy (SIM), photoactivation localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), and stimulated emission depletion microscopy (STED), have been implemented in plant cell research. However, progress has been limited due to the challenging properties of plant material. Here we summarize the basic principles of existing super-resolution methods and provide examples of applications in plant science. The limitations imposed by the nature of plant material are reviewed and the potential for future applications in plant cell imaging is highlighted. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. Robust microbubble tracking for super resolution imaging in ultrasound

    DEFF Research Database (Denmark)

    Hansen, Kristoffer B.; Villagómez Hoyos, Carlos Armando; Brasen, Jens Christian

    2016-01-01

    Currently ultrasound resolution is limited by diffraction to approximately half the wavelength of the sound wave employed. In recent years, super resolution imaging techniques have overcome the diffraction limit through the localization and tracking of a sparse set of microbubbles through...... the vasculature. However, this has only been performed on fixated tissue, limiting its clinical application. This paper proposes a technique for making super resolution images on non-fixated tissue by first compensating for tissue movement and then tracking the individual microbubbles. The experiment is performed...... on the kidney of a anesthetized Sprage-Dawley rat by infusing SonoVue at 0.1× original concentration. The algorithm demonstrated in vivo that the motion compensation was capable of removing the movement caused by the mechanical ventilator. The results shows that microbubbles were localized with a higher...

  20. Wavelet Filter Banks for Super-Resolution SAR Imaging

    Science.gov (United States)

    Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess

    2011-01-01

    This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

  1. Linearized inversion frameworks toward high-resolution seismic imaging

    KAUST Repository

    Aldawood, Ali

    2016-09-01

    Seismic exploration utilizes controlled sources, which emit seismic waves that propagate through the earth subsurface and get reflected off subsurface interfaces and scatterers. The reflected and scattered waves are recorded by recording stations installed along the earth surface or down boreholes. Seismic imaging is a powerful tool to map these reflected and scattered energy back to their subsurface scattering or reflection points. Seismic imaging is conventionally based on the single-scattering assumption, where only energy that bounces once off a subsurface scatterer and recorded by a receiver is projected back to its subsurface position. The internally multiply scattered seismic energy is considered as unwanted noise and is usually suppressed or removed from the recorded data. Conventional seismic imaging techniques yield subsurface images that suffer from low spatial resolution, migration artifacts, and acquisition fingerprint due to the limited acquisition aperture, number of sources and receivers, and bandwidth of the source wavelet. Hydrocarbon traps are becoming more challenging and considerable reserves are trapped in stratigraphic and pinch-out traps, which require highly resolved seismic images to delineate them. This thesis focuses on developing and implementing new advanced cost-effective seismic imaging techniques aiming at enhancing the resolution of the migrated images by exploiting the sparseness of the subsurface reflectivity distribution and utilizing the multiples that are usually neglected when imaging seismic data. I first formulate the seismic imaging problem as a Basis pursuit denoise problem, which I solve using an L1-minimization algorithm to obtain the sparsest migrated image corresponding to the recorded data. Imaging multiples may illuminate subsurface zones, which are not easily illuminated by conventional seismic imaging using primary reflections only. I then develop an L2-norm (i.e. least-squares) inversion technique to image

  2. AN IMPROVED SNAKE MODEL FOR REFINEMENT OF LIDAR-DERIVED BUILDING ROOF CONTOURS USING AERIAL IMAGES

    Directory of Open Access Journals (Sweden)

    Q. Chen

    2016-06-01

    Full Text Available Building roof contours are considered as very important geometric data, which have been widely applied in many fields, including but not limited to urban planning, land investigation, change detection and military reconnaissance. Currently, the demand on building contours at a finer scale (especially in urban areas has been raised in a growing number of studies such as urban environment quality assessment, urban sprawl monitoring and urban air pollution modelling. LiDAR is known as an effective means of acquiring 3D roof points with high elevation accuracy. However, the precision of the building contour obtained from LiDAR data is restricted by its relatively low scanning resolution. With the use of the texture information from high-resolution imagery, the precision can be improved. In this study, an improved snake model is proposed to refine the initial building contours extracted from LiDAR. First, an improved snake model is constructed with the constraints of the deviation angle, image gradient, and area. Then, the nodes of the contour are moved in a certain range to find the best optimized result using greedy algorithm. Considering both precision and efficiency, the candidate shift positions of the contour nodes are constrained, and the searching strategy for the candidate nodes is explicitly designed. The experiments on three datasets indicate that the proposed method for building contour refinement is effective and feasible. The average quality index is improved from 91.66% to 93.34%. The statistics of the evaluation results for every single building demonstrated that 77.0% of the total number of contours is updated with higher quality index.

  3. Resolution-recovery-embedded image reconstruction for a high-resolution animal SPECT system.

    Science.gov (United States)

    Zeraatkar, Navid; Sajedi, Salar; Farahani, Mohammad Hossein; Arabi, Hossein; Sarkar, Saeed; Ghafarian, Pardis; Rahmim, Arman; Ay, Mohammad Reza

    2014-11-01

    The small-animal High-Resolution SPECT (HiReSPECT) is a dedicated dual-head gamma camera recently designed and developed in our laboratory for imaging of murine models. Each detector is composed of an array of 1.2 × 1.2 mm(2) (pitch) pixelated CsI(Na) crystals. Two position-sensitive photomultiplier tubes (H8500) are coupled to each head's crystal. In this paper, we report on a resolution-recovery-embedded image reconstruction code applicable to the system and present the experimental results achieved using different phantoms and mouse scans. Collimator-detector response functions (CDRFs) were measured via a pixel-driven method using capillary sources at finite distances from the head within the field of view (FOV). CDRFs were then fitted by independent Gaussian functions. Thereafter, linear interpolations were applied to the standard deviation (σ) values of the fitted Gaussians, yielding a continuous map of CDRF at varying distances from the head. A rotation-based maximum-likelihood expectation maximization (MLEM) method was used for reconstruction. A fast rotation algorithm was developed to rotate the image matrix according to the desired angle by means of pre-generated rotation maps. The experiments demonstrated improved resolution utilizing our resolution-recovery-embedded image reconstruction. While the full-width at half-maximum (FWHM) radial and tangential resolution measurements of the system were over 2 mm in nearly all positions within the FOV without resolution recovery, reaching around 2.5 mm in some locations, they fell below 1.8 mm everywhere within the FOV using the resolution-recovery algorithm. The noise performance of the system was also acceptable; the standard deviation of the average counts per voxel in the reconstructed images was 6.6% and 8.3% without and with resolution recovery, respectively. Copyright © 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  4. Learning-based compressed sensing for infrared image super resolution

    Science.gov (United States)

    Zhao, Yao; Sui, Xiubao; Chen, Qian; Wu, Shaochi

    2016-05-01

    This paper presents an infrared image super-resolution method based on compressed sensing (CS). First, the reconstruction model under the CS framework is established and a Toeplitz matrix is selected as the sensing matrix. Compared with traditional learning-based methods, the proposed method uses a set of sub-dictionaries instead of two coupled dictionaries to recover high resolution (HR) images. And Toeplitz sensing matrix allows the proposed method time-efficient. Second, all training samples are divided into several feature spaces by using the proposed adaptive k-means classification method, which is more accurate than the standard k-means method. On the basis of this approach, a complex nonlinear mapping from the HR space to low resolution (LR) space can be converted into several compact linear mappings. Finally, the relationships between HR and LR image patches can be obtained by multi-sub-dictionaries and HR infrared images are reconstructed by the input LR images and multi-sub-dictionaries. The experimental results show that the proposed method is quantitatively and qualitatively more effective than other state-of-the-art methods.

  5. Adaptive optics with pupil tracking for high resolution retinal imaging.

    Science.gov (United States)

    Sahin, Betul; Lamory, Barbara; Levecq, Xavier; Harms, Fabrice; Dainty, Chris

    2012-02-01

    Adaptive optics, when integrated into retinal imaging systems, compensates for rapidly changing ocular aberrations in real time and results in improved high resolution images that reveal the photoreceptor mosaic. Imaging the retina at high resolution has numerous potential medical applications, and yet for the development of commercial products that can be used in the clinic, the complexity and high cost of the present research systems have to be addressed. We present a new method to control the deformable mirror in real time based on pupil tracking measurements which uses the default camera for the alignment of the eye in the retinal imaging system and requires no extra cost or hardware. We also present the first experiments done with a compact adaptive optics flood illumination fundus camera where it was possible to compensate for the higher order aberrations of a moving model eye and in vivo in real time based on pupil tracking measurements, without the real time contribution of a wavefront sensor. As an outcome of this research, we showed that pupil tracking can be effectively used as a low cost and practical adaptive optics tool for high resolution retinal imaging because eye movements constitute an important part of the ocular wavefront dynamics.

  6. Natural-pose hand detection in low-resolution images

    Directory of Open Access Journals (Sweden)

    Nyan Bo Bo1

    2009-07-01

    Full Text Available Robust real-time hand detection and tracking in video sequences would enable many applications in areas as diverse ashuman-computer interaction, robotics, security and surveillance, and sign language-based systems. In this paper, we introducea new approach for detecting human hands that works on single, cluttered, low-resolution images. Our prototype system, whichis primarily intended for security applications in which the images are noisy and low-resolution, is able to detect hands as smallas 2424 pixels in cluttered scenes. The system uses grayscale appearance information to classify image sub-windows as eithercontaining or not containing a human hand very rapidly at the cost of a high false positive rate. To improve on the false positiverate of the main classifier without affecting its detection rate, we introduce a post-processor system that utilizes the geometricproperties of skin color blobs. When we test our detector on a test image set containing 106 hands, 92 of those hands aredetected (86.8% detection rate, with an average false positive rate of 1.19 false positive detections per image. The rapiddetection speed, the high detection rate of 86.8%, and the low false positive rate together ensure that our system is useable asthe main detector in a diverse variety of applications requiring robust hand detection and tracking in low-resolution, clutteredscenes.

  7. Measurement of the Energy-Dependent Angular Response of the ARES Detector System and Application to Aerial Imaging

    Science.gov (United States)

    Joshi, Tenzing H. Y.; Quiter, Brian J.; Maltz, Jonathan S.; Bandstra, Mark S.; Haefner, Andrew; Eikmeier, Nicole; Wagner, Eric; Luke, Tanushree; Malchow, Russell; McCall, Karen

    2017-07-01

    The Airborne Radiological Enhanced-sensor System (ARES) includes a prototype helicopter-borne CsI(Na) detector array that has been developed as part of the DHS Domestic Nuclear Detection Office Advanced Technology Demonstration. The detector system geometry comprises two pairs of 23-detector arrays designed to function as active masks, providing additional angular resolution of measured gamma rays in the roll dimension. Experimental measurements, using five radioisotopes (137Cs, 60Co, 241Am, 131I, and 99mTc), were performed to map the detector response in both roll and pitch dimensions. This paper describes the acquisition and analysis of these characterization measurements, calculation of the angular response of the ARES system, and how this response function is used to improve aerial detection and localization of radiological and nuclear threat sources.

  8. Optimized multiple linear mappings for single image super-resolution

    Science.gov (United States)

    Zhang, Kaibing; Li, Jie; Xiong, Zenggang; Liu, Xiuping; Gao, Xinbo

    2017-12-01

    Learning piecewise linear regression has been recognized as an effective way for example learning-based single image super-resolution (SR) in literature. In this paper, we employ an expectation-maximization (EM) algorithm to further improve the SR performance of our previous multiple linear mappings (MLM) based SR method. In the training stage, the proposed method starts with a set of linear regressors obtained by the MLM-based method, and then jointly optimizes the clustering results and the low- and high-resolution subdictionary pairs for regression functions by using the metric of the reconstruction errors. In the test stage, we select the optimal regressor for SR reconstruction by accumulating the reconstruction errors of m-nearest neighbors in the training set. Thorough experimental results carried on six publicly available datasets demonstrate that the proposed SR method can yield high-quality images with finer details and sharper edges in terms of both quantitative and perceptual image quality assessments.

  9. Image thresholding in the high resolution target movement monitor

    Science.gov (United States)

    Moss, Randy H.; Watkins, Steve E.; Jones, Tristan H.; Apel, Derek B.; Bairineni, Deepti

    2009-03-01

    Image thresholding in the High Resolution Target Movement Monitor (HRTMM) is examined. The HRTMM was developed at the Missouri University of Science and Technology to detect and measure wall movements in underground mines to help reduce fatality and injury rates. The system detects the movement of a target with sub-millimeter accuracy based on the images of one or more laser dots projected on the target and viewed by a high-resolution camera. The relative position of the centroid of the laser dot (determined by software using thresholding concepts) in the images is the key factor in detecting the target movement. Prior versions of the HRTMM set the image threshold based on a manual, visual examination of the images. This work systematically examines the effect of varying threshold on the calculated centroid position and describes an algorithm for determining a threshold setting. First, the thresholding effects on the centroid position are determined for a stationary target. Plots of the centroid positions as a function of varying thresholds are obtained to identify clusters of thresholds for which the centroid position does not change for stationary targets. Second, the target is moved away from the camera in sub-millimeter increments and several images are obtained at each position and analyzed as a function of centroid position, target movement and varying threshold values. With this approach, the HRTMM can accommodate images in batch mode without the need for manual intervention. The capability for the HRTMM to provide automated, continuous monitoring of wall movement is enhanced.

  10. Post-Processing Approach for Refining Raw Land Cover Change Detection of Very High-Resolution Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Zhiyong Lv

    2018-03-01

    Full Text Available In recent decades, land cover change detection (LCCD using very high-spatial resolution (VHR remote sensing images has been a major research topic. However, VHR remote sensing images usually lead to a large amount of noises in spectra, thereby reducing the reliability of the detected results. To solve this problem, this study proposes an object-based expectation maximization (OBEM post-processing approach for enhancing raw LCCD results. OBEM defines a refinement of the labeling in a detected map to enhance its raw detection accuracies. Current mainstream change detection (preprocessing techniques concentrate on proposing a change magnitude measurement or considering image spatial features to obtain a change detection map. The proposed OBEM approach is a new solution to enhance change detection accuracy by refining the raw result. Post-processing approaches can achieve competitive accuracies to the preprocessing methods, but in a direct and succinct manner. The proposed OBEM post-processing method synthetically considers multi-scale segmentation and expectation maximum algorithms to refine the raw change detection result. Then, the influence of the scale of segmentation on the LCCD accuracy of the proposed OBEM is investigated. Four pairs of remote sensing images, one of two pairs (aerial image with 0.5 m/pixel resolution which depict two landslide sites on Landtau Island, Hong Kong, China, are used in the experiments to evaluate the effectiveness of the proposed approach. In addition, the proposed approach is applied, and validated by two case studies, LCCD in Tianjin City China (SPOT-5 satellite image with 2.5 m/pixel resolution and Mexico forest fire case (Landsat TM images with 30 m/pixel resolution, respectively. Quantitative evaluations show that the proposed OBEM post-processing approach can achieve better performance and higher accuracies than several commonly used preprocessing methods. To the best of the authors’ knowledge, this type

  11. A hybrid MLP-CNN classifier for very fine resolution remotely sensed image classification

    Science.gov (United States)

    Zhang, Ce; Pan, Xin; Li, Huapeng; Gardiner, Andy; Sargent, Isabel; Hare, Jonathon; Atkinson, Peter M.

    2018-06-01

    The contextual-based convolutional neural network (CNN) with deep architecture and pixel-based multilayer perceptron (MLP) with shallow structure are well-recognized neural network algorithms, representing the state-of-the-art deep learning method and the classical non-parametric machine learning approach, respectively. The two algorithms, which have very different behaviours, were integrated in a concise and effective way using a rule-based decision fusion approach for the classification of very fine spatial resolution (VFSR) remotely sensed imagery. The decision fusion rules, designed primarily based on the classification confidence of the CNN, reflect the generally complementary patterns of the individual classifiers. In consequence, the proposed ensemble classifier MLP-CNN harvests the complementary results acquired from the CNN based on deep spatial feature representation and from the MLP based on spectral discrimination. Meanwhile, limitations of the CNN due to the adoption of convolutional filters such as the uncertainty in object boundary partition and loss of useful fine spatial resolution detail were compensated. The effectiveness of the ensemble MLP-CNN classifier was tested in both urban and rural areas using aerial photography together with an additional satellite sensor dataset. The MLP-CNN classifier achieved promising performance, consistently outperforming the pixel-based MLP, spectral and textural-based MLP, and the contextual-based CNN in terms of classification accuracy. This research paves the way to effectively address the complicated problem of VFSR image classification.

  12. The inelastic contribution to high resolution images of defects

    International Nuclear Information System (INIS)

    Krivanek, O.L.; Ahn, C.C.; Wood, G.J.

    1990-01-01

    The importance of the contribution due to inelastically scattered electrons to unfiltered HREM images is examined, with emphasis on imaging of defects in semiconductors. Whenever the low energy loss spectrum contains sharp peaks, the contribution is not featureless. At specimen thickness of a few tens of nm, it may change the image appearance in a major way. The strongest effect occurs in high resolution, medium voltage (200 to 500 kV) electron microscope images of defects at focus values minimizing the contrast of the elastic image in low Z materials such as Al and Si. In higher Z materials or those with no sharp 'plasmons', the contribution is small. 23 refs., 8 figs

  13. Optimization of Monochromated TEM for Ultimate Resolution Imaging and Ultrahigh Resolution Electron Energy Loss Spectroscopy

    KAUST Repository

    Lopatin, Sergei; Cheng, Bin; Liu, Wei-Ting; Tsai, Meng-Lin; He, Jr-Hau; Chuvilin, Andrey

    2017-01-01

    The performance of a monochromated transmission electron microscope with Wien type monochromator is optimized to achieve an extremely narrow energy spread of electron beam and an ultrahigh energy resolution with spectroscopy. The energy spread in the beam is improved by almost an order of magnitude as compared to specified values. The optimization involves both the monochromator and the electron energy loss detection system. We demonstrate boosted capability of optimized systems with respect to ultra-low loss EELS and sub-angstrom resolution imaging (in a combination with spherical aberration correction).

  14. Study of DOI resolution and imaging resolution of a PET device

    International Nuclear Information System (INIS)

    Saha, Lipika; Saitoh, Kazumi; Kobayashi, Shigeharu

    2004-01-01

    As a recent trend of DOI measurement for the PET, a simple method of utilizing the light attenuation properties of scintillation materials has been paid attention. We have studied the DOI resolutions for less expensive materials as BGO in both the bench test and the simulation by GEANT4.0. By comparison with both the results, we have recognized the importance of removing the multiple Compton absorption events to obtain the better DOI information. The simulation results for the imaging resolution suggested that its deterioration attributes to the parallax error as well as the systematic displacement inherent in the present method of 3D-reconstruction

  15. Optimization of Monochromated TEM for Ultimate Resolution Imaging and Ultrahigh Resolution Electron Energy Loss Spectroscopy

    KAUST Repository

    Lopatin, Sergei

    2017-09-01

    The performance of a monochromated transmission electron microscope with Wien type monochromator is optimized to achieve an extremely narrow energy spread of electron beam and an ultrahigh energy resolution with spectroscopy. The energy spread in the beam is improved by almost an order of magnitude as compared to specified values. The optimization involves both the monochromator and the electron energy loss detection system. We demonstrate boosted capability of optimized systems with respect to ultra-low loss EELS and sub-angstrom resolution imaging (in a combination with spherical aberration correction).

  16. Improving PET spatial resolution and detectability for prostate cancer imaging

    International Nuclear Information System (INIS)

    Bal, H; Guerin, L; Casey, M E; Conti, M; Eriksson, L; Michel, C; Fanti, S; Pettinato, C; Adler, S; Choyke, P

    2014-01-01

    Prostate cancer, one of the most common forms of cancer among men, can benefit from recent improvements in positron emission tomography (PET) technology. In particular, better spatial resolution, lower noise and higher detectability of small lesions could be greatly beneficial for early diagnosis and could provide a strong support for guiding biopsy and surgery. In this article, the impact of improved PET instrumentation with superior spatial resolution and high sensitivity are discussed, together with the latest development in PET technology: resolution recovery and time-of-flight reconstruction. Using simulated cancer lesions, inserted in clinical PET images obtained with conventional protocols, we show that visual identification of the lesions and detectability via numerical observers can already be improved using state of the art PET reconstruction methods. This was achieved using both resolution recovery and time-of-flight reconstruction, and a high resolution image with 2 mm pixel size. Channelized Hotelling numerical observers showed an increase in the area under the LROC curve from 0.52 to 0.58. In addition, a relationship between the simulated input activity and the area under the LROC curve showed that the minimum detectable activity was reduced by more than 23%. (paper)

  17. Noise and physical limits to maximum resolution of PET images

    Energy Technology Data Exchange (ETDEWEB)

    Herraiz, J.L.; Espana, S. [Dpto. Fisica Atomica, Molecular y Nuclear, Facultad de Ciencias Fisicas, Universidad Complutense de Madrid, Avda. Complutense s/n, E-28040 Madrid (Spain); Vicente, E.; Vaquero, J.J.; Desco, M. [Unidad de Medicina y Cirugia Experimental, Hospital GU ' Gregorio Maranon' , E-28007 Madrid (Spain); Udias, J.M. [Dpto. Fisica Atomica, Molecular y Nuclear, Facultad de Ciencias Fisicas, Universidad Complutense de Madrid, Avda. Complutense s/n, E-28040 Madrid (Spain)], E-mail: jose@nuc2.fis.ucm.es

    2007-10-01

    In this work we show that there is a limit for the maximum resolution achievable with a high resolution PET scanner, as well as for the best signal-to-noise ratio, which are ultimately related to the physical effects involved in the emission and detection of the radiation and thus they cannot be overcome with any particular reconstruction method. These effects prevent the spatial high frequency components of the imaged structures to be recorded by the scanner. Therefore, the information encoded in these high frequencies cannot be recovered by any reconstruction technique. Within this framework, we have determined the maximum resolution achievable for a given acquisition as a function of data statistics and scanner parameters, like the size of the crystals or the inter-crystal scatter. In particular, the noise level in the data as a limitation factor to yield high-resolution images in tomographs with small crystal sizes is outlined. These results have implications regarding how to decide the optimal number of voxels of the reconstructed image or how to design better PET scanners.

  18. Noise and physical limits to maximum resolution of PET images

    International Nuclear Information System (INIS)

    Herraiz, J.L.; Espana, S.; Vicente, E.; Vaquero, J.J.; Desco, M.; Udias, J.M.

    2007-01-01

    In this work we show that there is a limit for the maximum resolution achievable with a high resolution PET scanner, as well as for the best signal-to-noise ratio, which are ultimately related to the physical effects involved in the emission and detection of the radiation and thus they cannot be overcome with any particular reconstruction method. These effects prevent the spatial high frequency components of the imaged structures to be recorded by the scanner. Therefore, the information encoded in these high frequencies cannot be recovered by any reconstruction technique. Within this framework, we have determined the maximum resolution achievable for a given acquisition as a function of data statistics and scanner parameters, like the size of the crystals or the inter-crystal scatter. In particular, the noise level in the data as a limitation factor to yield high-resolution images in tomographs with small crystal sizes is outlined. These results have implications regarding how to decide the optimal number of voxels of the reconstructed image or how to design better PET scanners

  19. Spatial scales of pollution from variable resolution satellite imaging

    International Nuclear Information System (INIS)

    Chudnovsky, Alexandra A.; Kostinski, Alex; Lyapustin, Alexei; Koutrakis, Petros

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM 2.5 as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM 2.5 and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM 2.5 ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM 2.5 levels and wind speed. - Highlights: ► The correlation between PM 2.5 and AOD decreases as AOD resolution is degraded. ► High resolution MAIAC AOD 1 km retrieval can be used to investigate within-city PM 2.5 variability. ► Low pollution days exhibit higher spatial variability of AOD and PM 2.5 then moderate pollution days. ► AOD spatial variability within urban area is higher during the lower wind speed conditions. - The correlation between PM 2.5 and AOD decreases as AOD resolution is degraded. The new high-resolution MAIAC AOD retrieval has the potential to capture PM 2.5 variability at the intra-urban scale.

  20. Subpicosecond time-resolution image converter the picochron

    International Nuclear Information System (INIS)

    Butslov, M.M.; Fanchenko, S.D.; Chikin, R.V.

    The problem of X-band resonance ultra-high-speed electron image swept in image converters is considered. A time analysis image converter tube is described. It is provided with a circular image-sweeping system, the sweeping speed ranging from 1 up to 2 light velocities. The swept-image intensifier makes it possible to record every electron emerging from the input photocathode. The time analysis electrostatic lens provides an electronic field at the input photocathode, strong enough to obtain a high physical time resolution. The image sweeping system to be described enables one to have a 5.10 -13 s time resolution over on observation period as long as 5.10 -8 s. It requires no precise limiting with the process to observed. The picochron tube design is described together with some results of its testing in Nd-laser experiments. Transitories as short as 0.5-1psec have been detected in ultra-short laser radiation pulses

  1. Dynamic Raman imaging system with high spatial and temporal resolution

    Science.gov (United States)

    Wang, Lei; Dai, Yinzhen; He, Hao; Lv, Ruiqi; Zong, Cheng; Ren, Bin

    2017-09-01

    There is an increasing need to study dynamic changing systems with significantly high spatial and temporal resolutions. In this work, we integrated point-scanning, line-scanning, and wide-field Raman imaging techniques into a single system. By using an Electron Multiplying CCD (EMCCD) with a high gain and high frame rate, we significantly reduced the time required for wide-field imaging, making it possible to monitor the electrochemical reactions in situ. The highest frame rate of EMCDD was ˜50 fps, and the Raman images for a specific Raman peak can be obtained by passing the signal from the sample through the Liquid Crystal Tunable Filter. The spatial resolutions of scanning imaging and wide-field imaging with a 100× objective (NA = 0.9) are 0.5 × 0.5 μm2 and 0.36 × 0.36 μm2, respectively. The system was used to study the surface plasmon resonance of Au nanorods, the surface-enhanced Raman scattering signal distribution for Au Nanoparticle aggregates, and dynamic Raman imaging of an electrochemical reacting system.

  2. Super-Resolution Image Reconstruction Applied to Medical Ultrasound

    Science.gov (United States)

    Ellis, Michael

    Ultrasound is the preferred imaging modality for many diagnostic applications due to its real-time image reconstruction and low cost. Nonetheless, conventional ultrasound is not used in many applications because of limited spatial resolution and soft tissue contrast. Most commercial ultrasound systems reconstruct images using a simple delay-and-sum architecture on receive, which is fast and robust but does not utilize all information available in the raw data. Recently, more sophisticated image reconstruction methods have been developed that make use of far more information in the raw data to improve resolution and contrast. One such method is the Time-Domain Optimized Near-Field Estimator (TONE), which employs a maximum a priori estimation to solve a highly underdetermined problem, given a well-defined system model. TONE has been shown to significantly improve both the contrast and resolution of ultrasound images when compared to conventional methods. However, TONE's lack of robustness to variations from the system model and extremely high computational cost hinder it from being readily adopted in clinical scanners. This dissertation aims to reduce the impact of TONE's shortcomings, transforming it from an academic construct to a clinically viable image reconstruction algorithm. By altering the system model from a collection of individual hypothetical scatterers to a collection of weighted, diffuse regions, dTONE is able to achieve much greater robustness to modeling errors. A method for efficient parallelization of dTONE is presented that reduces reconstruction time by more than an order of magnitude with little loss in image fidelity. An alternative reconstruction algorithm, called qTONE, is also developed and is able to reduce reconstruction times by another two orders of magnitude while simultaneously improving image contrast. Each of these methods for improving TONE are presented, their limitations are explored, and all are used in concert to reconstruct in

  3. A parallel solution for high resolution histological image analysis.

    Science.gov (United States)

    Bueno, G; González, R; Déniz, O; García-Rojo, M; González-García, J; Fernández-Carrobles, M M; Vállez, N; Salido, J

    2012-10-01

    This paper describes a general methodology for developing parallel image processing algorithms based on message passing for high resolution images (on the order of several Gigabytes). These algorithms have been applied to histological images and must be executed on massively parallel processing architectures. Advances in new technologies for complete slide digitalization in pathology have been combined with developments in biomedical informatics. However, the efficient use of these digital slide systems is still a challenge. The image processing that these slides are subject to is still limited both in terms of data processed and processing methods. The work presented here focuses on the need to design and develop parallel image processing tools capable of obtaining and analyzing the entire gamut of information included in digital slides. Tools have been developed to assist pathologists in image analysis and diagnosis, and they cover low and high-level image processing methods applied to histological images. Code portability, reusability and scalability have been tested by using the following parallel computing architectures: distributed memory with massive parallel processors and two networks, INFINIBAND and Myrinet, composed of 17 and 1024 nodes respectively. The parallel framework proposed is flexible, high performance solution and it shows that the efficient processing of digital microscopic images is possible and may offer important benefits to pathology laboratories. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  4. Adaptive optics improves multiphoton super-resolution imaging

    Science.gov (United States)

    Zheng, Wei; Wu, Yicong; Winter, Peter; Shroff, Hari

    2018-02-01

    Three dimensional (3D) fluorescence microscopy has been essential for biological studies. It allows interrogation of structure and function at spatial scales spanning the macromolecular, cellular, and tissue levels. Critical factors to consider in 3D microscopy include spatial resolution, signal-to-noise (SNR), signal-to-background (SBR), and temporal resolution. Maintaining high quality imaging becomes progressively more difficult at increasing depth (where optical aberrations, induced by inhomogeneities of refractive index in the sample, degrade resolution and SNR), and in thick or densely labeled samples (where out-of-focus background can swamp the valuable, in-focus-signal from each plane). In this report, we introduce our new instrumentation to address these problems. A multiphoton structured illumination microscope was simply modified to integrate an adpative optics system for optical aberrations correction. Firstly, the optical aberrations are determined using direct wavefront sensing with a nonlinear guide star and subsequently corrected using a deformable mirror, restoring super-resolution information. We demonstrate the flexibility of our adaptive optics approach on a variety of semi-transparent samples, including bead phantoms, cultured cells in collagen gels and biological tissues. The performance of our super-resolution microscope is improved in all of these samples, as peak intensity is increased (up to 40-fold) and resolution recovered (up to 176+/-10 nm laterally and 729+/-39 nm axially) at depths up to 250 μm from the coverslip surface.

  5. Snow and Ice Products from the Moderate Resolution Imaging Spectroradiometer

    Science.gov (United States)

    Hall, Dorothy K.; Salomonson, Vincent V.; Riggs, George A.; Klein, Andrew G.

    2003-01-01

    Snow and sea ice products, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, flown on the Terra and Aqua satellites, are or will be available through the National Snow and Ice Data Center Distributed Active Archive Center (DAAC). The algorithms that produce the products are automated, thus providing a consistent global data set that is suitable for climate studies. The suite of MODIS snow products begins with a 500-m resolution, 2330-km swath snow-cover map that is then projected onto a sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to daily and 8-day composite climate-modeling grid (CMG) products at 0.05 resolution. A daily snow albedo product will be available in early 2003 as a beta test product. The sequence of sea ice products begins with a swath product at 1-km resolution that provides sea ice extent and ice-surface temperature (IST). The sea ice swath products are then mapped onto the Lambert azimuthal equal area or EASE-Grid projection to create a daily and 8-day composite sea ice tile product, also at 1 -km resolution. Climate-Modeling Grid (CMG) sea ice products in the EASE-Grid projection at 4-km resolution are planned for early 2003.

  6. COMPREHENSIVE COMPARISON OF TWO IMAGE-BASED POINT CLOUDS FROM AERIAL PHOTOS WITH AIRBORNE LIDAR FOR LARGE-SCALE MAPPING

    Directory of Open Access Journals (Sweden)

    E. Widyaningrum

    2017-09-01

    Full Text Available The integration of computer vision and photogrammetry to generate three-dimensional (3D information from images has contributed to a wider use of point clouds, for mapping purposes. Large-scale topographic map production requires 3D data with high precision and accuracy to represent the real conditions of the earth surface. Apart from LiDAR point clouds, the image-based matching is also believed to have the ability to generate reliable and detailed point clouds from multiple-view images. In order to examine and analyze possible fusion of LiDAR and image-based matching for large-scale detailed mapping purposes, point clouds are generated by Semi Global Matching (SGM and by Structure from Motion (SfM. In order to conduct comprehensive and fair comparison, this study uses aerial photos and LiDAR data that were acquired at the same time. Qualitative and quantitative assessments have been applied to evaluate LiDAR and image-matching point clouds data in terms of visualization, geometric accuracy, and classification result. The comparison results conclude that LiDAR is the best data for large-scale mapping.

  7. High Resolution Energetic X-ray Imager (HREXI)

    Science.gov (United States)

    Grindlay, Jonathan

    We propose to design and build the first imaging hard X-ray detector system that incorporates 3D stacking of closely packed detector readouts in finely-spaced imaging arrays with their required data processing and control electronics. In virtually all imaging astronomical detectors, detector readout is done with flex connectors or connections that are not vertical but rather horizontal , requiring loss of focal plane area. For high resolution pixel detectors needed for high speed event-based X-ray imaging, from low energy applications (CMOS) with focusing X-ray telescopes, to hard X-ray applications with pixelated CZT for large area coded aperture telescopes, this new detector development offers great promise. We propose to extend our previous and current APRA supported ProtoEXIST program that has developed the first large area imaging CZT detectors and demonstrated their astrophysical capabilities on two successful balloon flight to a next generation High Resolution Energetic X-ray Imager (HREXI), which would incorporate microvia technology for the first time to connect the readout ASIC on each CZT crystal directly to its control and data processing system. This 3-dimensional stacking of detector and readout/control system means that large area (>2m2) imaging detector planes for a High Resolution Wide-field hard X-ray telescope can be built with initially greatly reduced detector gaps and ultimately with no gaps. This increases detector area, efficiency, and simplicity of detector integration. Thus higher sensitivity wide-field imagers will be possible at lower cost. HREXI will enable a post-Swift NASA mission such as the EREXS concept proposed to PCOS to be conducted as a future MIDEX mission. This mission would conduct a high resolution (<2 arcmin) , broad band (5 200 keV) hard X-ray survey of black holes on all scales with ~10X higher sensitivity than Swift. In the current era of Time Domain Astrophysics, such a survey capability, in conjunction with a n

  8. Image quality assessment for selfies with and without super resolution

    Science.gov (United States)

    Kubota, Aya; Gohshi, Seiichi

    2018-04-01

    With the advent of cellphone cameras, in particular, on smartphones, many people now take photos of themselves alone and with others in the frame; such photos are popularly known as "selfies". Most smartphones are equipped with two cameras: the front-facing and rear cameras. The camera located on the back of the smartphone is referred to as the "out-camera," whereas the one located on the front of the smartphone is called the "in-camera." In-cameras are mainly used for selfies. Some smartphones feature high-resolution cameras. However, the original image quality cannot be obtained because smartphone cameras often have low-performance lenses. Super resolution (SR) is one of the recent technological advancements that has increased image resolution. We developed a new SR technology that can be processed on smartphones. Smartphones with new SR technology are currently available in the market have already registered sales. However, the effective use of new SR technology has not yet been verified. Comparing the image quality with and without SR on smartphone display is necessary to confirm the usefulness of this new technology. Methods that are based on objective and subjective assessments are required to quantitatively measure image quality. It is known that the typical object assessment value, such as Peak Signal to Noise Ratio (PSNR), does not go together with how we feel when we assess image/video. When digital broadcast started, the standard was determined using subjective assessment. Although subjective assessment usually comes at high cost because of personnel expenses for observers, the results are highly reproducible when they are conducted under right conditions and statistical analysis. In this study, the subjective assessment results for selfie images are reported.

  9. Three very high resolution optical images for land use mapping of a suburban catchment: input to distributed hydrological models

    Science.gov (United States)

    Jacqueminet, Christine; Kermadi, Saïda; Michel, Kristell; Jankowfsky, Sonja; Braud, Isabelle; Branger, Flora; Beal, David; Gagnage, Matthieu

    2010-05-01

    Keywords : land cover mapping, very high resolution, remote sensing processing techniques, object oriented approach, distributed hydrological model, peri-urban area Urbanization and other modifications of land use affect the hydrological cycle of suburban catchments. In order to quantify these impacts, the AVuPUR project (Assessing the Vulnerability of Peri-Urban Rivers) is currently developing a distributed hydrological model that includes anthropogenic features. The case study is the Yzeron catchment (150 km²), located close to Lyon city, France. This catchment experiences a growing of urbanization and a modification of traditional land use since the middle of the 20th century, resulting in an increase of flooding, water pollution and river banks erosion. This contribution discusses the potentials of automated data processing techniques on three different VHR images, in order to produce appropriate and detailed land cover data for the models. Of particular interest is the identification of impermeable surfaces (buildings, roads, and parking places) and permeable surfaces (forest areas, agricultural fields, gardens, trees…) within the catchment, because their infiltration capacity and their impact on runoff generation are different. Three aerial and spatial images were acquired: (1) BD Ortho IGN aerial images, 0.50 m resolution, visible bands, may 5th 2008; (2) QuickBird satellite image, 2.44 m resolution, visible and near-infrared bands, august 29th 2008; (3) Spot satellite image, 2.50 m resolution, visible and near-infrared bands, September 22nd 2008. From these images, we developed three image processing methods: (1) a pixel-based method associated to a segmentation using Matlab®, (2) a pixel-based method using ENVI®, (3) an object-based classification using Definiens®. We extracted six land cover types from the BD Ortho IGN (visible bands) and height classes from the satellite images (visible and near infrared bands). The three classified images are

  10. High resolution imaging of surface patterns of single bacterial cells

    International Nuclear Information System (INIS)

    Greif, Dominik; Wesner, Daniel; Regtmeier, Jan; Anselmetti, Dario

    2010-01-01

    We systematically studied the origin of surface patterns observed on single Sinorhizobium meliloti bacterial cells by comparing the complementary techniques atomic force microscopy (AFM) and scanning electron microscopy (SEM). Conditions ranged from living bacteria in liquid to fixed bacteria in high vacuum. Stepwise, we applied different sample modifications (fixation, drying, metal coating, etc.) and characterized the observed surface patterns. A detailed analysis revealed that the surface structure with wrinkled protrusions in SEM images were not generated de novo but most likely evolved from similar and naturally present structures on the surface of living bacteria. The influence of osmotic stress to the surface structure of living cells was evaluated and also the contribution of exopolysaccharide and lipopolysaccharide (LPS) by imaging two mutant strains of the bacterium under native conditions. AFM images of living bacteria in culture medium exhibited surface structures of the size of single proteins emphasizing the usefulness of AFM for high resolution cell imaging.

  11. High-resolution imaging in the scanning transmission electron microscope

    International Nuclear Information System (INIS)

    Pennycook, S.J.; Jesson, D.E.

    1992-03-01

    The high-resolution imaging of crystalline materials in the scanning transmission electron microscopy (STEM) is reviewed with particular emphasis on the conditions under which an incoherent image can be obtained. It is shown that a high-angle annular detector can be used to break the coherence of the imaging process, in the transverse plane through the geometry of the detector, or in three dimensions if multiphonon diffuse scattering is detected. In the latter case, each atom can be treated as a highly independent source of high-angle scattering. The most effective fast electron states are therefore tightly bound s-type Bloch states. Furthermore, they add constructively for each incident angle in the coherent STEM probe, so that s states are responsible for practically the entire image contrast. Dynamical effects are largely removed, and almost perfect incoherent imaging is achieved. s states are relatively insensitive to neighboring strings, so that incoherent imaging is maintained for superlattice and interfaces, and supercell calculations are unnecessary. With an optimum probe profile, the incoherent image represents a direct image of the crystal projection, with compositional sensitivity built in through the strong dependence of the scattering cross sections on atomic number Z

  12. High resolution X radiography imaging detector-micro gap chamber

    International Nuclear Information System (INIS)

    Long Huqiang; Wang Yun; Xu Dong; Xie Kuanzhong; Bian Jianjiang

    2007-01-01

    Micro gap chamber (MGC) is a new type of Two-Dimensional position sensitive detector having excellent properties on the space and time resolution, counting rate, 2D compact structure and the flexible of application. It will become a candidate of a new tracking detector for high energy physics experiment. The basic structure and properties of MGC as well as its main research subjects are presented in this paper. Furthermore, the feasibility and validity of utilizing diamond films as the MGC gap material were also discussed in detail. So, a potential radiography imaging detector is provided in order to realize X image and X ray diffraction experiment having very good spatial and time resolution in the 3rd Generation of Synchrotron Radiation Facility. (authors)

  13. Collection and Analysis of Crowd Data with Aerial, Rooftop, and Ground Views

    Science.gov (United States)

    2014-11-10

    collected these datasets using different aircrafts. Erista 8 HL OctaCopter is a heavy-lift aerial platform capable of using high-resolution cinema ...is another high-resolution camera that is cinema grade and high quality, with the capability of capturing videos with 4K resolution at 30 frames per...292.58 Imaging Systems and Accessories Blackmagic Production Camera 4 Crowd Counting using 4K Cameras High resolution cinema grade digital video

  14. Precision crystal alignment for high-resolution electron microscope imaging

    International Nuclear Information System (INIS)

    Wood, G.J.; Beeching, M.J.

    1990-01-01

    One of the more difficult tasks involved in obtaining quality high-resolution electron micrographs is the precise alignment of a specimen into the required zone. The current accepted procedure, which involves changing to diffraction mode and searching for symmetric point diffraction pattern, is insensitive to small amounts of misalignment and at best qualitative. On-line analysis of the fourier space representation of the image, both for determining and correcting crystal tilt, is investigated. 8 refs., 42 figs

  15. High-Resolution Imaging of Colliding and Merging Galaxies

    Science.gov (United States)

    Whitmore, Brad

    1991-07-01

    We propose to obtain high-resolution images, using the WF/PC, of two colliding and merging galaxies (i.e., NGC 4038/4039 = "The Antennae" and NGC 7252 ="Atoms-for-Peace Galaxy". Our goal is to use HST to make critical observations of each object in order to gain a better understanding of the various phases of the merger process. Our primary objective is to determine whether globular clusters are formed during mergers\\?

  16. High resolution microphotonic needle for endoscopic imaging (Conference Presentation)

    Science.gov (United States)

    Tadayon, Mohammad Amin; Mohanty, Aseema; Roberts, Samantha P.; Barbosa, Felippe; Lipson, Michal

    2017-02-01

    GRIN (Graded index) lens have revolutionized micro endoscopy enabling deep tissue imaging with high resolution. The challenges of traditional GRIN lenses are their large size (when compared with the field of view) and their limited resolution. This is because of the relatively weak NA in standard graded index lenses. Here we introduce a novel micro-needle platform for endoscopy with much higher resolution than traditional GRIN lenses and a FOV that corresponds to the whole cross section of the needle. The platform is based on polymeric (SU-8) waveguide integrated with a microlens micro fabricated on a silicon substrate using a unique molding process. Due to the high index of refraction of the material the NA of the needle is much higher than traditional GRIN lenses. We tested the probe in a fluorescent dye solution (19.6 µM Alexa Flour 647 solution) and measured a numerical aperture of 0.25, focal length of about 175 µm and minimal spot size of about 1.6 µm. We show that the platform can image a sample with the field of view corresponding to the cross sectional area of the waveguide (80x100 µm2). The waveguide size can in principle be modified to vary size of the imaging field of view. This demonstration, combined with our previous work demonstrating our ability to implant the high NA needle in a live animal, shows that the proposed system can be used for deep tissue imaging with very high resolution and high field of view.

  17. Image Quality in High-resolution and High-cadence Solar Imaging

    Science.gov (United States)

    Denker, C.; Dineva, E.; Balthasar, H.; Verma, M.; Kuckein, C.; Diercke, A.; González Manrique, S. J.

    2018-03-01

    Broad-band imaging and even imaging with a moderate bandpass (about 1 nm) provides a photon-rich environment, where frame selection (lucky imaging) becomes a helpful tool in image restoration, allowing us to perform a cost-benefit analysis on how to design observing sequences for imaging with high spatial resolution in combination with real-time correction provided by an adaptive optics (AO) system. This study presents high-cadence (160 Hz) G-band and blue continuum image sequences obtained with the High-resolution Fast Imager (HiFI) at the 1.5-meter GREGOR solar telescope, where the speckle-masking technique is used to restore images with nearly diffraction-limited resolution. The HiFI employs two synchronized large-format and high-cadence sCMOS detectors. The median filter gradient similarity (MFGS) image-quality metric is applied, among others, to AO-corrected image sequences of a pore and a small sunspot observed on 2017 June 4 and 5. A small region of interest, which was selected for fast-imaging performance, covered these contrast-rich features and their neighborhood, which were part of Active Region NOAA 12661. Modifications of the MFGS algorithm uncover the field- and structure-dependency of this image-quality metric. However, MFGS still remains a good choice for determining image quality without a priori knowledge, which is an important characteristic when classifying the huge number of high-resolution images contained in data archives. In addition, this investigation demonstrates that a fast cadence and millisecond exposure times are still insufficient to reach the coherence time of daytime seeing. Nonetheless, the analysis shows that data acquisition rates exceeding 50 Hz are required to capture a substantial fraction of the best seeing moments, significantly boosting the performance of post-facto image restoration.

  18. Monitoring of Antarctic moss ecosystems using a high spatial resolution imaging spectroscopy

    Science.gov (United States)

    Malenovsky, Zbynek; Lucieer, Arko; Robinson, Sharon; Harwin, Stephen; Turner, Darren; Veness, Tony

    2013-04-01

    controlled by the composition and content of various foliar pigments (chlorophylls, xanthophylls, etc.). Additionally, the high spectral resolution reflectance together with the narrow bandwidth allows retrieving the steady state chlorophyll fluorescence, which indicates the actual moss photosynthetic activity. A first airborne imaging spectroscopy acquisition with the mini-Hyperspec sensor on-board a low-flying remote-controlled multi-rotor helicopter (known as micro Unmanned Aerial Systems - UAS) will be performed during the summer 2013. The aim of the UAS observations is to generate high spatial resolution maps of actual physiological state of several moss beds located within the Australian Antarctic Territory. The regular airborne monitoring is expected to reveal spatio-temporal changes in the Antarctic moss ecosystems, indicating the impact of the global climate change in Antarctica.

  19. Retrospective farm scale spatial analysis of viticultural terroir fertility using a 70 y-aerial photograph time series, soil survey and very high resolution Pléiades and EM38 data

    Science.gov (United States)

    Vaudour, Emmanuelle; Leclercq, Léa; Gilliot, Jean-Marc; Chaignon, Benoît

    2016-04-01

    In order to elaborate adequate and sustainable practices while better controlling harvest composition at farm scale, the detailed spatial assessment of terroir units is needed. Although such assessment is made in the present time, it reflects vine behaviour and soil quality according to cumulated past choices in vineyard management. in addition to demarcate homogeneous within-vineyard zones, there is a need, in cases where the winegrower starts up its activities, to retrace the behaviour of these zones in the past, so as to consolidate the diagnosis of vine fertility, and determine further adoption of new soil and vineyard management practices that are likely to favour a long-term preservation of quality production together with soil ecosystem functions. In this study we aimed at performing such historical and spatial tracing using a long term time-series of aerial survey images, in combination with a set of very high resolution data: resistivity EM38 measurements and very high resolution Pléiades satellite images. This study was conducted over a 6 ha-farm mainly planted with rainfed black Grenache and Syrah varieties in the Southern Rhone Valley. In a previous study carried out at regional scale, soil landscape and potential terroir units had been characterized. A new field survey carried out in January 2015 considered a total of 98 topsoil sampling sites in addition to 14 soil pits, the horizons of which were described and sampled. Physico-chemical analyses were made for all soil samples, and for those horizons having the highest root development, additional analytical parameters such as copper, active lime and mineral nutrients contents were determined. Along with soil parameters, soil surface condition, vine biological parameters including vigour, presence of diseases, stock-unearthing were collected. A total of 25 aerial photographs in digitized format from the French National Institute of Geographic and Forest Information (IGN) were examined over the 1947

  20. Use of Aerial high resolution visible imagery to produce large river bathymetry: a multi temporal and spatial study over the by-passed Upper Rhine

    Science.gov (United States)

    Béal, D.; Piégay, H.; Arnaud, F.; Rollet, A.; Schmitt, L.

    2011-12-01

    Aerial high resolution visible imagery allows producing large river bathymetry assuming that water depth is related to water colour (Beer-Bouguer-Lambert law). In this paper we aim at monitoring Rhine River geometry changes for a diachronic study as well as sediment transport after an artificial injection (25.000 m3 restoration operation). For that a consequent data base of ground measurements of river depth is used, built on 3 different sources: (i) differential GPS acquisitions, (ii) sounder data and (iii) lateral profiles realized by experts. Water depth is estimated using a multi linear regression over neo channels built on a principal component analysis over red, green and blue bands and previously cited depth data. The study site is a 12 km long reach of the by-passed section of the Rhine River that draws French and German border. This section has been heavily impacted by engineering works during the last two centuries: channelization since 1842 for navigation purposes and the construction of a 45 km long lateral canal and 4 consecutive hydroelectric power plants of since 1932. Several bathymetric models are produced based on 3 different spatial resolutions (6, 13 and 20 cm) and 5 acquisitions (January, March, April, August and October) since 2008. Objectives are to find the optimal spatial resolution and to characterize seasonal effects. Best performances according to the 13 cm resolution show a 18 cm accuracy when suspended matters impacted less water transparency. Discussions are oriented to the monitoring of the artificial reload after 2 flood events during winter 2010-2011. Bathymetric models produced are also useful to build 2D hydraulic model's mesh.

  1. Low drive field amplitude for improved image resolution in magnetic particle imaging.

    Science.gov (United States)

    Croft, Laura R; Goodwill, Patrick W; Konkle, Justin J; Arami, Hamed; Price, Daniel A; Li, Ada X; Saritas, Emine U; Conolly, Steven M

    2016-01-01

    Magnetic particle imaging (MPI) is a new imaging technology that directly detects superparamagnetic iron oxide nanoparticles. The technique has potential medical applications in angiography, cell tracking, and cancer detection. In this paper, the authors explore how nanoparticle relaxation affects image resolution. Historically, researchers have analyzed nanoparticle behavior by studying the time constant of the nanoparticle physical rotation. In contrast, in this paper, the authors focus instead on how the time constant of nanoparticle rotation affects the final image resolution, and this reveals nonobvious conclusions for tailoring MPI imaging parameters for optimal spatial resolution. The authors first extend x-space systems theory to include nanoparticle relaxation. The authors then measure the spatial resolution and relative signal levels in an MPI relaxometer and a 3D MPI imager at multiple drive field amplitudes and frequencies. Finally, these image measurements are used to estimate relaxation times and nanoparticle phase lags. The authors demonstrate that spatial resolution, as measured by full-width at half-maximum, improves at lower drive field amplitudes. The authors further determine that relaxation in MPI can be approximated as a frequency-independent phase lag. These results enable the authors to accurately predict MPI resolution and sensitivity across a wide range of drive field amplitudes and frequencies. To balance resolution, signal-to-noise ratio, specific absorption rate, and magnetostimulation requirements, the drive field can be a low amplitude and high frequency. Continued research into how the MPI drive field affects relaxation and its adverse effects will be crucial for developing new nanoparticles tailored to the unique physics of MPI. Moreover, this theory informs researchers how to design scanning sequences to minimize relaxation-induced blurring for better spatial resolution or to exploit relaxation-induced blurring for MPI with

  2. Spatial scales of pollution from variable resolution satellite imaging.

    Science.gov (United States)

    Chudnovsky, Alexandra A; Kostinski, Alex; Lyapustin, Alexei; Koutrakis, Petros

    2013-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not adequate for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(2.5) as measured by the EPA ground monitoring stations was investigated at varying spatial scales. Our analysis suggested that the correlation between PM(2.5) and AOD decreased significantly as AOD resolution was degraded. This is so despite the intrinsic mismatch between PM(2.5) ground level measurements and AOD vertically integrated measurements. Furthermore, the fine resolution results indicated spatial variability in particle concentration at a sub-10 km scale. Finally, this spatial variability of AOD within the urban domain was shown to depend on PM(2.5) levels and wind speed. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. Effects of scanning resolution and digital image magnification on photostimulable phosphor imaging system

    International Nuclear Information System (INIS)

    Sakurai, Takashi; Inagaki, Masafumi; Asai, Hideomi; Koyama, Atsushi; Kashima, Isamu

    2000-01-01

    The purpose of this study is to examine the effects of changes in scanning resolution and digital magnification on the image quality and diagnostic ability of the photostimulable phosphor imaging system. Using a photostimulable phosphor imaging system, images of a human adult dried mandible phantom embedded in a 25 mm-thick epoxy resin block were made. The latent images on the photostimulable phosphor imaging plate were scanned using four different pixel sizes as follows: 25 μm x 25 μm, 50 μm x 50 μm, 100 μm x 100 μm and 200 μm x 200 μm. A primary image was produced for each pixel size. These images were also digitally magnified at powers of 2, 4 and 8 times. The gradient range, brightness and contrast of each image were adjusted to optimum levels on a cathode ray tube display, and hard copies were produced with a writing pixel size of 60 μm x 60 μm. The granularity, sharpness and anatomical diagnostic ability of the images were assessed subjectively by eight dentists. Increasing the scanning resolution tended to generally improve image quality and diagnostic ability. Visual image quality was maintained up to a pixel size of 50 μm, and diagnostic ability was maintained up to a pixel size of 100 μm. Digital image magnification degraded image quality, and more than 2-times magnification degraded diagnostic ability. Under the present experimental conditions, increasing the scanning resolution did not always lead to an improvement in image quality or diagnostic ability, and digital image magnification degraded image quality and diagnostic ability. (author)

  4. Mapping bare soil in South West Wales, UK, using high resolution colour infra-red aerial photography for water quality and flood risk management applications

    Science.gov (United States)

    Sykes, Helena; Neale, Simon; Coe, Sarah

    2016-04-01

    Natural Resources Wales is a UK government body responsible for environmental regulation, among other areas. River walks in Water Framework Directive (WFD) priority catchments in South West Wales, UK, identified soil entering water courses due to poaching and bank erosion, leading to deterioration in the water quality and jeopardising the water quality meeting legal minimum standards. Bare soil has also been shown to cause quicker and higher hydrograph peaks in rural catchments than if those areas were vegetated, which can lead to flooding of domestic properties during peak storm flows. The aim was to target farm visits by operational staff to advise on practices likely to improve water quality and to identify areas where soft engineering solutions such as revegetation could alleviate flood risk in rural areas. High resolution colour-infrared aerial photography, 25cm in the three colour bands and 50cm in the near infrared band, was used to map bare soil in seven catchments using supervised classification of a five band stack including the Normalised Difference Vegetation Index (NDVI). Mapping was combined with agricultural land use and field boundary data to filter out arable fields, which are supposed to bare soil for part of their cycle, and was very successful when compared to ground truthing, with the exception of silage fields which contained sparse, no or unproductive vegetation at the time the imagery was acquired leading to spectral similarity to bare soil. A raindrop trace model was used to show the path sediment from bare soil areas would take when moving through the catchment to a watercourse, with hedgerows inserted as barriers following our observations from ground truthing. The findings have been used to help farmers gain funding for improvements such as fencing to keep animals away from vulnerable river banks. These efficient and automated methods can be rolled out to more catchments in Wales and updated using aerial imagery acquired more recently to

  5. A Mobile System for Measuring Water Surface Velocities Using Unmanned Aerial Vehicle and Large-Scale Particle Image Velocimetry

    Science.gov (United States)

    Chen, Y. L.

    2015-12-01

    Measurement technologies for velocity of river flow are divided into intrusive and nonintrusive methods. Intrusive method requires infield operations. The measuring process of intrusive methods are time consuming, and likely to cause damages of operator and instrument. Nonintrusive methods require fewer operators and can reduce instrument damages from directly attaching to the flow. Nonintrusive measurements may use radar or image velocimetry to measure the velocities at the surface of water flow. The image velocimetry, such as large scale particle image velocimetry (LSPIV) accesses not only the point velocity but the flow velocities in an area simultaneously. Flow properties of an area hold the promise of providing spatially information of flow fields. This study attempts to construct a mobile system UAV-LSPIV by using an unmanned aerial vehicle (UAV) with LSPIV to measure flows in fields. The mobile system consists of a six-rotor UAV helicopter, a Sony nex5T camera, a gimbal, an image transfer device, a ground station and a remote control device. The activate gimbal helps maintain the camera lens orthogonal to the water surface and reduce the extent of images being distorted. The image transfer device can monitor the captured image instantly. The operator controls the UAV by remote control device through ground station and can achieve the flying data such as flying height and GPS coordinate of UAV. The mobile system was then applied to field experiments. The deviation of velocities measured by UAV-LSPIV of field experiments and handhold Acoustic Doppler Velocimeter (ADV) is under 8%. The results of the field experiments suggests that the application of UAV-LSPIV can be effectively applied to surface flow studies.

  6. High resolution 3D imaging of synchrotron generated microbeams

    Energy Technology Data Exchange (ETDEWEB)

    Gagliardi, Frank M., E-mail: frank.gagliardi@wbrc.org.au [Alfred Health Radiation Oncology, The Alfred, Melbourne, Victoria 3004, Australia and School of Medical Sciences, RMIT University, Bundoora, Victoria 3083 (Australia); Cornelius, Iwan [Imaging and Medical Beamline, Australian Synchrotron, Clayton, Victoria 3168, Australia and Centre for Medical Radiation Physics, University of Wollongong, Wollongong, New South Wales 2500 (Australia); Blencowe, Anton [Division of Health Sciences, School of Pharmacy and Medical Sciences, The University of South Australia, Adelaide, South Australia 5000, Australia and Division of Information Technology, Engineering and the Environment, Mawson Institute, University of South Australia, Mawson Lakes, South Australia 5095 (Australia); Franich, Rick D. [School of Applied Sciences and Health Innovations Research Institute, RMIT University, Melbourne, Victoria 3000 (Australia); Geso, Moshi [School of Medical Sciences, RMIT University, Bundoora, Victoria 3083 (Australia)

    2015-12-15

    Purpose: Microbeam radiation therapy (MRT) techniques are under investigation at synchrotrons worldwide. Favourable outcomes from animal and cell culture studies have proven the efficacy of MRT. The aim of MRT researchers currently is to progress to human clinical trials in the near future. The purpose of this study was to demonstrate the high resolution and 3D imaging of synchrotron generated microbeams in PRESAGE® dosimeters using laser fluorescence confocal microscopy. Methods: Water equivalent PRESAGE® dosimeters were fabricated and irradiated with microbeams on the Imaging and Medical Beamline at the Australian Synchrotron. Microbeam arrays comprised of microbeams 25–50 μm wide with 200 or 400 μm peak-to-peak spacing were delivered as single, cross-fire, multidirectional, and interspersed arrays. Imaging of the dosimeters was performed using a NIKON A1 laser fluorescence confocal microscope. Results: The spatial fractionation of the MRT beams was clearly visible in 2D and up to 9 mm in depth. Individual microbeams were easily resolved with the full width at half maximum of microbeams measured on images with resolutions of as low as 0.09 μm/pixel. Profiles obtained demonstrated the change of the peak-to-valley dose ratio for interspersed MRT microbeam arrays and subtle variations in the sample positioning by the sample stage goniometer were measured. Conclusions: Laser fluorescence confocal microscopy of MRT irradiated PRESAGE® dosimeters has been validated in this study as a high resolution imaging tool for the independent spatial and geometrical verification of MRT beam delivery.

  7. High resolution 3D imaging of synchrotron generated microbeams

    International Nuclear Information System (INIS)

    Gagliardi, Frank M.; Cornelius, Iwan; Blencowe, Anton; Franich, Rick D.; Geso, Moshi

    2015-01-01

    Purpose: Microbeam radiation therapy (MRT) techniques are under investigation at synchrotrons worldwide. Favourable outcomes from animal and cell culture studies have proven the efficacy of MRT. The aim of MRT researchers currently is to progress to human clinical trials in the near future. The purpose of this study was to demonstrate the high resolution and 3D imaging of synchrotron generated microbeams in PRESAGE® dosimeters using laser fluorescence confocal microscopy. Methods: Water equivalent PRESAGE® dosimeters were fabricated and irradiated with microbeams on the Imaging and Medical Beamline at the Australian Synchrotron. Microbeam arrays comprised of microbeams 25–50 μm wide with 200 or 400 μm peak-to-peak spacing were delivered as single, cross-fire, multidirectional, and interspersed arrays. Imaging of the dosimeters was performed using a NIKON A1 laser fluorescence confocal microscope. Results: The spatial fractionation of the MRT beams was clearly visible in 2D and up to 9 mm in depth. Individual microbeams were easily resolved with the full width at half maximum of microbeams measured on images with resolutions of as low as 0.09 μm/pixel. Profiles obtained demonstrated the change of the peak-to-valley dose ratio for interspersed MRT microbeam arrays and subtle variations in the sample positioning by the sample stage goniometer were measured. Conclusions: Laser fluorescence confocal microscopy of MRT irradiated PRESAGE® dosimeters has been validated in this study as a high resolution imaging tool for the independent spatial and geometrical verification of MRT beam delivery

  8. Special issue on high-resolution optical imaging

    Science.gov (United States)

    Smith, Peter J. S.; Davis, Ilan; Galbraith, Catherine G.; Stemmer, Andreas

    2013-09-01

    The pace of development in the field of advanced microscopy is truly breath-taking, and is leading to major breakthroughs in our understanding of molecular machines and cell function. This special issue of Journal of Optics draws attention to a number of interesting approaches, ranging from fluorescence and imaging of unlabelled cells, to computational methods, all of which are describing the ever increasing detail of the dynamic behaviour of molecules in the living cell. This is a field which traditionally, and currently, demonstrates a marvellous interplay between the disciplines of physics, chemistry and biology, where apparent boundaries to resolution dissolve and living cells are viewed in ever more clarity. It is fertile ground for those interested in optics and non-conventional imaging to contribute high-impact outputs in the fields of cell biology and biomedicine. The series of articles presented here has been selected to demonstrate this interdisciplinarity and to encourage all those with a background in the physical sciences to 'dip their toes' into the exciting and dynamic discoveries surrounding cell function. Although single molecule super-resolution microscopy is commercially available, specimen preparation and interpretation of single molecule data remain a major challenge for scientists wanting to adopt the techniques. The paper by Allen and Davidson [1] provides a much needed detailed introduction to the practical aspects of stochastic optical reconstruction microscopy, including sample preparation, image acquisition and image analysis, as well as a brief description of the different variants of single molecule localization microscopy. Since super-resolution microscopy is no longer restricted to three-dimensional imaging of fixed samples, the review by Fiolka [2] is a timely introduction to techniques that have been successfully applied to four-dimensional live cell super-resolution microscopy. The combination of multiple high-resolution techniques

  9. Quantifying volume loss from ice cliffs on debris-covered glaciers using high-resolution terrestrial and aerial photogrammetry

    NARCIS (Netherlands)

    Brun, Fanny; Buri, Pascal; Miles, Evan S.; Wagnon, Patrick; Steiner, J.F.; Berthier, Etienne; Ragettli, S.; Kraaijenbrink, P.D.A.; Immerzeel, W.W.; Pellicciotti, Francesca

    Mass losses originating from supraglacial ice cliffs at the lower tongues of debris-covered glaciers are a potentially large component of the mass balance, but have rarely been quantified. In this study, we develop a method to estimate ice cliff volume losses based on high-resolution topographic

  10. Imaging collagen type I fibrillogenesis with high spatiotemporal resolution

    International Nuclear Information System (INIS)

    Stamov, Dimitar R; Stock, Erik; Franz, Clemens M; Jähnke, Torsten; Haschke, Heiko

    2015-01-01

    Fibrillar collagens, such as collagen type I, belong to the most abundant extracellular matrix proteins and they have received much attention over the last five decades due to their large interactome, complex hierarchical structure and high mechanical stability. Nevertheless, the collagen self-assembly process is still incompletely understood. Determining the real-time kinetics of collagen type I formation is therefore pivotal for better understanding of collagen type I structure and function, but visualising the dynamic self-assembly process of collagen I on the molecular scale requires imaging techniques offering high spatiotemporal resolution. Fast and high-speed scanning atomic force microscopes (AFM) provide the means to study such processes on the timescale of seconds under near-physiological conditions. In this study we have applied fast AFM tip scanning to study the assembly kinetics of fibrillar collagen type I nanomatrices with a temporal resolution reaching eight seconds for a frame size of 500 nm. By modifying the buffer composition and pH value, the kinetics of collagen fibrillogenesis can be adjusted for optimal analysis by fast AFM scanning. We furthermore show that amplitude-modulation imaging can be successfully applied to extract additional structural information from collagen samples even at high scan rates. Fast AFM scanning with controlled amplitude modulation therefore provides a versatile platform for studying dynamic collagen self-assembly processes at high resolution. - Highlights: • Continuous non-invasive time-lapse investigation of collagen I fibrillogenesis in situ. • Imaging of collagen I self-assembly with high spatiotemporal resolution. • Application of setpoint modulation to study the hierarchical structure of collagen I. • Observing real-time formation of the D-banding pattern in collagen I

  11. Imaging collagen type I fibrillogenesis with high spatiotemporal resolution

    Energy Technology Data Exchange (ETDEWEB)

    Stamov, Dimitar R, E-mail: stamov@jpk.com [JPK Instruments AG, Bouchéstrasse 12, 12435 Berlin (Germany); Stock, Erik [JPK Instruments AG, Bouchéstrasse 12, 12435 Berlin (Germany); Franz, Clemens M [DFG-Center for Functional Nanostructures (CFN), Karlsruhe Institute of Technology (KIT), Wolfgang-Gaede-Strasse 1a, 76131 Karlsruhe (Germany); Jähnke, Torsten; Haschke, Heiko [JPK Instruments AG, Bouchéstrasse 12, 12435 Berlin (Germany)

    2015-02-15

    Fibrillar collagens, such as collagen type I, belong to the most abundant extracellular matrix proteins and they have received much attention over the last five decades due to their large interactome, complex hierarchical structure and high mechanical stability. Nevertheless, the collagen self-assembly process is still incompletely understood. Determining the real-time kinetics of collagen type I formation is therefore pivotal for better understanding of collagen type I structure and function, but visualising the dynamic self-assembly process of collagen I on the molecular scale requires imaging techniques offering high spatiotemporal resolution. Fast and high-speed scanning atomic force microscopes (AFM) provide the means to study such processes on the timescale of seconds under near-physiological conditions. In this study we have applied fast AFM tip scanning to study the assembly kinetics of fibrillar collagen type I nanomatrices with a temporal resolution reaching eight seconds for a frame size of 500 nm. By modifying the buffer composition and pH value, the kinetics of collagen fibrillogenesis can be adjusted for optimal analysis by fast AFM scanning. We furthermore show that amplitude-modulation imaging can be successfully applied to extract additional structural information from collagen samples even at high scan rates. Fast AFM scanning with controlled amplitude modulation therefore provides a versatile platform for studying dynamic collagen self-assembly processes at high resolution. - Highlights: • Continuous non-invasive time-lapse investigation of collagen I fibrillogenesis in situ. • Imaging of collagen I self-assembly with high spatiotemporal resolution. • Application of setpoint modulation to study the hierarchical structure of collagen I. • Observing real-time formation of the D-banding pattern in collagen I.

  12. Multi-stage classification method oriented to aerial image based on low-rank recovery and multi-feature fusion sparse representation.

    Science.gov (United States)

    Ma, Xu; Cheng, Yongmei; Hao, Shuai

    2016-12-10

    Automatic classification of terrain surfaces from an aerial image is essential for an autonomous unmanned aerial vehicle (UAV) landing at an unprepared site by using vision. Diverse terrain surfaces may show similar spectral properties due to the illumination and noise that easily cause poor classification performance. To address this issue, a multi-stage classification algorithm based on low-rank recovery and multi-feature fusion sparse representation is proposed. First, color moments and Gabor texture feature are extracted from training data and stacked as column vectors of a dictionary. Then we perform low-rank matrix recovery for the dictionary by using augmented Lagrange multipliers and construct a multi-stage terrain classifier. Experimental results on an aerial map database that we prepared verify the classification accuracy and robustness of the proposed method.

  13. DETECTION OF BARCHAN DUNES IN HIGH RESOLUTION SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    M. A. Azzaoui

    2016-06-01

    Full Text Available Barchan dunes are the fastest moving sand dunes in the desert. We developed a process to detect barchans dunes on High resolution satellite images. It consisted of three steps, we first enhanced the image using histogram equalization and noise reduction filters. Then, the second step proceeds to eliminate the parts of the image having a texture different from that of the barchans dunes. Using supervised learning, we tested a coarse to fine textural analysis based on Kolomogorov Smirnov test and Youden’s J-statistic on co-occurrence matrix. As an output we obtained a mask that we used in the next step to reduce the search area. In the third step we used a gliding window on the mask and check SURF features with SVM to get barchans dunes candidates. Detected barchans dunes were considered as the fusion of overlapping candidates. The results of this approach were very satisfying in processing time and precision.

  14. Evaluation of remote sensing aerial systems in existing transportation practices, phase II.

    Science.gov (United States)

    2011-06-01

    A low-cost aerial platform represents a flexible tool for acquiring high-resolution images for ground areas of interest. The geo-referencing of objects within these images could benefit civil engineers in a variety of research areas including, but no...

  15. Photo-magnetic imaging: resolving optical contrast at MRI resolution

    International Nuclear Information System (INIS)

    Lin Yuting; Thayer, David; Luk, Alex L; Gulsen, Gultekin; Gao Hao

    2013-01-01

    In this paper, we establish the mathematical framework of a novel imaging technique, namely photo-magnetic imaging (PMI). PMI uses a laser to illuminate biological tissues and measure the induced temperature variations using magnetic resonance imaging (MRI). PMI overcomes the limitation of conventional optical imaging and allows imaging of the optical contrast at MRI spatial resolution. The image reconstruction for PMI, using a finite-element-based algorithm with an iterative approach, is presented in this paper. The quantitative accuracy of PMI is investigated for various inclusion sizes, depths and absorption values. Then, a comparison between conventional diffuse optical tomography (DOT) and PMI is carried out to illustrate the superior performance of PMI. An example is presented showing that two 2 mm diameter inclusions embedded 4.5 mm deep and located side by side in a 25 mm diameter circular geometry medium are recovered as a single 6 mm diameter object with DOT. However, these two objects are not only effectively resolved with PMI, but their true concentrations are also recovered successfully. (paper)

  16. Aerial Photography and Imagery, Uncorrected - images.DBO.NSB2004COLOR

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Ortho Photography collected as part of the New Smyrna Beach LiDAR collection project. True color, 1 Foot pixel resolution, horizontal accuracies less than 2 Feet....

  17. High Resolution Depth-Resolved Imaging From Multi-Focal Images for Medical Ultrasound

    DEFF Research Database (Denmark)

    Diamantis, Konstantinos; Dalgarno, Paul A.; Greenaway, Alan H.

    2015-01-01

    An ultrasound imaging technique providing subdiffraction limit axial resolution for point sources is proposed. It is based on simultaneously acquired multi-focal images of the same object, and on the image metric of sharpness. The sharpness is extracted by image data and presents higher values...... calibration curves combined with the use of a maximum-likelihood algorithm is then able to estimate, with high precision, the depth location of any emitter fron each single image. Estimated values are compared with the ground truth demonstrating that an accuracy of 28.6 µm (0.13λ) is achieved for a 4 mm depth...

  18. High-resolution mapping based on an Unmanned Aerial Vehicle (UAV) to capture paleoseismic offsets along the Altyn-Tagh fault, China.

    Science.gov (United States)

    Gao, Mingxing; Xu, Xiwei; Klinger, Yann; van der Woerd, Jerome; Tapponnier, Paul

    2017-08-15

    The recent dramatic increase in millimeter- to centimeter- resolution topographic datasets obtained via multi-view photogrammetry raises the possibility of mapping detailed offset geomorphology and constraining the spatial characteristics of active faults. Here, for the first time, we applied this new method to acquire high-resolution imagery and generate topographic data along the Altyn Tagh fault, which is located in a remote high elevation area and shows preserved ancient earthquake surface ruptures. A digital elevation model (DEM) with a resolution of 0.065 m and an orthophoto with a resolution of 0.016 m were generated from these images. We identified piercing markers and reconstructed offsets based on both the orthoimage and the topography. The high-resolution UAV data were used to accurately measure the recent seismic offset. We obtained the recent offset of 7 ± 1 m. Combined with the high resolution satellite image, we measured cumulative offsets of 15 ± 2 m, 20 ± 2 m, 30 ± 2 m, which may be due to multiple paleo-earthquakes. Therefore, UAV mapping can provide fine-scale data for the assessment of the seismic hazards.

  19. Nanometric depth resolution from multi-focal images in microscopy.

    Science.gov (United States)

    Dalgarno, Heather I C; Dalgarno, Paul A; Dada, Adetunmise C; Towers, Catherine E; Gibson, Gavin J; Parton, Richard M; Davis, Ilan; Warburton, Richard J; Greenaway, Alan H

    2011-07-06

    We describe a method for tracking the position of small features in three dimensions from images recorded on a standard microscope with an inexpensive attachment between the microscope and the camera. The depth-measurement accuracy of this method is tested experimentally on a wide-field, inverted microscope and is shown to give approximately 8 nm depth resolution, over a specimen depth of approximately 6 µm, when using a 12-bit charge-coupled device (CCD) camera and very bright but unresolved particles. To assess low-flux limitations a theoretical model is used to derive an analytical expression for the minimum variance bound. The approximations used in the analytical treatment are tested using numerical simulations. It is concluded that approximately 14 nm depth resolution is achievable with flux levels available when tracking fluorescent sources in three dimensions in live-cell biology and that the method is suitable for three-dimensional photo-activated localization microscopy resolution. Sub-nanometre resolution could be achieved with photon-counting techniques at high flux levels.

  20. A high-resolution full-field range imaging system

    Science.gov (United States)

    Carnegie, D. A.; Cree, M. J.; Dorrington, A. A.

    2005-08-01

    There exist a number of applications where the range to all objects in a field of view needs to be obtained. Specific examples include obstacle avoidance for autonomous mobile robots, process automation in assembly factories, surface profiling for shape analysis, and surveying. Ranging systems can be typically characterized as being either laser scanning systems where a laser point is sequentially scanned over a scene or a full-field acquisition where the range to every point in the image is simultaneously obtained. The former offers advantages in terms of range resolution, while the latter tend to be faster and involve no moving parts. We present a system for determining the range to any object within a camera's field of view, at the speed of a full-field system and the range resolution of some point laser scans. Initial results obtained have a centimeter range resolution for a 10 second acquisition time. Modifications to the existing system are discussed that should provide faster results with submillimeter resolution.

  1. Atomic-Resolution Spectrum Imaging of Semiconductor Nanowires.

    Science.gov (United States)

    Zamani, Reza R; Hage, Fredrik S; Lehmann, Sebastian; Ramasse, Quentin M; Dick, Kimberly A

    2018-03-14

    Over the past decade, III-V heterostructure nanowires have attracted a surge of attention for their application in novel semiconductor devices such as tunneling field-effect transistors (TFETs). The functionality of such devices critically depends on the specific atomic arrangement at the semiconductor heterointerfaces. However, most of the currently available characterization techniques lack sufficient spatial resolution to provide local information on the atomic structure and composition of these interfaces. Atomic-resolution spectrum imaging by means of electron energy-loss spectroscopy (EELS) in the scanning transmission electron microscope (STEM) is a powerful technique with the potential to resolve structure and chemical composition with sub-angstrom spatial resolution and to provide localized information about the physical properties of the material at the atomic scale. Here, we demonstrate the use of atomic-resolution EELS to understand the interface atomic arrangement in three-dimensional heterostructures in semiconductor nanowires. We observed that the radial interfaces of GaSb-InAs heterostructure nanowires are atomically abrupt, while the axial interface in contrast consists of an interfacial region where intermixing of the two compounds occurs over an extended spatial region. The local atomic configuration affects the band alignment at the interface and, hence, the charge transport properties of devices such as GaSb-InAs nanowire TFETs. STEM-EELS thus represents a very promising technique for understanding nanowire physical properties, such as differing electrical behavior across the radial and axial heterointerfaces of GaSb-InAs nanowires for TFET applications.

  2. MUSIC electromagnetic imaging with enhanced resolution for small inclusions

    International Nuclear Information System (INIS)

    Chen Xudong; Zhong Yu

    2009-01-01

    This paper investigates the influence of the test dipole on the resolution of the multiple signal classification (MUSIC) imaging method applied to the electromagnetic inverse scattering problem of determining the locations of a collection of small objects embedded in a known background medium. Based on the analysis of the induced electric dipoles in eigenstates, an algorithm is proposed to determine the test dipole that generates a pseudo-spectrum with enhanced resolution. The amplitudes in three directions of the optimal test dipole are not necessarily in phase, i.e., the optimal test dipole may not correspond to a physical direction in the real three-dimensional space. In addition, the proposed test-dipole-searching algorithm is able to deal with some special scenarios, due to the shapes and materials of objects, to which the standard MUSIC does not apply

  3. High temporal resolution functional MRI using parallel echo volumar imaging

    International Nuclear Information System (INIS)

    Rabrait, C.; Ciuciu, P.; Ribes, A.; Poupon, C.; Dehaine-Lambertz, G.; LeBihan, D.; Lethimonnier, F.; Le Roux, P.; Dehaine-Lambertz, G.

    2008-01-01

    Purpose: To combine parallel imaging with 3D single-shot acquisition (echo volumar imaging, EVI) in order to acquire high temporal resolution volumar functional MRI (fMRI) data. Materials and Methods: An improved EVI sequence was associated with parallel acquisition and field of view reduction in order to acquire a large brain volume in 200 msec. Temporal stability and functional sensitivity were increased through optimization of all imaging parameters and Tikhonov regularization of parallel reconstruction. Two human volunteers were scanned with parallel EVI in a 1.5 T whole-body MR system, while submitted to a slow event-related auditory paradigm. Results: Thanks to parallel acquisition, the EVI volumes display a low level of geometric distortions and signal losses. After removal of low-frequency drifts and physiological artifacts,activations were detected in the temporal lobes of both volunteers and voxel-wise hemodynamic response functions (HRF) could be computed. On these HRF different habituation behaviors in response to sentence repetition could be identified. Conclusion: This work demonstrates the feasibility of high temporal resolution 3D fMRI with parallel EVI. Combined with advanced estimation tools,this acquisition method should prove useful to measure neural activity timing differences or study the nonlinearities and non-stationarities of the BOLD response. (authors)

  4. Multi-example feature-constrained back-projection method for image super-resolution

    Institute of Scientific and Technical Information of China (English)

    Junlei Zhang; Dianguang Gai; Xin Zhang; Xuemei Li

    2017-01-01

    Example-based super-resolution algorithms,which predict unknown high-resolution image information using a relationship model learnt from known high- and low-resolution image pairs, have attracted considerable interest in the field of image processing. In this paper, we propose a multi-example feature-constrained back-projection method for image super-resolution. Firstly, we take advantage of a feature-constrained polynomial interpolation method to enlarge the low-resolution image. Next, we consider low-frequency images of different resolutions to provide an example pair. Then, we use adaptive k NN search to find similar patches in the low-resolution image for every image patch in the high-resolution low-frequency image, leading to a regression model between similar patches to be learnt. The learnt model is applied to the low-resolution high-frequency image to produce high-resolution high-frequency information. An iterative back-projection algorithm is used as the final step to determine the final high-resolution image.Experimental results demonstrate that our method improves the visual quality of the high-resolution image.

  5. Precision cosmology with time delay lenses: high resolution imaging requirements

    Energy Technology Data Exchange (ETDEWEB)

    Meng, Xiao-Lei; Liao, Kai [Department of Astronomy, Beijing Normal University, 19 Xinjiekouwai Street, Beijing, 100875 (China); Treu, Tommaso; Agnello, Adriano [Department of Physics, University of California, Broida Hall, Santa Barbara, CA 93106 (United States); Auger, Matthew W. [Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA (United Kingdom); Marshall, Philip J., E-mail: xlmeng919@gmail.com, E-mail: tt@astro.ucla.edu, E-mail: aagnello@physics.ucsb.edu, E-mail: mauger@ast.cam.ac.uk, E-mail: liaokai@mail.bnu.edu.cn, E-mail: dr.phil.marshall@gmail.com [Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, 452 Lomita Mall, Stanford, CA 94305 (United States)

    2015-09-01

    Lens time delays are a powerful probe of cosmology, provided that the gravitational potential of the main deflector can be modeled with sufficient precision. Recent work has shown that this can be achieved by detailed modeling of the host galaxies of lensed quasars, which appear as ''Einstein Rings'' in high resolution images. The distortion of these arcs and counter-arcs, as measured over a large number of pixels, provides tight constraints on the difference between the gravitational potential between the quasar image positions, and thus on cosmology in combination with the measured time delay. We carry out a systematic exploration of the high resolution imaging required to exploit the thousands of lensed quasars that will be discovered by current and upcoming surveys with the next decade. Specifically, we simulate realistic lens systems as imaged by the Hubble Space Telescope (HST), James Webb Space Telescope (JWST), and ground based adaptive optics images taken with Keck or the Thirty Meter Telescope (TMT). We compare the performance of these pointed observations with that of images taken by the Euclid (VIS), Wide-Field Infrared Survey Telescope (WFIRST) and Large Synoptic Survey Telescope (LSST) surveys. We use as our metric the precision with which the slope γ' of the total mass density profile ρ{sub tot}∝ r{sup −γ'} for the main deflector can be measured. Ideally, we require that the statistical error on γ' be less than 0.02, such that it is subdominant to other sources of random and systematic uncertainties. We find that survey data will likely have sufficient depth and resolution to meet the target only for the brighter gravitational lens systems, comparable to those discovered by the SDSS survey. For fainter systems, that will be discovered by current and future surveys, targeted follow-up will be required. However, the exposure time required with upcoming facilitites such as JWST, the Keck Next Generation

  6. Precision cosmology with time delay lenses: High resolution imaging requirements

    Energy Technology Data Exchange (ETDEWEB)

    Meng, Xiao -Lei [Beijing Normal Univ., Beijing (China); Univ. of California, Santa Barbara, CA (United States); Treu, Tommaso [Univ. of California, Santa Barbara, CA (United States); Univ. of California, Los Angeles, CA (United States); Agnello, Adriano [Univ. of California, Santa Barbara, CA (United States); Univ. of California, Los Angeles, CA (United States); Auger, Matthew W. [Univ. of Cambridge, Cambridge (United Kingdom); Liao, Kai [Beijing Normal Univ., Beijing (China); Univ. of California, Santa Barbara, CA (United States); Univ. of California, Los Angeles, CA (United States); Marshall, Philip J. [Stanford Univ., Stanford, CA (United States)

    2015-09-28

    Lens time delays are a powerful probe of cosmology, provided that the gravitational potential of the main deflector can be modeled with sufficient precision. Recent work has shown that this can be achieved by detailed modeling of the host galaxies of lensed quasars, which appear as ``Einstein Rings'' in high resolution images. The distortion of these arcs and counter-arcs, as measured over a large number of pixels, provides tight constraints on the difference between the gravitational potential between the quasar image positions, and thus on cosmology in combination with the measured time delay. We carry out a systematic exploration of the high resolution imaging required to exploit the thousands of lensed quasars that will be discovered by current and upcoming surveys with the next decade. Specifically, we simulate realistic lens systems as imaged by the Hubble Space Telescope (HST), James Webb Space Telescope (JWST), and ground based adaptive optics images taken with Keck or the Thirty Meter Telescope (TMT). We compare the performance of these pointed observations with that of images taken by the Euclid (VIS), Wide-Field Infrared Survey Telescope (WFIRST) and Large Synoptic Survey Telescope (LSST) surveys. We use as our metric the precision with which the slope γ' of the total mass density profile ρtot∝ r–γ' for the main deflector can be measured. Ideally, we require that the statistical error on γ' be less than 0.02, such that it is subdominant to other sources of random and systematic uncertainties. We find that survey data will likely have sufficient depth and resolution to meet the target only for the brighter gravitational lens systems, comparable to those discovered by the SDSS survey. For fainter systems, that will be discovered by current and future surveys, targeted follow-up will be required. Furthermore, the exposure time required with upcoming facilitites such as JWST, the Keck Next Generation Adaptive

  7. A mechanical microcompressor for high resolution imaging of motile specimens.

    Science.gov (United States)

    Zinskie, Jessica A; Shribak, Michael; Bruist, Michael F; Aufderheide, Karl J; Janetopoulos, Chris

    2015-10-01

    In order to obtain fine details in 3 dimensions (3D) over time, it is critical for motile biological specimens to be appropriately immobilized. Of the many immobilization options available, the mechanical microcompressor offers many benefits. Our device, previously described, achieves gentle flattening of a cell, allowing us to image finely detailed structures of numerous organelles and physiological processes in living cells. We have imaged protozoa and other small metazoans using differential interference contrast (DIC) microscopy, orientation-independent (OI) DIC, and real-time birefringence imaging using a video-enhanced polychromatic polscope. We also describe an enhancement of our previous design by engineering a new device where the coverslip mount is fashioned onto the top of the base; so the entire apparatus is accessible on top of the stage. The new location allows for easier manipulation of the mount when compressing or releasing a specimen on an inverted microscope. Using this improved design, we imaged immobilized bacteria, yeast, paramecia, and nematode worms and obtained an unprecedented view of cell and specimen details. A variety of microscopic techniques were used to obtain high resolution images of static and dynamic cellular and physiological events. Copyright © 2015 Elsevier Inc. All rights reserved.

  8. Exploration of mineral resource deposits based on analysis of aerial and satellite image data employing artificial intelligence methods

    Science.gov (United States)

    Osipov, Gennady

    2013-04-01

    includes noncontact registration of eye motion, reconstruction of "attention landscape" fixed by the expert, recording the comments of the expert who is a specialist in the field of images` interpretation, and transfer this information into knowledge base.Creation of base of ophthalmologic images (OI) includes making semantic contacts from great number of OI based on analysis of OI and expert's comments.Processing of OI and making generalized OI (GOI) is realized by inductive logic algorithms and consists in synthesis of structural invariants of OI. The mode of recognition and interpretation of unknown images consists of several stages, which include: comparison of unknown image with the base of structural invariants of OI; revealing of structural invariants in unknown images; ynthesis of interpretive message of the structural invariants base and OI base (the experts` comments stored in it). We want to emphasize that the training mode does not assume special involvement of experts to teach the system - it is realized in the process of regular experts` work on image interpretation and it becomes possible after installation of a special apparatus for non contact registration of experts` attention. Consequently, the technology, which principles is described there, provides fundamentally new effective solution to the problem of exploration of mineral resource deposits based on computer analysis of aerial and satellite image data.

  9. Mapping of Polar Areas Based on High-Resolution Satellite Images: The Example of the Henryk Arctowski Polish Antarctic Station

    Science.gov (United States)

    Kurczyński, Zdzisław; Różycki, Sebastian; Bylina, Paweł

    2017-12-01

    To produce orthophotomaps or digital elevation models, the most commonly used method is photogrammetric measurement. However, the use of aerial images is not easy in polar regions for logistical reasons. In these areas, remote sensing data acquired from satellite systems is much more useful. This paper presents the basic technical requirements of different products which can be obtain (in particular orthoimages and digital elevation model (DEM)) using Very-High-Resolution Satellite (VHRS) images. The study area was situated in the vicinity of the Henryk Arctowski Polish Antarctic Station on the Western Shore of Admiralty Bay, King George Island, Western Antarctic. Image processing was applied on two triplets of images acquired by the Pléiades 1A and 1B in March 2013. The results of the generation of orthoimages from the Pléiades systems without control points showed that the proposed method can achieve Root Mean Squared Error (RMSE) of 3-9 m. The presented Pléiades images are useful for thematic remote sensing analysis and processing of measurements. Using satellite images to produce remote sensing products for polar regions is highly beneficial and reliable and compares well with more expensive airborne photographs or field surveys.

  10. MATCHING AERIAL IMAGES TO 3D BUILDING MODELS BASED ON CONTEXT-BASED GEOMETRIC HASHING

    Directory of Open Access Journals (Sweden)

    J. Jung

    2016-06-01

    Full Text Available In this paper, a new model-to-image framework to automatically align a single airborne image with existing 3D building models using geometric hashing is proposed. As a prerequisite process for various applications such as data fusion, object tracking, change detection and texture mapping, the proposed registration method is used for determining accurate exterior orientation parameters (EOPs of a single image. This model-to-image matching process consists of three steps: 1 feature extraction, 2 similarity measure and matching, and 3 adjustment of EOPs of a single image. For feature extraction, we proposed two types of matching cues, edged corner points representing the saliency of building corner points with associated edges and contextual relations among the edged corner points within an individual roof. These matching features are extracted from both 3D building and a single airborne image. A set of matched corners are found with given proximity measure through geometric hashing and optimal matches are then finally determined by maximizing the matching cost encoding contextual similarity between matching candidates. Final matched corners are used for adjusting EOPs of the single airborne image by the least square method based on co-linearity equations. The result shows that acceptable accuracy of single image's EOP can be achievable by the proposed registration approach as an alternative to labour-intensive manual registration process.

  11. Waveguide image-slicers for ultrahigh resolution spectroscopy

    Science.gov (United States)

    Beckert, Erik; Strassmeier, Klaus G.; Woche, Manfred; Eberhardt, Ramona; Tünnermann, Andreas; Andersen, Michael

    2008-07-01

    Waveguide image-slicer prototypes with resolutions up to 310.000 for the fiber fed PEPSI echelle spectrograph at the LBT and single waveguide thicknesses of down to 30 μm have been manufactured. The waveguides were macroscopically prepared, stacked up to an order of 7 and thinned back to square stack cross sections. A high filling ratio was achieved by realizing homogenous adhesive gaps of 4.6 μm, using index matching adhesives for TIR within the waveguides. The image-slicer stacks can be used in immersion mode and are miniaturized to be implemented in a set of four, measurements indicate an overall efficiency of above 80% for them.

  12. Multi-resolution waveguide image slicer for the PEPSI instrument

    Science.gov (United States)

    Beckert, Erik; Strassmeier, Klaus G.; Woche, Manfred; Harnisch, Gerd; Hornaff, Marcel; Weber, Michael; Barnes, Stuart

    2016-07-01

    A waveguide image slicer with resolutions up to 270.000 (planned: 300.000) for the fiber fed PEPSI echelle spectrograph at the LBT and single waveguide thicknesses of down to 70 μm has been manufactured and tested. The waveguides were macroscopically prepared, stacked up to an order of seven and thinned back to square stack cross sections. A high filling ratio was achieved by realizing homogenous adhesive gaps of 3.6 μm, using index matching adhesives for TIR within the waveguides. The image slicer stacks are used in immersion mode and are miniaturized to enable implementation in a set of 2x8. The overall efficiency is between 92 % and 96 %.

  13. Porous silicon phantoms for high-resolution scintillation imaging

    Energy Technology Data Exchange (ETDEWEB)

    Di Francia, G. [Portici Research Centre, ENEA, Via Vecchio Macello, 80055 Portici, Naples (Italy); Scafe, R. [Casaccia Research Centre, ENEA, 00060 S.Maria di Galeria, Rome (Italy)]. E-mail: scafe@casaccia.enea.it; De Vincentis, G. [Department of Radiological Sciences, University of Rome ' La Sapienza' , V.le Regina Elena, 324, 00161 Rome (Italy); La Ferrara, V. [Portici Research Centre, ENEA, Via Vecchio Macello, 80055 Portici, Naples (Italy); Iurlaro, G. [Casaccia Research Centre, ENEA, 00060 S.Maria di Galeria, Rome (Italy); Nasti, I. [Portici Research Centre, ENEA, Via Vecchio Macello, 80055 Portici, Naples (Italy); Montani, L. [Casaccia Research Centre, ENEA, 00060 S.Maria di Galeria, Rome (Italy); Pellegrini, R. [Department of Experimental Medicine, University of Rome ' La Sapienza' , V.le Regina Elena, 324, 00161 Rome (Italy); Betti, M. [Department of Experimental Medicine, University of Rome ' La Sapienza' , V.le Regina Elena, 324, 00161 Rome (Italy); Martucciello, N. [Portici Research Centre, ENEA, Via Vecchio Macello, 80055 Portici, Naples (Italy); Pani, R. [Department of Experimental Medicine, University of Rome ' La Sapienza' , V.le Regina Elena, 324, 00161 Rome (Italy)

    2006-12-20

    High resolution radionuclide imaging requires phantoms with precise geometries and known activities using either Anger cameras equipped with pinhole collimators or dedicated small animal devices. Porous silicon samples, having areas of different shape and size, can be made and loaded with a radioactive material, obtaining: (a) precise radio-emitting figures corresponding to the porous areas geometry (b) a radioactivity of each figure depending on the pore's specifications, and (c) the same emission energy to be used in true exams. To this aim a sample with porous circular areas has been made and loaded with a {sup 99m}TcO{sub 4} {sup -} solution. Imaging has been obtained using both general purpose and pinhole collimators. This first sample shows some defects that are analyzed and discussed.

  14. Chandra High Resolution Imaging of NGC 1365 and NGC 4151

    Science.gov (United States)

    Wang, Junfeng; Fabbiano, G.; Elvis, M.; Risaliti, G.; Karovska, M.; Zezas, A.; Mazzarella, J. M.; Lord, S.; Howell, J. H.; Mundell, C. G.

    2010-07-01

    We present Chandra high resolution imaging of the circumnuclear regions of two nearby active galaxies, namely the starburst/AGN composite Seyfert 1.8 NGC 1365 and the archetypal Seyfert 1 NGC 4151. In NGC 1365, the X-ray morphology shows a biconical soft X-ray-emission region extending ~5 kpc in projection from the nucleus, coincident with the optical high-excitation outflows. Chandra HRC imaging of the NGC 4151 nucleus resolves X-ray emission from the 4 arcsec radio jet and the narrow line region (NLR) clouds. Our results demonstrate the unique power of spatially resolved spectroscopy with Chandra, and support previous claims that frequent jet-ISM interaction may explain why jets in Seyfert galaxies appear small, slow, and thermally dominated.

  15. High-resolution flow imaging of the carotid arteries

    International Nuclear Information System (INIS)

    Masaryk, T.J.; Modic, M.T.; Haacke, E.M.; Lenz, G.W.; Ross, J.S.

    1986-01-01

    Recently, high-contrast vascular images have been demonstrated using short TEs, gating and subtraction. However, to obtain short TE values, large gradients are required. This potentially limits the field of view, signal-to-noise- ratio, and resolution. Furthermore, gating in different parts of the cardiac cycle can lead to pixel misregistration. In this study, additional refocusing gradients were applied so that no velocity-dependent dephasing occurs at the echo restoring signal from moving blood. Two cardiac-gated sequences using the same trigger delay and one acquisition were obtained. Preliminary results indicate that good quality vascular images of the carotid bifurcation can be obtained with modifications of the spin-echo technique of with short TEs utilizing a gradient echo technique

  16. High-resolution imaging of solar system objects

    International Nuclear Information System (INIS)

    Goldberg, B.A.

    1988-01-01

    The strategy of this investigation has been to develop new high-resolution imaging capabilities and to apply them to extended observing programs. These programs have included Io's neutral sodium cloud and comets. The Io observing program was carried out at Table Mountain Observatory (1976 to 1981), providing a framework interpreting Voyager measurements of the Io torus, and serving as an important reference for studying asymmetries and time variabilities in the Jovian magnetosphere. Comet observations made with the 3.6 m Canada-France-Hawaii Telescope and 1.6 m AMOS telescope (1984 to 1987) provide basis for studying early coma development in Halley, the kinematics of its nucleus, and the internal and external structure of the nucleus. Images of GZ from the ICE encounter period form the basis for unique comparisons with in situ magnetic field and dust impact measurements to determine the ion tail and dust coma structure, respectively

  17. Weed mapping in early-season maize fields using object-based analysis of unmanned aerial vehicle (UAV) images.

    Science.gov (United States)

    Peña, José Manuel; Torres-Sánchez, Jorge; de Castro, Ana Isabel; Kelly, Maggi; López-Granados, Francisca

    2013-01-01

    The use of remote imagery captured by unmanned aerial vehicles (UAV) has tremendous potential for designing detailed site-specific weed control treatments in early post-emergence, which have not possible previously with conventional airborne or satellite images. A robust and entirely automatic object-based image analysis (OBIA) procedure was developed on a series of UAV images using a six-band multispectral camera (visible and near-infrared range) with the ultimate objective of generating a weed map in an experimental maize field in Spain. The OBIA procedure combines several contextual, hierarchical and object-based features and consists of three consecutive phases: 1) classification of crop rows by application of a dynamic and auto-adaptive classification approach, 2) discrimination of crops and weeds on the basis of their relative positions with reference to the crop rows, and 3) generation of a weed infestation map in a grid structure. The estimation of weed coverage from the image analysis yielded satisfactory results. The relationship of estimated versus observed weed densities had a coefficient of determination of r(2)=0.89 and a root mean square error of 0.02. A map of three categories of weed coverage was produced with 86% of overall accuracy. In the experimental field, the area free of weeds was 23%, and the area with low weed coverage (weeds) was 47%, which indicated a high potential for reducing herbicide application or other weed operations. The OBIA procedure computes multiple data and statistics derived from the classification outputs, which permits calculation of herbicide requirements and estimation of the overall cost of weed management operations in advance.

  18. Application of two-dimensional crystallography and image processing to atomic resolution Z-contrast images.

    Science.gov (United States)

    Morgan, David G; Ramasse, Quentin M; Browning, Nigel D

    2009-06-01

    Zone axis images recorded using high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM or Z-contrast imaging) reveal the atomic structure with a resolution that is defined by the probe size of the microscope. In most cases, the full images contain many sub-images of the crystal unit cell and/or interface structure. Thanks to the repetitive nature of these images, it is possible to apply standard image processing techniques that have been developed for the electron crystallography of biological macromolecules and have been used widely in other fields of electron microscopy for both organic and inorganic materials. These methods can be used to enhance the signal-to-noise present in the original images, to remove distortions in the images that arise from either the instrumentation or the specimen itself and to quantify properties of the material in ways that are difficult without such data processing. In this paper, we describe briefly the theory behind these image processing techniques and demonstrate them for aberration-corrected, high-resolution HAADF-STEM images of Si(46) clathrates developed for hydrogen storage.

  19. Fast Aerial Video Stitching

    Directory of Open Access Journals (Sweden)

    Jing Li

    2014-10-01

    Full Text Available The highly efficient and robust stitching of aerial video captured by unmanned aerial vehicles (UAVs is a challenging problem in the field of robot vision. Existing commercial image stitching systems have seen success with offline stitching tasks, but they cannot guarantee high-speed performance when dealing with online aerial video sequences. In this paper, we present a novel system which has an unique ability to stitch high-frame rate aerial video at a speed of 150 frames per second (FPS. In addition, rather than using a high-speed vision platform such as FPGA or CUDA, our system is running on a normal personal computer. To achieve this, after the careful comparison of the existing invariant features, we choose the FAST corner and binary descriptor for efficient feature extraction and representation, and present a spatial and temporal coherent filter to fuse the UAV motion information into the feature matching. The proposed filter can remove the majority of feature correspondence outliers and significantly increase the speed of robust feature matching by up to 20 times. To achieve a balance between robustness and efficiency, a dynamic key frame-based stitching framework is used to reduce the accumulation errors. Extensive experiments on challenging UAV datasets demonstrate that our approach can break through the speed limitation and generate an accurate stitching image for aerial video stitching tasks.

  20. Multiple speckle illumination for optical-resolution photoacoustic imaging

    Science.gov (United States)

    Poisson, Florian; Stasio, Nicolino; Moser, Christophe; Psaltis, Demetri; Bossy, Emmanuel

    2017-03-01

    Optical-resolution photoacoustic microscopy offers exquisite and specific contrast to optical absorption. Conventional approaches generally involves raster scanning a focused spot over the sample. Here, we demonstrate that a full-field illumination approach with multiple speckle illumination can also provide diffraction-limited optical-resolution photoacoustic images. Two different proof-of-concepts are demonstrated with micro-structured test samples. The first approach follows the principle of correlation/ghost imaging,1, 2 and is based on cross-correlating photoacoustic signals under multiple speckle illumination with known speckle patterns measured during a calibration step. The second approach is a speckle scanning microscopy technique, which adapts the technique proposed in fluorescence microscopy by Bertolotti and al.:3 in our work, spatially unresolved photoacoustic measurements are performed for various translations of unknown speckle patterns. A phase-retrieval algorithm is used to reconstruct the object from the knowledge of the modulus of its Fourier Transform yielded by the measurements. Because speckle patterns naturally appear in many various situations, including propagation through biological tissue or multi-mode fibers (for which focusing light is either very demanding if not impossible), speckle-illumination-based photoacoustic microscopy provides a powerful framework for the development of novel reconstruction approaches, well-suited to compressed sensing approaches.2

  1. D Surface Generation from Aerial Thermal Imagery

    Science.gov (United States)

    Khodaei, B.; Samadzadegan, F.; Dadras Javan, F.; Hasani, H.

    2015-12-01

    Aerial thermal imagery has been recently applied to quantitative analysis of several scenes. For the mapping purpose based on aerial thermal imagery, high accuracy photogrammetric process is necessary. However, due to low geometric resolution and low contrast of thermal imaging sensors, there are some challenges in precise 3D measurement of objects. In this paper the potential of thermal video in 3D surface generation is evaluated. In the pre-processing step, thermal camera is geometrically calibrated using a calibration grid based on emissivity differences between the background and the targets. Then, Digital Surface Model (DSM) generation from thermal video imagery is performed in four steps. Initially, frames are extracted from video, then tie points are generated by Scale-Invariant Feature Transform (SIFT) algorithm. Bundle adjustment is then applied and the camera position and orientation parameters are determined. Finally, multi-resolution dense image matching algorithm is used to create 3D point cloud of the scene. Potential of the proposed method is evaluated based on thermal imaging cover an industrial area. The thermal camera has 640×480 Uncooled Focal Plane Array (UFPA) sensor, equipped with a 25 mm lens which mounted in the Unmanned Aerial Vehicle (UAV). The obtained results show the comparable accuracy of 3D model generated based on thermal images with respect to DSM generated from visible images, however thermal based DSM is somehow smoother with lower level of texture. Comparing the generated DSM with the 9 measured GCPs in the area shows the Root Mean Square Error (RMSE) value is smaller than 5 decimetres in both X and Y directions and 1.6 meters for the Z direction.

  2. Overcoming Registration Uncertainty in Image Super-Resolution: Maximize or Marginalize?

    Directory of Open Access Journals (Sweden)

    Andrew Zisserman

    2007-01-01

    Full Text Available In multiple-image super-resolution, a high-resolution image is estimated from a number of lower-resolution images. This usually involves computing the parameters of a generative imaging model (such as geometric and photometric registration, and blur and obtaining a MAP estimate by minimizing a cost function including an appropriate prior. Two alternative approaches are examined. First, both registrations and the super-resolution image are found simultaneously using a joint MAP optimization. Second, we perform Bayesian integration over the unknown image registration parameters, deriving a cost function whose only variables of interest are the pixel values of the super-resolution image. We also introduce a scheme to learn the parameters of the image prior as part of the super-resolution algorithm. We show examples on a number of real sequences including multiple stills, digital video, and DVDs of movies.

  3. Matching Aerial Images to 3D Building Models Using Context-Based Geometric Hashing

    Directory of Open Access Journals (Sweden)

    Jaewook Jung

    2016-06-01

    Full Text Available A city is a dynamic entity, which environment is continuously changing over time. Accordingly, its virtual city models also need to be regularly updated to support accurate model-based decisions for various applications, including urban planning, emergency response and autonomous navigation. A concept of continuous city modeling is to progressively reconstruct city models by accommodating their changes recognized in spatio-temporal domain, while preserving unchanged structures. A first critical step for continuous city modeling is to coherently register remotely sensed data taken at different epochs with existing building models. This paper presents a new model-to-image registration method using a context-based geometric hashing (CGH method to align a single image with existing 3D building models. This model-to-image registration process consists of three steps: (1 feature extraction; (2 similarity measure; and matching, and (3 estimating exterior orientation parameters (EOPs of a single image. For feature extraction, we propose two types of matching cues: edged corner features representing the saliency of building corner points with associated edges, and contextual relations among the edged corner features within an individual roof. A set of matched corners are found with given proximity measure through geometric hashing, and optimal matches are then finally determined by maximizing the matching cost encoding contextual similarity between matching candidates. Final matched corners are used for adjusting EOPs of the single airborne image by the least square method based on collinearity equations. The result shows that acceptable accuracy of EOPs of a single image can be achievable using the proposed registration approach as an alternative to a labor-intensive manual registration process.

  4. Using an Unmanned Aerial Vehicle-Based Digital Imaging System to Derive a 3D Point Cloud for Landslide Scarp Recognition

    Directory of Open Access Journals (Sweden)

    Abdulla Al-Rawabdeh

    2016-01-01

    Full Text Available Landslides often cause economic losses, property damage, and loss of lives. Monitoring landslides using high spatial and temporal resolution imagery and the ability to quickly identify landslide regions are the basis for emergency disaster management. This study presents a comprehensive system that uses unmanned aerial vehicles (UAVs and Semi-Global dense Matching (SGM techniques to identify and extract landslide scarp data. The selected study area is located along a major highway in a mountainous region in Jordan, and contains creeping landslides induced by heavy rainfall. Field observations across the slope body and a deformation analysis along the highway and existing gabions indicate that the slope is active and that scarp features across the slope will continue to open and develop new tension crack features, leading to the downward movement of rocks. The identification of landslide scarps in this study was performed via a dense 3D point cloud of topographic information generated from high-resolution images captured using a low-cost UAV and a target-based camera calibration procedure for a low-cost large-field-of-view camera. An automated approach was used to accurately detect and extract the landslide head scarps based on geomorphological factors: the ratio of normalized Eigenvalues (i.e., λ1/λ2 ≥ λ3 derived using principal component analysis, topographic surface roughness index values, and local-neighborhood slope measurements from the 3D image-based point cloud. Validation of the results was performed using root mean square error analysis and a confusion (error matrix between manually digitized landslide scarps and the automated approaches. The experimental results using the fully automated 3D point-based analysis algorithms show that these approaches can effectively distinguish landslide scarps. The proposed algorithms can accurately identify and extract landslide scarps with centimeter-scale accuracy. In addition, the combination

  5. High Resolution 3D Radar Imaging of Comet Interiors

    Science.gov (United States)

    Asphaug, E. I.; Gim, Y.; Belton, M.; Brophy, J.; Weissman, P. R.; Heggy, E.

    2012-12-01

    Knowing the interiors of comets and other primitive bodies is fundamental to our understanding of how planets formed. We have developed a Discovery-class mission formulation, Comet Radar Explorer (CORE), based on the use of previously flown planetary radar sounding techniques, with the goal of obtaining high resolution 3D images of the interior of a small primitive body. We focus on the Jupiter-Family Comets (JFCs) as these are among the most primitive bodies reachable by spacecraft. Scattered in from far beyond Neptune, they are ultimate targets of a cryogenic sample return mission according to the Decadal Survey. Other suitable targets include primitive NEOs, Main Belt Comets, and Jupiter Trojans. The approach is optimal for small icy bodies ~3-20 km diameter with spin periods faster than about 12 hours, since (a) navigation is relatively easy, (b) radar penetration is global for decameter wavelengths, and (c) repeated overlapping ground tracks are obtained. The science mission can be as short as ~1 month for a fast-rotating JFC. Bodies smaller than ~1 km can be globally imaged, but the navigation solutions are less accurate and the relative resolution is coarse. Larger comets are more interesting, but radar signal is unlikely to be reflected from depths greater than ~10 km. So, JFCs are excellent targets for a variety of reasons. We furthermore focus on the use of Solar Electric Propulsion (SEP) to rendezvous shortly after the comet's perihelion. This approach leaves us with ample power for science operations under dormant conditions beyond ~2-3 AU. This leads to a natural mission approach of distant observation, followed by closer inspection, terminated by a dedicated radar mapping orbit. Radar reflections are obtained from a polar orbit about the icy nucleus, which spins underneath. Echoes are obtained from a sounder operating at dual frequencies 5 and 15 MHz, with 1 and 10 MHz bandwidths respectively. The dense network of echoes is used to obtain global 3D

  6. Interaction of image noise, spatial resolution, and low contrast fine detail preservation in digital image processing

    Science.gov (United States)

    Artmann, Uwe; Wueller, Dietmar

    2009-01-01

    We present a method to improve the validity of noise and resolution measurements on digital cameras. If non-linear adaptive noise reduction is part of the signal processing in the camera, the measurement results for image noise and spatial resolution can be good, while the image quality is low due to the loss of fine details and a watercolor like appearance of the image. To improve the correlation between objective measurement and subjective image quality we propose to supplement the standard test methods with an additional measurement of the texture preserving capabilities of the camera. The proposed method uses a test target showing white Gaussian noise. The camera under test reproduces this target and the image is analyzed. We propose to use the kurtosis of the derivative of the image as a metric for the texture preservation of the camera. Kurtosis is a statistical measure for the closeness of a distribution compared to the Gaussian distribution. It can be shown, that the distribution of digital values in the derivative of the image showing the chart becomes the more leptokurtic (increased kurtosis) the stronger the noise reduction has an impact on the image.

  7. An integrated photogrammetric and spatial database management system for producing fully structured data using aerial and remote sensing images.

    Science.gov (United States)

    Ahmadi, Farshid Farnood; Ebadi, Hamid

    2009-01-01

    3D spatial data acquired from aerial and remote sensing images by photogrammetric techniques is one of the most accurate and economic data sources for GIS, map production, and spatial data updating. However, there are still many problems concerning storage, structuring and appropriate management of spatial data obtained using these techniques. According to the capabilities of spatial database management systems (SDBMSs); direct integration of photogrammetric and spatial database management systems can save time and cost of producing and updating digital maps. This integration is accomplished by replacing digital maps with a single spatial database. Applying spatial databases overcomes the problem of managing spatial and attributes data in a coupled approach. This management approach is one of the main problems in GISs for using map products of photogrammetric workstations. Also by the means of these integrated systems, providing structured spatial data, based on OGC (Open GIS Consortium) standards and topological relations between different feature classes, is possible at the time of feature digitizing process. In this paper, the integration of photogrammetric systems and SDBMSs is evaluated. Then, different levels of integration are described. Finally design, implementation and test of a software package called Integrated Photogrammetric and Oracle Spatial Systems (IPOSS) is presented.

  8. An Integrated Photogrammetric and Spatial Database Management System for Producing Fully Structured Data Using Aerial and Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Farshid Farnood Ahmadi

    2009-03-01

    Full Text Available 3D spatial data acquired from aerial and remote sensing images by photogrammetric techniques is one of the most accurate and economic data sources for GIS, map production, and spatial data updating. However, there are still many problems concerning storage, structuring and appropriate management of spatial data obtained using these techniques. According to the capabilities of spatial database management systems (SDBMSs; direct integration of photogrammetric and spatial database management systems can save time and cost of producing and updating digital maps. This integration is accomplished by replacing digital maps with a single spatial database. Applying spatial databases overcomes the problem of managing spatial and attributes data in a coupled approach. This management approach is one of the main problems in GISs for using map products of photogrammetric workstations. Also by the means of these integrated systems, providing structured spatial data, based on OGC (Open GIS Consortium standards and topological relations between different feature classes, is possible at the time of feature digitizing process. In this paper, the integration of photogrammetric systems and SDBMSs is evaluated. Then, different levels of integration are described. Finally design, implementation and test of a software package called Integrated Photogrammetric and Oracle Spatial Systems (IPOSS is presented.

  9. a Spatio-Spectral Camera for High Resolution Hyperspectral Imaging

    Science.gov (United States)

    Livens, S.; Pauly, K.; Baeck, P.; Blommaert, J.; Nuyts, D.; Zender, J.; Delauré, B.

    2017-08-01

    Imaging with a conventional frame camera from a moving remotely piloted aircraft system (RPAS) is by design very inefficient. Less than 1 % of the flying time is used for collecting light. This unused potential can be utilized by an innovative imaging concept, the spatio-spectral camera. The core of the camera is a frame sensor with a large number of hyperspectral filters arranged on the sensor in stepwise lines. It combines the advantages of frame cameras with those of pushbroom cameras. By acquiring images in rapid succession, such a camera can collect detailed hyperspectral information, while retaining the high spatial resolution offered by the sensor. We have developed two versions of a spatio-spectral camera and used them in a variety of conditions. In this paper, we present a summary of three missions with the in-house developed COSI prototype camera (600-900 nm) in the domains of precision agriculture (fungus infection monitoring in experimental wheat plots), horticulture (crop status monitoring to evaluate irrigation management in strawberry fields) and geology (meteorite detection on a grassland field). Additionally, we describe the characteristics of the 2nd generation, commercially available ButterflEYE camera offering extended spectral range (475-925 nm), and we discuss future work.

  10. Structure recognition from high resolution images of ceramic composites

    Energy Technology Data Exchange (ETDEWEB)

    Ushizima, Daniela; Perciano, Talita; Krishnan, Harinarayan; Loring, Burlen; Bale, Hrishikesh; Parkinson, Dilworth; Sethian, James

    2015-01-05

    Fibers provide exceptional strength-to-weight ratio capabilities when woven into ceramic composites, transforming them into materials with exceptional resistance to high temperature, and high strength combined with improved fracture toughness. Microcracks are inevitable when the material is under strain, which can be imaged using synchrotron X-ray computed micro-tomography (mu-CT) for assessment of material mechanical toughness variation. An important part of this analysis is to recognize fibrillar features. This paper presents algorithms for detecting and quantifying composite cracks and fiber breaks from high-resolution image stacks. First, we propose recognition algorithms to identify the different structures of the composite, including matrix cracks and fibers breaks. Second, we introduce our package F3D for fast filtering of large 3D imagery, implemented in OpenCL to take advantage of graphic cards. Results show that our algorithms automatically identify micro-damage and that the GPU-based implementation introduced here takes minutes, being 17x faster than similar tools on a typical image file.

  11. A SPATIO-SPECTRAL CAMERA FOR HIGH RESOLUTION HYPERSPECTRAL IMAGING

    Directory of Open Access Journals (Sweden)

    S. Livens

    2017-08-01

    Full Text Available Imaging with a conventional frame camera from a moving remotely piloted aircraft system (RPAS is by design very inefficient. Less than 1 % of the flying time is used for collecting light. This unused potential can be utilized by an innovative imaging concept, the spatio-spectral camera. The core of the camera is a frame sensor with a large number of hyperspectral filters arranged on the sensor in stepwise lines. It combines the advantages of frame cameras with those of pushbroom cameras. By acquiring images in rapid succession, such a camera can collect detailed hyperspectral information, while retaining the high spatial resolution offered by the sensor. We have developed two versions of a spatio-spectral camera and used them in a variety of conditions. In this paper, we present a summary of three missions with the in-house developed COSI prototype camera (600–900 nm in the domains of precision agriculture (fungus infection monitoring in experimental wheat plots, horticulture (crop status monitoring to evaluate irrigation management in strawberry fields and geology (meteorite detection on a grassland field. Additionally, we describe the characteristics of the 2nd generation, commercially available ButterflEYE camera offering extended spectral range (475–925 nm, and we discuss future work.

  12. Cheetah: A high frame rate, high resolution SWIR image camera

    Science.gov (United States)

    Neys, Joel; Bentell, Jonas; O'Grady, Matt; Vermeiren, Jan; Colin, Thierry; Hooylaerts, Peter; Grietens, Bob

    2008-10-01

    A high resolution, high frame rate InGaAs based image sensor and associated camera has been developed. The sensor and the camera are capable of recording and delivering more than 1700 full 640x512pixel frames per second. The FPA utilizes a low lag CTIA current integrator in each pixel, enabling integration times shorter than one microsecond. On-chip logics allows for four different sub windows to be read out simultaneously at even higher rates. The spectral sensitivity of the FPA is situated in the SWIR range [0.9-1.7 μm] and can be further extended into the Visible and NIR range. The Cheetah camera has max 16 GB of on-board memory to store the acquired images and transfer the data over a Gigabit Ethernet connection to the PC. The camera is also equipped with a full CameralinkTM interface to directly stream the data to a frame grabber or dedicated image processing unit. The Cheetah camera is completely under software control.

  13. Design and development of a very high resolution thermal imager

    Science.gov (United States)

    Kuerbitz, Gunther; Duchateau, Ruediger

    1998-10-01

    The design goal of this project was to develop a thermal imaging system with ultimate geometrical resolution without sacrificing thermal sensitivity. It was necessary to fulfil the criteria for a future advanced video standard. This video standard is the so-called HDTV standard (HDTV High Definition TeleVision). The thermal imaging system is a parallel scanning system working in the 7...11 micrometer spectral region. The detector for that system has to have 576 X n (n number of TDI stages) detector elements taking into account a twofold interlace. It must be carefully optimized in terms of range performance and size of optics entrance pupil as well as producibility and yield. This was done in strong interaction with the detector manufacturer. The 16:9 aspect ratio of the HDTV standard together with the high number of 1920 pixels/line impose high demands on the scanner design in terms of scan efficiency and linearity. As an advanced second generation thermal imager the system has an internal thermal reference. The electronics is fully digitized and comprises circuits for Non Uniformity Correction (NUC), scan conversion, electronic zoom, auto gain and level, edge enhancement, up/down and left/right reversion etc. It can be completely remote-controlled via a serial interface.

  14. Physical properties of shallow landslides and their role in landscape evolution investigated with ultrahigh-resolution lidar data and aerial imagery

    Science.gov (United States)

    Nelson, M. D.; Bryk, A. B.; Fauria, K.; Huang, M. H.; Dietrich, W. E.

    2017-12-01

    Shallow landslides are often a primary method of sediment transport and a dominant process of hillslope evolution in steep, soil-mantled landscapes. However, detailed studies of single landslides can be difficult to generalize across a landscape and watershed-scale analyses using coarse-resolution digital elevation models often fail to capture the detail necessary to understand the mechanics of individual slides. During February 2017, an intense rainfall event generated over 400 shallow landslides within a 13 km2 field site in Colusa County, Northern California, providing a unique opportunity to investigate how landsliding affects landscape morphology at multiple scales. The hilly grass and oak woodland site is underlain by Great Valley Sequence shale, sandstone, and conglomerate turbidites uniformly dipping 50° east, with ridgelines and valleys following bedding orientation. Here we present results from ultrahigh-resolution ( 100 points per square meter) airborne lidar data and aerial imagery collected directly after the event, as well as high-resolution airborne lidar data collected in 2015 and preliminary findings from field surveys. Of the 136 landslides surveyed so far, the failure surface was at the soil-weathered bedrock boundary in 85%. Only 69% of the landslides traveled down hillslopes and reached active channels, and of these, 37% transformed into debris flows that scoured channel pathways to bedrock. These small landslides have a median width of 3.2 m and average failure depth of 0.4 m. Landslides occurred at a median pre-failure ground surface slope of 35°, and only 56% occurred in convergent or weakly convergent areas. This comprehensive before and after dataset is being used as a rigorous test of shallow landslide models that predict landslide size and location, as well as a lens to investigate patterns in slope stability or failure with across the landscape. After multiple years of fieldwork at this study site where small landslide scars suggested

  15. Image processing in aerial surveillance and reconnaissance: From pixels to understanding

    NARCIS (Netherlands)

    Dijk, J.; Eekeren, A.W.M. van; Rajadell Rojas, O.; Burghouts, G.J.; Schutte, K.

    2013-01-01

    Surveillance and reconnaissance tasks are currently often performed using an airborne platform such as a UAV. The airborne platform can carry different sensors. EO/IR cameras can be used to view a certain area from above. To support the task from the sensor analyst, different image processing

  16. Advances in high-resolution imaging--techniques for three-dimensional imaging of cellular structures.

    Science.gov (United States)

    Lidke, Diane S; Lidke, Keith A

    2012-06-01

    A fundamental goal in biology is to determine how cellular organization is coupled to function. To achieve this goal, a better understanding of organelle composition and structure is needed. Although visualization of cellular organelles using fluorescence or electron microscopy (EM) has become a common tool for the cell biologist, recent advances are providing a clearer picture of the cell than ever before. In particular, advanced light-microscopy techniques are achieving resolutions below the diffraction limit and EM tomography provides high-resolution three-dimensional (3D) images of cellular structures. The ability to perform both fluorescence and electron microscopy on the same sample (correlative light and electron microscopy, CLEM) makes it possible to identify where a fluorescently labeled protein is located with respect to organelle structures visualized by EM. Here, we review the current state of the art in 3D biological imaging techniques with a focus on recent advances in electron microscopy and fluorescence super-resolution techniques.

  17. Hyperspatial Thermal Imaging of Surface Hydrothermal Features at Pilgrim Hot Springs, Alaska using a small Unmanned Aerial System (sUAS)

    Science.gov (United States)

    Haselwimmer, C. E.; Wilson, R.; Upton, C.; Prakash, A.; Holdmann, G.; Walker, G.

    2013-12-01

    Thermal remote sensing provides a valuable tool for mapping and monitoring surface hydrothermal features associated with geothermal activity. The increasing availability of low-cost, small Unmanned Aerial Systems (sUAS) with integrated thermal imaging sensors offers a means to undertake very high spatial resolution (hyperspatial), quantitative thermal remote sensing of surface geothermal features in support of exploration and long-term monitoring efforts. Results from the deployment of a quadcopter sUAS equipped with a thermal camera over Pilgrim Hot Springs, Alaska for detailed mapping and heat flux estimation for hot springs, seeps, and thermal pools are presented. Hyperspatial thermal infrared imagery (4 cm pixels) was acquired over Pilgrim Hot Springs in July 2013 using a FLIR TAU 640 camera operating from an Aeryon Scout sUAS flying at an altitude of 40m. The registered and mosaicked thermal imagery is calibrated to surface temperature values using in-situ measurements of uniform blackbody tarps and the temperatures of geothermal and other surface pools acquired with a series of water temperature loggers. Interpretation of the pre-processed thermal imagery enables the delineation of hot springs, the extents of thermal pools, and the flow and mixing of individual geothermal outflow plumes with an unprecedented level of detail. Using the surface temperatures of thermal waters derived from the FLIR data and measured in-situ meteorological parameters the hot spring heat flux and outflow rate is calculated using a heat budget model for a subset of the thermal drainage. The heat flux/outflow rate estimates derived from the FLIR data are compared against in-situ measurements of the hot spring outflow rate recorded at the time of the thermal survey.

  18. Retrieving high-resolution images over the Internet from an anatomical image database

    Science.gov (United States)

    Strupp-Adams, Annette; Henderson, Earl

    1999-12-01

    The Visible Human Data set is an important contribution to the national collection of anatomical images. To enhance the availability of these images, the National Library of Medicine has supported the design and development of a prototype object-oriented image database which imports, stores, and distributes high resolution anatomical images in both pixel and voxel formats. One of the key database modules is its client-server Internet interface. This Web interface provides a query engine with retrieval access to high-resolution anatomical images that range in size from 100KB for browser viewable rendered images, to 1GB for anatomical structures in voxel file formats. The Web query and retrieval client-server system is composed of applet GUIs, servlets, and RMI application modules which communicate with each other to allow users to query for specific anatomical structures, and retrieve image data as well as associated anatomical images from the database. Selected images can be downloaded individually as single files via HTTP or downloaded in batch-mode over the Internet to the user's machine through an applet that uses Netscape's Object Signing mechanism. The image database uses ObjectDesign's object-oriented DBMS, ObjectStore that has a Java interface. The query and retrieval systems has been tested with a Java-CDE window system, and on the x86 architecture using Windows NT 4.0. This paper describes the Java applet client search engine that queries the database; the Java client module that enables users to view anatomical images online; the Java application server interface to the database which organizes data returned to the user, and its distribution engine that allow users to download image files individually and/or in batch-mode.

  19. Evaluation of deep neural networks for single image super-resolution in a maritime context

    NARCIS (Netherlands)

    Nieuwenhuizen, R.P.J.; Kruithof, M.; Schutte, K.

    2017-01-01

    High resolution imagery is of crucial importance for the performance on visual recognition tasks. Super-resolution (SR) reconstruction algorithms aim to enhance the image resolution beyond the capability of the image sensor being used. Traditional SR algorithms approach this inverse problem using

  20. Self-triggered image intensifier tube for high-resolution UHECR imaging detector

    CERN Document Server

    Sasaki, M; Jobashi, M

    2003-01-01

    The authors have developed a self-triggered image intensifier tube with high-resolution imaging capability. An image detected by a first image intensifier tube as an electrostatic lens with a photocathode diameter of 100 mm is separated by a half-mirror into a path for CCD readout (768x494 pixels) and a fast control to recognize and trigger the image. The proposed system provides both a high signal-to-noise ratio to improve single photoelectron detection and excellent spatial resolution between 207 and 240 mu m rendering this device a potentially essential tool for high-energy physics and astrophysics experiments, as well as high-speed photography. When combined with a 1-arcmin resolution optical system with 50 deg. field-of-view proposed by the present authors, the observation of ultra high-energy cosmic rays and high-energy neutrinos using this device is expected, leading to revolutionary progress in particle astrophysics as a complementary technique to traditional astronomical observations at multiple wave...

  1. High resolution LBT imaging of Io and Jupiter

    Science.gov (United States)

    Conrad, A.; de Kleer, K.; Leisenring, J.; La Camera, A.; Arcidiacono, C.; Bertero, M.; Boccacci, P.; Defrère, D.; de Pater, I.; Hinz, P.; Hoffman, K.-H.; Kürster, M.; Rathbun, J.; Schertl, D.; Skemer, A.; Skrutskie, M.; Spencer, J.; Veillet, C.; Weigelt, G.; Woodward, C.

    2015-10-01

    We report here results from observing Io at high angular resolution, ˜32 mas at 4.8 μm, with LBT at two favorable oppositions as described in our report given at the 2011 EPSC [1]. Analysis of datasets acquired during the last two oppositions has yielded spatially resolved M-band emission at Loki Patera [2], L-band fringes at an eruption site, an occultation of Loki and Pele by Europa, and sufficient sub-earth longitude (SEL) and parallactic angle coverage to produce a full disk map.We summarize completed results for the first of these, and give brief progress reports for the latter three. Finally, we provide plans for imaging the full disk of Jupiter using the MCAO system which is in its commissioning phase at LBT.

  2. Spatial resolution enhancement of satellite image data using fusion approach

    Science.gov (United States)

    Lestiana, H.; Sukristiyanti

    2018-02-01

    Object identification using remote sensing data has a problem when the spatial resolution is not in accordance with the object. The fusion approach is one of methods to solve the problem, to improve the object recognition and to increase the objects information by combining data from multiple sensors. The application of fusion image can be used to estimate the environmental component that is needed to monitor in multiple views, such as evapotranspiration estimation, 3D ground-based characterisation, smart city application, urban environments, terrestrial mapping, and water vegetation. Based on fusion application method, the visible object in land area has been easily recognized using the method. The variety of object information in land area has increased the variation of environmental component estimation. The difficulties in recognizing the invisible object like Submarine Groundwater Discharge (SGD), especially in tropical area, might be decreased by the fusion method. The less variation of the object in the sea surface temperature is a challenge to be solved.

  3. High resolution ultrastructure imaging of fractures in human dental tissues

    Directory of Open Access Journals (Sweden)

    Tan Sui

    2014-01-01

    Full Text Available Human dental hard tissues are dentine, cementum, and enamel. These are hydrated mineralised composite tissues with a hierarchical structure and versatile thermo-mechanical properties. The hierarchical structure of dentine and enamel was imaged by transmission electron microscopy (TEM of samples prepared by focused ion beam (FIB milling. High resolution TEM was carried out in the vicinity of a crack tip in dentine. An intricate “random weave” pattern of hydroxyapatile crystallites was observed and this provided a possible explanation for toughening of the mineralized dentine tissue at the nano-scale. The results reported here provide the basis for improved understanding of the relationship between the multi-scale nature and the mechanical properties of hierarchically structured biomaterials, and will also be useful for the development of better prosthetic and dental restorative materials.

  4. Aerial Photography and Imagery, Ortho-Corrected, Leaf-on September 2004 0.5m resolution RGB orthoimagery that covers Connecticut's coastal communities. Data were collected by Earth Data, under contract to NOAA, using a Leica ADS40 sensor., Published in 2004, University of Connecticut.

    Data.gov (United States)

    NSGIC Education | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2004. Leaf-on September 2004 0.5m resolution RGB orthoimagery that covers Connecticut's coastal...

  5. Aerial Photography and Imagery, Ortho-Corrected, Leaf-on September 2004 0.5m resolution CIR orthoimagery that covers Connecticut's coastal communities. Data were collected by Earth Data, under contract to NOAA, using a Leica ADS40 sensor., Published in 2004, University of Connecticut.

    Data.gov (United States)

    NSGIC Education | GIS Inventory — Aerial Photography and Imagery, Ortho-Corrected dataset current as of 2004. Leaf-on September 2004 0.5m resolution CIR orthoimagery that covers Connecticut's coastal...

  6. Single photon imaging at ultra-high resolution

    Energy Technology Data Exchange (ETDEWEB)

    Bellazzini, R. [INFN sez. Pisa, Pisa (Italy); Spandre, G. [INFN sez. Pisa, Pisa (Italy)], E-mail: Gloria.Spandre@pi.infn.it; Minuti, M.; Brez, A.; Baldini, L.; Latronico, L.; Omodei, N.; Sgro, C.; Bregeon, J.; Razzano, M.; Pinchera, M. [INFN sez. Pisa, Pisa (Italy); Tremsin, A.; McPhate, J.; Vallerga, J.V.; Siegmund, O. [SSL, Berkeley (United States)

    2008-06-11

    We present a detection system capable of imaging both single photon/positive ion and multiple coincidence photons/positive ions with extremely high spatial resolution. In this detector the photoelectrons excited by the incoming photons are multiplied by microchannel plate(s) (MCP). The process of multiplication is spatially constrained within an MCP pore, which can be as small as 4 {mu}m for commercially available MCPs. An electron cloud originated by a single photoelectron is then encoded by a pixellated custom analog ASIC consisting of 105 K charge sensitive pixels of 50 {mu}m in size arranged on a hexagonal grid. Each pixel registers the charge with an accuracy of <100 electrons rms. Computation of the event centroid from the readout charges results in an accurate event position. A large number of simultaneous photons spatially separated by {approx}0.4 mm can be detected simultaneously allowing multiple coincidence operation for the experiments where a large number of incoming photons/positive ions have to be detected simultaneously. The experimental results prove that the spatial resolution of the readout system itself is {approx}3 {mu}m FWHM enabling detection resolution better than 6 {mu}m for the small pore MCPs. An attractive feature of the detection system is its capability to register the timing of each incoming photon/positive ion (in single photon detection mode) or of the first incoming particle (for the multiple coincidence detection) with an accuracy of {approx}130 ps FWHM. There is also virtually no dark count noise in the detection system making it suitable for low count rate applications.

  7. LAKE ICE DETECTION IN LOW-RESOLUTION OPTICAL SATELLITE IMAGES

    Directory of Open Access Journals (Sweden)

    M. Tom

    2018-05-01

    Full Text Available Monitoring and analyzing the (decreasing trends in lake freezing provides important information for climate research. Multi-temporal satellite images are a natural data source to survey ice on lakes. In this paper, we describe a method for lake ice monitoring, which uses low spatial resolution (250 m–1000 m satellite images to determine whether a lake is frozen or not. We report results on four selected lakes in Switzerland: Sihl, Sils, Silvaplana and St. Moritz. These lakes have different properties regarding area, altitude, surrounding topography and freezing frequency, describing cases of medium to high difficulty. Digitized Open Street Map (OSM lake outlines are back-projected on to the image space after generalization. As a pre-processing step, the absolute geolocation error of the lake outlines is corrected by matching the projected outlines to the images. We define the lake ice detection as a two-class (frozen, non-frozen semantic segmentation problem. Several spectral channels of the multi-spectral satellite data are used, both reflective and emissive (thermal. Only the cloud-free (clean pixels which lie completely inside the lake are analyzed. The most useful channels to solve the problem are selected with xgboost and visual analysis of histograms of reference data, while the classification is done with non-linear support vector machine (SVM. We show experimentally that this straight-forward approach works well with both MODIS and VIIRS satellite imagery. Moreover, we show that the algorithm produces consistent results when tested on data from multiple winters.

  8. Lake Ice Detection in Low-Resolution Optical Satellite Images

    Science.gov (United States)

    Tom, M.; Kälin, U.; Sütterlin, M.; Baltsavias, E.; Schindler, K.

    2018-05-01

    Monitoring and analyzing the (decreasing) trends in lake freezing provides important information for climate research. Multi-temporal satellite images are a natural data source to survey ice on lakes. In this paper, we describe a method for lake ice monitoring, which uses low spatial resolution (250 m-1000 m) satellite images to determine whether a lake is frozen or not. We report results on four selected lakes in Switzerland: Sihl, Sils, Silvaplana and St. Moritz. These lakes have different properties regarding area, altitude, surrounding topography and freezing frequency, describing cases of medium to high difficulty. Digitized Open Street Map (OSM) lake outlines are back-projected on to the image space after generalization. As a pre-processing step, the absolute geolocation error of the lake outlines is corrected by matching the projected outlines to the images. We define the lake ice detection as a two-class (frozen, non-frozen) semantic segmentation problem. Several spectral channels of the multi-spectral satellite data are used, both reflective and emissive (thermal). Only the cloud-free (clean) pixels which lie completely inside the lake are analyzed. The most useful channels to solve the problem are selected with xgboost and visual analysis of histograms of reference data, while the classification is done with non-linear support vector machine (SVM). We show experimentally that this straight-forward approach works well with both MODIS and VIIRS satellite imagery. Moreover, we show that the algorithm produces consistent results when tested on data from multiple winters.

  9. Study of fish response using particle image velocimetry and high-speed, high-resolution imaging

    Energy Technology Data Exchange (ETDEWEB)

    Deng, Z. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Richmond, M. C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Mueller, R. P. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Gruensch, G. R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2004-10-01

    Fish swimming has fascinated both engineers and fish biologists for decades. Digital particle image velocimetry (DPIV) and high-speed, high-resolution digital imaging are recently developed analysis tools that can help engineers and biologists better understand how fish respond to turbulent environments. This report details studies to evaluate DPIV. The studies included a review of existing literature on DPIV, preliminary studies to test the feasibility of using DPIV conducted at our Flow Biology Laboratory in Richland, Washington September through December 2003, and applications of high-speed, high-resolution digital imaging with advanced motion analysis to investigations of fish injury mechanisms in turbulent shear flows and bead trajectories in laboratory physical models. Several conclusions were drawn based on these studies, which are summarized as recommendations for proposed research at the end of this report.

  10. AUTOMATIC INTERPRETATION OF HIGH RESOLUTION SAR IMAGES: FIRST RESULTS OF SAR IMAGE SIMULATION FOR SINGLE BUILDINGS

    Directory of Open Access Journals (Sweden)

    J. Tao

    2012-09-01

    Full Text Available Due to the all-weather data acquisition capabilities, high resolution space borne Synthetic Aperture Radar (SAR plays an important role in remote sensing applications like change detection. However, because of the complex geometric mapping of buildings in urban areas, SAR images are often hard to interpret. SAR simulation techniques ease the visual interpretation of SAR images, while fully automatic interpretation is still a challenge. This paper presents a method for supporting the interpretation of high resolution SAR images with simulated radar images using a LiDAR digital surface model (DSM. Line features are extracted from the simulated and real SAR images and used for matching. A single building model is generated from the DSM and used for building recognition in the SAR image. An application for the concept is presented for the city centre of Munich where the comparison of the simulation to the TerraSAR-X data shows a good similarity. Based on the result of simulation and matching, special features (e.g. like double bounce lines, shadow areas etc. can be automatically indicated in SAR image.

  11. Lensless high-resolution photoacoustic imaging scanner for in vivo skin imaging

    Science.gov (United States)

    Ida, Taiichiro; Iwazaki, Hideaki; Omuro, Toshiyuki; Kawaguchi, Yasushi; Tsunoi, Yasuyuki; Kawauchi, Satoko; Sato, Shunichi

    2018-02-01

    We previously launched a high-resolution photoacoustic (PA) imaging scanner based on a unique lensless design for in vivo skin imaging. The design, imaging algorithm and characteristics of the system are described in this paper. Neither an optical lens nor an acoustic lens is used in the system. In the imaging head, four sensor elements are arranged quadrilaterally, and by checking the phase differences for PA waves detected with these four sensors, a set of PA signals only originating from a chromophore located on the sensor center axis is extracted for constructing an image. A phantom study using a carbon fiber showed a depth-independent horizontal resolution of 84.0 ± 3.5 µm, and the scan direction-dependent variation of PA signals was about ± 20%. We then performed imaging of vasculature phantoms: patterns of red ink lines with widths of 100 or 200 μm formed in an acrylic block co-polymer. The patterns were visualized with high contrast, showing the capability for imaging arterioles and venues in the skin. Vasculatures in rat burn models and healthy human skin were also clearly visualized in vivo.

  12. Applications of high lateral and energy resolution imaging XPS with a double hemispherical analyser based spectromicroscope

    International Nuclear Information System (INIS)

    Escher, M.; Winkler, K.; Renault, O.; Barrett, N.

    2010-01-01

    The design and applications of an instrument for imaging X-ray photoelectron spectroscopy (XPS) are reviewed. The instrument is based on a photoelectron microscope and a double hemispherical analyser whose symmetric configuration avoids the spherical aberration (α 2 -term) inherent for standard analysers. The analyser allows high transmission imaging without sacrificing the lateral and energy resolution of the instrument. The importance of high transmission, especially for highest resolution imaging XPS with monochromated laboratory X-ray sources, is outlined and the close interrelation of energy resolution, lateral resolution and analyser transmission is illustrated. Chemical imaging applications using a monochromatic laboratory Al Kα-source are shown, with a lateral resolution of 610 nm. Examples of measurements made using synchrotron and laboratory ultra-violet light show the broad field of applications from imaging of core level electrons with chemical shift identification, high resolution threshold photoelectron emission microscopy (PEEM), work function imaging and band structure imaging.

  13. A Fast Algorithm for Image Super-Resolution from Blurred Observations

    Directory of Open Access Journals (Sweden)

    Ng Michael K

    2006-01-01

    Full Text Available We study the problem of reconstruction of a high-resolution image from several blurred low-resolution image frames. The image frames consist of blurred, decimated, and noisy versions of a high-resolution image. The high-resolution image is modeled as a Markov random field (MRF, and a maximum a posteriori (MAP estimation technique is used for the restoration. We show that with the periodic boundary condition, a high-resolution image can be restored efficiently by using fast Fourier transforms. We also apply the preconditioned conjugate gradient method to restore high-resolution images in the aperiodic boundary condition. Computer simulations are given to illustrate the effectiveness of the proposed approach.

  14. Coded aperture subreflector array for high resolution radar imaging

    Science.gov (United States)

    Lynch, Jonathan J.; Herrault, Florian; Kona, Keerti; Virbila, Gabriel; McGuire, Chuck; Wetzel, Mike; Fung, Helen; Prophet, Eric

    2017-05-01

    HRL Laboratories has been developing a new approach for high resolution radar imaging on stationary platforms. High angular resolution is achieved by operating at 235 GHz and using a scalable tile phased array architecture that has the potential to realize thousands of elements at an affordable cost. HRL utilizes aperture coding techniques to minimize the size and complexity of the RF electronics needed for beamforming, and wafer level fabrication and integration allow tiles containing 1024 elements to be manufactured with reasonable costs. This paper describes the results of an initial feasibility study for HRL's Coded Aperture Subreflector Array (CASA) approach for a 1024 element micromachined antenna array with integrated single-bit phase shifters. Two candidate electronic device technologies were evaluated over the 170 - 260 GHz range, GaN HEMT transistors and GaAs Schottky diodes. Array structures utilizing silicon micromachining and die bonding were evaluated for etch and alignment accuracy. Finally, the overall array efficiency was estimated to be about 37% (not including spillover losses) using full wave array simulations and measured device performance, which is a reasonable value at 235 GHz. Based on the measured data we selected GaN HEMT devices operated passively with 0V drain bias due to their extremely low DC power dissipation.

  15. Theoretical study for aerial image intensity in resist in high numerical aperture projection optics and experimental verification with one-dimensional patterns

    Science.gov (United States)

    Shibuya, Masato; Takada, Akira; Nakashima, Toshiharu

    2016-04-01

    In optical lithography, high-performance exposure tools are indispensable to obtain not only fine patterns but also preciseness in pattern width. Since an accurate theoretical method is necessary to predict these values, some pioneer and valuable studies have been proposed. However, there might be some ambiguity or lack of consensus regarding the treatment of diffraction by object, incoming inclination factor onto image plane in scalar imaging theory, and paradoxical phenomenon of the inclined entrance plane wave onto image in vector imaging theory. We have reconsidered imaging theory in detail and also phenomenologically resolved the paradox. By comparing theoretical aerial image intensity with experimental pattern width for one-dimensional pattern, we have validated our theoretical consideration.

  16. Fluid Lensing, Applications to High-Resolution 3D Subaqueous Imaging & Automated Remote Biosphere Assessment from Airborne and Space-borne Platforms

    Science.gov (United States)

    Chirayath, V.

    2014-12-01

    Fluid Lensing is a theoretical model and algorithm I present for fluid-optical interactions in turbulent flows as well as two-fluid surface boundaries that, when coupled with an unique computer vision and image-processing pipeline, may be used to significantly enhance the angular resolution of a remote sensing optical system with applicability to high-resolution 3D imaging of subaqueous regions and through turbulent fluid flows. This novel remote sensing technology has recently been implemented on a quadcopter-based UAS for imaging shallow benthic systems to create the first dataset of a biosphere with unprecedented sub-cm-level imagery in 3D over areas as large as 15 square kilometers. Perturbed two-fluid boundaries with different refractive indices, such as the surface between the ocean and air, may be exploited for use as lensing elements for imaging targets on either side of the interface with enhanced angular resolution. I present theoretical developments behind Fluid Lensing and experimental results from its recent implementation for the Reactive Reefs project to image shallow reef ecosystems at cm scales. Preliminary results from petabyte-scale aerial survey efforts using Fluid Lensing to image at-risk coral reefs in American Samoa (August, 2013) show broad applicability to large-scale automated species identification, morphology studies and reef ecosystem characterization for shallow marine environments and terrestrial biospheres, of crucial importance to understanding climate change's impact on coastal zones, global oxygen production and carbon sequestration.

  17. Resolution of coherent and incoherent imaging systems reconsidered : Classical criteria and a statistical alternative

    NARCIS (Netherlands)

    Van Aert, S.; Van Dyck, D.; Den Dekker, A.J.

    2006-01-01

    The resolution of coherent and incoherent imaging systems is usually evaluated in terms of classical resolution criteria, such as Rayleigh’s. Based on these criteria, incoherent imaging is generally concluded to be ‘better’ than coherent imaging. However, this paper reveals some misconceptions in

  18. Monitoring post-fire changes in species composition and stand structure in boreal forests using high-resolution, 3-D aerial drone data and Landsat

    Science.gov (United States)

    Alonzo, M.; Morton, D. C.; Cook, B.; Andersen, H. E.; Mack, M. C.

    2017-12-01

    The growing frequency and severity of boreal forest fires has important consequences for fire carbon emissions and ecosystem composition. Severe fires are typically associated with high degrees of both canopy and soil organic layer (SOL) consumption, particularly in black spruce stands. Complete canopy consumption can decrease the likelihood of spruce regeneration due to reduced viability of the aerial seedbank. Deeper burning of the SOL increases fire emissions and can expose mineral soil that promotes colonization by broadleaf species. There is mounting evidence that a disturbance-driven shift from spruce to broadleaf forests may indicate an ecological state change with feedbacks to regional and global climate. If post-fire successional dynamics can be characterized at an ecosystem scale using remote sensing data, we will be better equipped to constrain carbon and energy fluxes from SOL losses and albedo changes. In this study, we used Landsat time series, very high-resolution structure-from-motion (SFM) drone imagery, and field measurements to investigate post-fire regrowth 13 years after the 2004 Taylor Complex (TC) fires in interior Alaska. Twenty-seven TC plots span a gradient of moisture conditions and burn severity as estimated by loss of SOL. A range of variables potentially governing seedling species dominance (e.g., moisture status, distance to seed sources) have been collected systematically over the years following fire. In July 2017, we additionally collected drone imagery over 25 of the TC plots. We processed these highly overlapped, nadir-view and oblique angle photos into extremely dense (>700 pts/m2) RGB-colored point clouds using SFM techniques. With these point clouds and high resolution orthomosaics, we estimated: 1) snag heights and biomass, 2) remnant snag fine branching, and 3) species and structure of shrubs and groundcover that have regrown since fire. We additionally assembled a dense Landsat time series arranged by day-of-year to monitor

  19. Magnetic Resonance Super-resolution Imaging Measurement with Dictionary-optimized Sparse Learning

    Directory of Open Access Journals (Sweden)

    Li Jun-Bao

    2017-06-01

    Full Text Available Magnetic Resonance Super-resolution Imaging Measurement (MRIM is an effective way of measuring materials. MRIM has wide applications in physics, chemistry, biology, geology, medical and material science, especially in medical diagnosis. It is feasible to improve the resolution of MR imaging through increasing radiation intensity, but the high radiation intensity and the longtime of magnetic field harm the human body. Thus, in the practical applications the resolution of hardware imaging reaches the limitation of resolution. Software-based super-resolution technology is effective to improve the resolution of image. This work proposes a framework of dictionary-optimized sparse learning based MR super-resolution method. The framework is to solve the problem of sample selection for dictionary learning of sparse reconstruction. The textural complexity-based image quality representation is proposed to choose the optimal samples for dictionary learning. Comprehensive experiments show that the dictionary-optimized sparse learning improves the performance of sparse representation.

  20. EXTRACTION OF ROOF LINES FROM HIGH-RESOLUTION IMAGES BY A GROUPING METHOD

    Directory of Open Access Journals (Sweden)

    A. P. Dal Poz

    2016-06-01

    Full Text Available This paper proposes a method for extracting groups of straight lines that represent roof boundaries and roof ridgelines from highresolution aerial images using corresponding Airborne Laser Scanner (ALS roof polyhedrons as initial approximations. The proposed method is based on two main steps. First, straight lines that are candidates to represent roof ridgelines and roof boundaries of a building are extracted from the aerial image. Second, a group of straight lines that represent roof boundaries and roof ridgelines of a selected building is obtained through the optimization of a Markov Random Field (MRF-based energy function using the genetic algorithm optimization method. The formulation of this energy function considers several attributes, such as the proximity of the extracted straight lines to the corresponding projected ALS-derived roof polyhedron and the rectangularity (extracted straight lines that intersect at nearly 90°. Experimental results are presented and discussed in this paper.

  1. Influence of total beam current on HRTEM image resolution in differentially pumped ETEM with nitrogen gas

    International Nuclear Information System (INIS)

    Bright, A.N.; Yoshida, K.; Tanaka, N.

    2013-01-01

    Environmental transmission electron microscopy (ETEM) enables the study of catalytic and other reaction processes as they occur with Angstrom-level resolution. The microscope used is a dedicated ETEM (Titan ETEM, FEI Company) with a differential pumping vacuum system and apertures, allowing aberration corrected high-resolution transmission electron microscopy (HRTEM) imaging to be performed with gas pressures up to 20 mbar in the sample area and with significant advantages over membrane-type E-cell holders. The effect on image resolution of varying the nitrogen gas pressure, electron beam current density and total beam current were measured using information limit (Young's fringes) on a standard cross grating sample and from silicon crystal lattice imaging. As expected, increasing gas pressure causes a decrease in HRTEM image resolution. However, the total electron beam current also causes big changes in the image resolution (lower beam current giving better resolution), whereas varying the beam current density has almost no effect on resolution, a result that has not been reported previously. This behavior is seen even with zero-loss filtered imaging, which we believe shows that the drop in resolution is caused by elastic scattering at gas ions created by the incident electron beam. Suitable conditions for acquiring high resolution images in a gas environment are discussed. Lattice images at nitrogen pressures up to 16 mbar are shown, with 0.12 nm information transfer at 4 mbar. -- Highlights: ► ETEM images with point resolution of 0.12 nm in 4 mbar of nitrogen gas. ► Clear Si lattice imaging with 16 mbar of nitrogen gas. ► ETEM image resolution in gas can be much improved by decreasing total beam current. ► Beam current density (beam convergence) has no effect on the image resolution.

  2. Regional snow-avalanche detection using object-based image analysis of near-infrared aerial imagery

    Directory of Open Access Journals (Sweden)

    K. Korzeniowska

    2017-10-01

    Full Text Available Snow avalanches are destructive mass movements in mountain regions that continue to claim lives and cause infrastructural damage and traffic detours. Given that avalanches often occur in remote and poorly accessible steep terrain, their detection and mapping is extensive and time consuming. Nonetheless, systematic avalanche detection over large areas could help to generate more complete and up-to-date inventories (cadastres necessary for validating avalanche forecasting and hazard mapping. In this study, we focused on automatically detecting avalanches and classifying them into release zones, tracks, and run-out zones based on 0.25 m near-infrared (NIR ADS80-SH92 aerial imagery using an object-based image analysis (OBIA approach. Our algorithm takes into account the brightness, the normalised difference vegetation index (NDVI, the normalised difference water index (NDWI, and its standard deviation (SDNDWI to distinguish avalanches from other land-surface elements. Using normalised parameters allows applying this method across large areas. We trained the method by analysing the properties of snow avalanches at three 4 km−2 areas near Davos, Switzerland. We compared the results with manually mapped avalanche polygons and obtained a user's accuracy of > 0.9 and a Cohen's kappa of 0.79–0.85. Testing the method for a larger area of 226.3 km−2, we estimated producer's and user's accuracies of 0.61 and 0.78, respectively, with a Cohen's kappa of 0.67. Detected avalanches that overlapped with reference data by > 80 % occurred randomly throughout the testing area, showing that our method avoids overfitting. Our method has potential for large-scale avalanche mapping, although further investigations into other regions are desirable to verify the robustness of our selected thresholds and the transferability of the method.

  3. Facilities for High Resolution Imaging of the Sun

    Science.gov (United States)

    von der Lühe, Oskar

    2018-04-01

    The Sun is the only star where physical processes can be observed at their intrinsic spatial scales. Even though the Sun in a mere 150 million km from Earth, it is difficult to resolve fundamental processes in the solar atmosphere, because they occur at scales of the order of the kilometer. They can be observed only with telescopes which have apertures of several meters. The current state-of-the-art are solar telescopes with apertures of 1.5 m which resolve 50 km on the solar surface, soon to be superseded by telescopes with 4 m apertures with 20 km resolution. The US American 4 m DSI Solar Telescope is currently constructed on Maui, Hawaii, and is expected to have first light in 2020. The European solar community collaborates intensively to pursue the 4 m European Solar Telescope with a construction start in the Canaries early in the next decade. Solar telescopes with slightly smaller are also in the planning by the Russian, Indian and Chinese communities. In order to achieve a resolution which approaches the diffraction limit, all modern solar telescopes use adaptive optics which compensates virtually any scene on the solar disk. Multi-conjugate adaptive optics designed to compensate fields of the order on one minute of arc have been demonstrated and will become a facility feature of the new telescopes. The requirements for high precision spectro-polarimetry – about one part in 104 – makes continuous monitoring of (MC)AO performance and post-processing image reconstruction methods a necessity.

  4. Effects of display resolution and size on primary diagnosis of chest images using a high-resolution electronic work station

    International Nuclear Information System (INIS)

    Fuhrman, C.R.; Cooperstein, L.A.; Herron, J.; Good, W.F.; Good, B.; Gur, D.; Maitz, G.; Tabor, E.; Hoy, R.J.

    1987-01-01

    To evaluate the acceptability of electronically displayed planar images, the authors have a high-resolution work station. This system utilizes a high-resolution film digitizer (100-micro resolution) interfaced to a mainframe computer and two high-resolution (2,048 X 2,048) display devices (Azuray). In a clinically simulated multiobserver blind study (19 cases and five observers) a prodetermined series of reading sessions is stored on magnetic disk and is transferred to the displays while the preceding set of images is being reviewed. Images can be linearly processed on the fly into 2,000 X 2,000 full resolution, 1,000 X 1,000 minified display, or 1,000 X 1,000 interpolated for full-size display. Results of the study indicate that radiologists accept but do not like significant minification (more than X2), and they rate 2,000 X 2,000 images as having better diagnostic quality than 1,000 X 1,000 images

  5. The Potential of Unmanned Aerial Vehicle for Large Scale Mapping of Coastal Area

    International Nuclear Information System (INIS)

    Darwin, N; Ahmad, A; Zainon, O

    2014-01-01

    Many countries in the tropical region are covered with cloud for most of the time, hence, it is difficult to get clear images especially from high resolution satellite imagery. Aerial photogrammetry can be used but most of the time the cloud problem still exists. Today, this problem could be solved using a system known as unmanned aerial vehicle (UAV) where the aerial images can be acquired at low altitude and the system can fly under the cloud. The UAV system could be used in various applications including mapping coastal area. The UAV system is equipped with an autopilot system and automatic method known as autonomous flying that can be utilized for data acquisition. To achieve high resolution imagery, a compact digital camera of high resolution was used to acquire the aerial images at an altitude. In this study, the UAV system was employed to acquire aerial images of a coastal simulation model at low altitude. From the aerial images, photogrammetric image processing was executed to produce photogrammetric outputs such a digital elevation model (DEM), contour line and orthophoto. In this study, ground control point (GCP) and check point (CP) were established using conventional ground surveying method (i.e total station). The GCP is used for exterior orientation in photogrammetric processes and CP for accuracy assessment based on Root Mean Square Error (RMSE). From this study, it was found that the UAV system can be used for large scale mapping of coastal simulation model with accuracy at millimeter level. It is anticipated that the same system could be used for large scale mapping of real coastal area and produces good accuracy. Finally, the UAV system has great potential to be used for various applications that require accurate results or products at limited time and less man power

  6. Classification of Urban Feature from Unmanned Aerial Vehicle Images Using Gasvm Integration and Multi-Scale Segmentation

    Science.gov (United States)

    Modiri, M.; Salehabadi, A.; Mohebbi, M.; Hashemi, A. M.; Masumi, M.

    2015-12-01

    The use of UAV in the application of photogrammetry to obtain cover images and achieve the main objectives of the photogrammetric mapping has been a boom in the region. The images taken from REGGIOLO region in the province of, Italy Reggio -Emilia by UAV with non-metric camera Canon Ixus and with an average height of 139.42 meters were used to classify urban feature. Using the software provided SURE and cover images of the study area, to produce dense point cloud, DSM and Artvqvtv spatial resolution of 10 cm was prepared. DTM area using Adaptive TIN filtering algorithm was developed. NDSM area was prepared with using the difference between DSM and DTM and a separate features in the image stack. In order to extract features, using simultaneous occurrence matrix features mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation for each of the RGB band image was used Orthophoto area. Classes used to classify urban problems, including buildings, trees and tall vegetation, grass and vegetation short, paved road and is impervious surfaces. Class consists of impervious surfaces such as pavement conditions, the cement, the car, the roof is stored. In order to pixel-based classification and selection of optimal features of classification was GASVM pixel basis. In order to achieve the classification results with higher accuracy and spectral composition informations, texture, and shape conceptual image featureOrthophoto area was fencing. The segmentation of multi-scale segmentation method was used.it belonged class. Search results using the proposed classification of urban feature, suggests the suitability of this method of classification complications UAV is a city using images. The overall accuracy and kappa coefficient method proposed in this study, respectively, 47/93% and 84/91% was.

  7. Roads Data Conflation Using Update High Resolution Satellite Images

    Science.gov (United States)

    Abdollahi, A.; Riyahi Bakhtiari, H. R.

    2017-11-01

    Urbanization, industrialization and modernization are rapidly growing in developing countries. New industrial cities, with all the problems brought on by rapid population growth, need infrastructure to support the growth. This has led to the expansion and development of the road network. A great deal of road network data has made by using traditional methods in the past years. Over time, a large amount of descriptive information has assigned to these map data, but their geometric accuracy and precision is not appropriate to today's need. In this regard, the improvement of the geometric accuracy of road network data by preserving the descriptive data attributed to them and updating of the existing geo databases is necessary. Due to the size and extent of the country, updating the road network maps using traditional methods is time consuming and costly. Conversely, using remote sensing technology and geographic information systems can reduce costs, save time and increase accuracy and speed. With increasing the availability of high resolution satellite imagery and geospatial datasets there is an urgent need to combine geographic information from overlapping sources to retain accurate data, minimize redundancy, and reconcile data conflicts. In this research, an innovative method for a vector-to-imagery conflation by integrating several image-based and vector-based algorithms presented. The SVM method for image classification and Level Set method used to extract the road the different types of road intersections extracted from imagery using morphological operators. For matching the extracted points and to find the corresponding points, matching function which uses the nearest neighborhood method was applied. Finally, after identifying the matching points rubber-sheeting method used to align two datasets. Two residual and RMSE criteria used to evaluate accuracy. The results demonstrated excellent performance. The average root-mean-square error decreased from 11.8 to 4.1 m.

  8. Automated, feature-based image alignment for high-resolution imaging mass spectrometry of large biological samples

    NARCIS (Netherlands)

    Broersen, A.; Liere, van R.; Altelaar, A.F.M.; Heeren, R.M.A.; McDonnell, L.A.

    2008-01-01

    High-resolution imaging mass spectrometry of large biological samples is the goal of several research groups. In mosaic imaging, the most common method, the large sample is divided into a mosaic of small areas that are then analyzed with high resolution. Here we present an automated alignment

  9. Signal Amplification Technique (SAT): an approach for improving resolution and reducing image noise in computed tomography

    International Nuclear Information System (INIS)

    Phelps, M.E.; Huang, S.C.; Hoffman, E.J.; Plummer, D.; Carson, R.

    1981-01-01

    Spatial resolution improvements in computed tomography (CT) have been limited by the large and unique error propagation properties of this technique. The desire to provide maximum image resolution has resulted in the use of reconstruction filter functions designed to produce tomographic images with resolution as close as possible to the intrinsic detector resolution. Thus, many CT systems produce images with excessive noise with the system resolution determined by the detector resolution rather than the reconstruction algorithm. CT is a rigorous mathematical technique which applies an increasing amplification to increasing spatial frequencies in the measured data. This mathematical approach to spatial frequency amplification cannot distinguish between signal and noise and therefore both are amplified equally. We report here a method in which tomographic resolution is improved by using very small detectors to selectively amplify the signal and not noise. Thus, this approach is referred to as the signal amplification technique (SAT). SAT can provide dramatic improvements in image resolution without increases in statistical noise or dose because increases in the cutoff frequency of the reconstruction algorithm are not required to improve image resolution. Alternatively, in cases where image counts are low, such as in rapid dynamic or receptor studies, statistical noise can be reduced by lowering the cutoff frequency while still maintaining the best possible image resolution. A possible system design for a positron CT system with SAT is described

  10. Influence of total beam current on HRTEM image resolution in differentially pumped ETEM with nitrogen gas.

    Science.gov (United States)

    Bright, A N; Yoshida, K; Tanaka, N

    2013-01-01

    Environmental transmission electron microscopy (ETEM) enables the study of catalytic and other reaction processes as they occur with Angstrom-level resolution. The microscope used is a dedicated ETEM (Titan ETEM, FEI Company) with a differential pumping vacuum system and apertures, allowing aberration corrected high-resolution transmission electron microscopy (HRTEM) imaging to be performed with gas pressures up to 20 mbar in the sample area and with significant advantages over membrane-type E-cell holders. The effect on image resolution of varying the nitrogen gas pressure, electron beam current density and total beam current were measured using information limit (Young's fringes) on a standard cross grating sample and from silicon crystal lattice imaging. As expected, increasing gas pressure causes a decrease in HRTEM image resolution. However, the total electron beam current also causes big changes in the image resolution (lower beam current giving better resolution), whereas varying the beam current density has almost no effect on resolution, a result that has not been reported previously. This behavior is seen even with zero-loss filtered imaging, which we believe shows that the drop in resolution is caused by elastic scattering at gas ions created by the incident electron beam. Suitable conditions for acquiring high resolution images in a gas environment are discussed. Lattice images at nitrogen pressures up to 16 mbar are shown, with 0.12 nm information transfer at 4 mbar. Copyright © 2012 Elsevier B.V. All rights reserved.

  11. Real-space imaging of interfacial water with submolecular resolution

    Science.gov (United States)

    Jiang, Ying; Peking University Team

    2014-03-01

    Water/solid interfaces are vital to our daily lives and also a central theme across an incredibly wide range of scientific disciplines. Resolving the internal structure, i.e. the O-H directionality, of water molecules adsorbed on solid surfaces has been one of the key issues of water science yet remains challenging. Using a low-temperature scanning tunneling microscope (STM), we report the submolecular-resolution imaging of individual water monomers and tetramers on NaCl(001) films supported by a Au(111) substrate at 5 K. The frontier molecular orbitals of adsorbed water were directly visualized, which allowed discriminating the orientation of the monomers and the H-bond directionality of the tetramers in real space. Comparison with ab initio density functional theory calculations reveals that the ability to access the orbital structures of water stems from the electronic decoupling effect provided by the NaCl films and the precisely tunable tip-water coupling. Supported by National Basic Research Programs of China and National Science Foundation of China.

  12. Atomic Resolution Imaging and Quantification of Chemical Functionality of Surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Schwarz, Udo D. [Yale Univ., New Haven, CT (United States). Dept. of Mechanical Engineering and Materials Science; Altman, Eric I. [Yale Univ., New Haven, CT (United States). Dept. of Chemical and Environmental Engineering

    2014-12-10

    The work carried out from 2006-2014 under DoE support was targeted at developing new approaches to the atomic-scale characterization of surfaces that include species-selective imaging and an ability to quantify chemical surface interactions with site-specific accuracy. The newly established methods were subsequently applied to gain insight into the local chemical interactions that govern the catalytic properties of model catalysts of interest to DoE. The foundation of our work was the development of three-dimensional atomic force microscopy (3DAFM), a new measurement mode that allows the mapping of the complete surface force and energy fields with picometer resolution in space (x, y, and z) and piconewton/millielectron volts in force/energy. From this experimental platform, we further expanded by adding the simultaneous recording of tunneling current (3D-AFM/STM) using chemically well-defined tips. Through comparison with simulations, we were able to achieve precise quantification and assignment of local chemical interactions to exact positions within the lattice. During the course of the project, the novel techniques were applied to surface-oxidized copper, titanium dioxide, and silicon oxide. On these materials, defect-induced changes to the chemical surface reactivity and electronic charge density were characterized with site-specific accuracy.

  13. A fast and mobile system for registration of low-altitude visual and thermal aerial images using multiple small-scale UAVs

    Science.gov (United States)

    Yahyanejad, Saeed; Rinner, Bernhard

    2015-06-01

    The use of multiple small-scale UAVs to support first responders in disaster management has become popular because of their speed and low deployment costs. We exploit such UAVs to perform real-time monitoring of target areas by fusing individual images captured from heterogeneous aerial sensors. Many approaches have already been presented to register images from homogeneous sensors. These methods have demonstrated robustness against scale, rotation and illumination variations and can also cope with limited overlap among individual images. In this paper we focus on thermal and visual image registration and propose different methods to improve the quality of interspectral registration for the purpose of real-time monitoring and mobile mapping. Images captured by low-altitude UAVs represent a very challenging scenario for interspectral registration due to the strong variations in overlap, scale, rotation, point of view and structure of such scenes. Furthermore, these small-scale UAVs have limited processing and communication power. The contributions of this paper include (i) the introduction of a feature descriptor for robustly identifying corresponding regions of images in different spectrums, (ii) the registration of image mosaics, and (iii) the registration of depth maps. We evaluated the first method using a test data set consisting of 84 image pairs. In all instances our approach combined with SIFT or SURF feature-based registration was superior to the standard versions. Although we focus mainly on aerial imagery, our evaluation shows that the presented approach would also be beneficial in other scenarios such as surveillance and human detection. Furthermore, we demonstrated the advantages of the other two methods in case of multiple image pairs.

  14. Mapping of invasive Acacia species in Brazilian Mussununga ecosystems using high- resolution IR remote sensing data acquired with an autonomous Unmanned Aerial System (UAS)

    Science.gov (United States)

    Lehmann, Jan Rudolf Karl; Zvara, Ondrej; Prinz, Torsten

    2015-04-01

    The biological invasion of Australian Acacia species in natural ecosystems outside Australia has often a negative impact on native and endemic plant species and the related biodiversity. In Brazil, the Atlantic rainforest of Bahia and Espirito Santo forms an associated type of ecosystem, the Mussununga. In our days this biologically diverse ecosystem is negatively affected by the invasion of Acacia mangium and Acacia auriculiformis, both introduced to Brazil by the agroforestry to increase the production of pulp and high grade woods. In order to detect the distribution of Acacia species and to monitor the expansion of this invasion the use of high-resolution imagery data acquired with an autonomous Unmanned Aerial System (UAS) proved to be a very promising approach. In this study, two types of datasets - CIR and RGB - were collected since both types provide different information. In case of CIR imagery attention was paid on spectral signatures related to plants, whereas in case of RGB imagery the focus was on surface characteristics. Orthophoto-mosaics and DSM/DTM for both dataset were extracted. RGB/IHS transformations of the imagery's colour space were utilized, as well as NDVIblue index in case of CIR imagery to discriminate plant associations. Next, two test areas were defined in order validate OBIA rule sets using eCognition software. In case of RGB dataset, a rule set based on elevation distinction between high vegetation (including Acacia) and low vegetation (including soils) was developed. High vegetation was classified using Nearest Neighbour algorithm while working with the CIR dataset. The IHS information was used to mask shadows, soils and low vegetation. Further Nearest Neighbour classification was used for distinction between Acacia and other high vegetation types. Finally an accuracy assessment was performed using a confusion matrix. One can state that the IHS information appeared to be helpful in Acacia detection while the surface elevation

  15. Comparison of Manual Mapping and Automated Object-Based Image Analysis of Non-Submerged Aquatic Vegetation from Very-High-Resolution UAS Images

    Directory of Open Access Journals (Sweden)

    Eva Husson

    2016-09-01

    Full Text Available Aquatic vegetation has important ecological and regulatory functions and should be monitored in order to detect ecosystem changes. Field data collection is often costly and time-consuming; remote sensing with unmanned aircraft systems (UASs provides aerial images with sub-decimetre resolution and offers a potential data source for vegetation mapping. In a manual mapping approach, UAS true-colour images with 5-cm-resolution pixels allowed for the identification of non-submerged aquatic vegetation at the species level. However, manual mapping is labour-intensive, and while automated classification methods are available, they have rarely been evaluated for aquatic vegetation, particularly at the scale of individual vegetation stands. We evaluated classification accuracy and time-efficiency for mapping non-submerged aquatic vegetation at three levels of detail at five test sites (100 m × 100 m differing in vegetation complexity. We used object-based image analysis and tested two classification methods (threshold classification and Random Forest using eCognition®. The automated classification results were compared to results from manual mapping. Using threshold classification, overall accuracy at the five test sites ranged from 93% to 99% for the water-versus-vegetation level and from 62% to 90% for the growth-form level. Using Random Forest classification, overall accuracy ranged from 56% to 94% for the growth-form level and from 52% to 75% for the dominant-taxon level. Overall classification accuracy decreased with increasing vegetation complexity. In test sites with more complex vegetation, automated classification was more time-efficient than manual mapping. This study demonstrated that automated classification of non-submerged aquatic vegetation from true-colour UAS images was feasible, indicating good potential for operative mapping of aquatic vegetation. When choosing the preferred mapping method (manual versus automated the desired level of

  16. A Simple Metric for Determining Resolution in Optical, Ion, and Electron Microscope Images.

    Science.gov (United States)

    Curtin, Alexandra E; Skinner, Ryan; Sanders, Aric W

    2015-06-01

    A resolution metric intended for resolution analysis of arbitrary spatially calibrated images is presented. By fitting a simple sigmoidal function to pixel intensities across slices of an image taken perpendicular to light-dark edges, the mean distance over which the light-dark transition occurs can be determined. A fixed multiple of this characteristic distance is then reported as the image resolution. The prefactor is determined by analysis of scanning transmission electron microscope high-angle annular dark field images of Si. This metric has been applied to optical, scanning electron microscope, and helium ion microscope images. This method provides quantitative feedback about image resolution, independent of the tool on which the data were collected. In addition, our analysis provides a nonarbitrary and self-consistent framework that any end user can utilize to evaluate the resolution of multiple microscopes from any vendor using the same metric.

  17. Multi-Sensor Fusion of Infrared and Electro-Optic Signals for High Resolution Night Images

    Directory of Open Access Journals (Sweden)

    Victor Lawrence

    2012-07-01

    Full Text Available Electro-optic (EO image sensors exhibit the properties of high resolution and low noise level at daytime, but they do not work in dark environments. Infrared (IR image sensors exhibit poor resolution and cannot separate objects with similar temperature. Therefore, we propose a novel framework of IR image enhancement based on the information (e.g., edge from EO images, which improves the resolution of IR images and helps us distinguish objects at night. Our framework superimposing/blending the edges of the EO image onto the corresponding transformed IR image improves their resolution. In this framework, we adopt the theoretical point spread function (PSF proposed by Hardie et al. for the IR image, which has the modulation transfer function (MTF of a uniform detector array and the incoherent optical transfer function (OTF of diffraction-limited optics. In addition, we design an inverse filter for the proposed PSF and use it for the IR image transformation. The framework requires four main steps: (1 inverse filter-based IR image transformation; (2 EO image edge detection; (3 registration; and (4 blending/superimposing of the obtained image pair. Simulation results show both blended and superimposed IR images, and demonstrate that blended IR images have better quality over the superimposed images. Additionally, based on the same steps, simulation result shows a blended IR image of better quality when only the original IR image is available.

  18. Solving the problem of imaging resolution: stochastic multi-scale image fusion

    Science.gov (United States)

    Karsanina, Marina; Mallants, Dirk; Gilyazetdinova, Dina; Gerke, Kiril

    2016-04-01

    Structural features of porous materials define the majority of its physical properties, including water infiltration and redistribution, multi-phase flow (e.g. simultaneous water/air flow, gas exchange between biologically active soil root zone and atmosphere, etc.) and solute transport. To characterize soil and rock microstructure X-ray microtomography is extremely useful. However, as any other imaging technique, this one also has a significant drawback - a trade-off between sample size and resolution. The latter is a significant problem for multi-scale complex structures, especially such as soils and carbonates. Other imaging techniques, for example, SEM/FIB-SEM or X-ray macrotomography can be helpful in obtaining higher resolution or wider field of view. The ultimate goal is to create a single dataset containing information from all scales or to characterize such multi-scale structure. In this contribution we demonstrate a general solution for merging multiscale categorical spatial data into a single dataset using stochastic reconstructions with rescaled correlation functions. The versatility of the method is demonstrated by merging three images representing macro, micro and nanoscale spatial information on porous media structure. Images obtained by X-ray microtomography and scanning electron microscopy were fused into a single image with predefined resolution. The methodology is sufficiently generic for implementation of other stochastic reconstruction techniques, any number of scales, any number of material phases, and any number of images for a given scale. The methodology can be further used to assess effective properties of fused porous media images or to compress voluminous spatial datasets for efficient data storage. Potential practical applications of this method are abundant in soil science, hydrology and petroleum engineering, as well as other geosciences. This work was partially supported by RSF grant 14-17-00658 (X-ray microtomography study of shale

  19. A comparative analysis of pixel- and object-based detection of landslides from very high-resolution images

    Science.gov (United States)

    Keyport, Ren N.; Oommen, Thomas; Martha, Tapas R.; Sajinkumar, K. S.; Gierke, John S.

    2018-02-01

    A comparative analysis of landslides detected by pixel-based and object-oriented analysis (OOA) methods was performed using very high-resolution (VHR) remotely sensed aerial images for the San Juan La Laguna, Guatemala, which witnessed widespread devastation during the 2005 Hurricane Stan. A 3-band orthophoto of 0.5 m spatial resolution together with a 115 field-based landslide inventory were used for the analysis. A binary reference was assigned with a zero value for landslide and unity for non-landslide pixels. The pixel-based analysis was performed using unsupervised classification, which resulted in 11 different trial classes. Detection of landslides using OOA includes 2-step K-means clustering to eliminate regions based on brightness; elimination of false positives using object properties such as rectangular fit, compactness, length/width ratio, mean difference of objects, and slope angle. Both overall accuracy and F-score for OOA methods outperformed pixel-based unsupervised classification methods in both landslide and non-landslide classes. The overall accuracy for OOA and pixel-based unsupervised classification was 96.5% and 94.3%, respectively, whereas the best F-score for landslide identification for OOA and pixel-based unsupervised methods: were 84.3% and 77.9%, respectively.Results indicate that the OOA is able to identify the majority of landslides with a few false positive when compared to pixel-based unsupervised classification.

  20. Combining Human Computing and Machine Learning to Make Sense of Big (Aerial) Data for Disaster Response.

    Science.gov (United States)

    Ofli, Ferda; Meier, Patrick; Imran, Muhammad; Castillo, Carlos; Tuia, Devis; Rey, Nicolas; Briant, Julien; Millet, Pauline; Reinhard, Friedrich; Parkan, Matthew; Joost, Stéphane

    2016-03-01

    Aerial imagery captured via unmanned aerial vehicles (UAVs) is playing an increasingly important role in disaster response. Unlike satellite imagery, aerial imagery can be captured and processed within hours rather than days. In addition, the spatial resolution of aerial imagery is an order of magnitude higher than the imagery produced by the most sophisticated commercial satellites today. Both the United States Federal Emergency Management Agency (FEMA) and the European Commission's Joint Research Center (JRC) have noted that aerial imagery will inevitably present a big data challenge. The purpose of this article is to get ahead of this future challenge by proposing a hybrid crowdsourcing and real-time machine learning solution to rapidly process large volumes of aerial data for disaster response in a time-sensitive manner. Crowdsourcing can be used to annotate features of interest in aerial images (such as damaged shelters and roads blocked by debris). These human-annotated features can then be used to train a supervised machine learning system to learn to recognize such features in new unseen images. In this article, we describe how this hybrid solution for image analysis can be implemented as a module (i.e., Aerial Clicker) to extend an existing platform called Artificial Intelligence for Disaster Response (AIDR), which has already been deployed to classify microblog messages during disasters using its Text Clicker module and in response to Cyclone Pam, a category 5 cyclone that devastated Vanuatu in March 2015. The hybrid solution we present can be applied to both aerial and satellite imagery and has applications beyond disaster response such as wildlife protection, human rights, and archeological exploration. As a proof of concept, we recently piloted this solution using very high-resolution aerial photographs of a wildlife reserve in Namibia to support rangers with their wildlife conservation efforts (SAVMAP project, http://lasig.epfl.ch/savmap ). The

  1. Super resolution reconstruction of infrared images based on classified dictionary learning

    Science.gov (United States)

    Liu, Fei; Han, Pingli; Wang, Yi; Li, Xuan; Bai, Lu; Shao, Xiaopeng

    2018-05-01

    Infrared images always suffer from low-resolution problems resulting from limitations of imaging devices. An economical approach to combat this problem involves reconstructing high-resolution images by reasonable methods without updating devices. Inspired by compressed sensing theory, this study presents and demonstrates a Classified Dictionary Learning method to reconstruct high-resolution infrared images. It classifies features of the samples into several reasonable clusters and trained a dictionary pair for each cluster. The optimal pair of dictionaries is chosen for each image reconstruction and therefore, more satisfactory results is achieved without the increase in computational complexity and time cost. Experiments and results demonstrated that it is a viable method for infrared images reconstruction since it improves image resolution and recovers detailed information of targets.

  2. Dedicated mobile high resolution prostate PET imager with an insertable transrectal probe

    Science.gov (United States)

    Majewski, Stanislaw; Proffitt, James

    2010-12-28

    A dedicated mobile PET imaging system to image the prostate and surrounding organs. The imaging system includes an outside high resolution PET imager placed close to the patient's torso and an insertable and compact transrectal probe that is placed in close proximity to the prostate and operates in conjunction with the outside imager. The two detector systems are spatially co-registered to each other. The outside imager is mounted on an open rotating gantry to provide torso-wide 3D images of the prostate and surrounding tissue and organs. The insertable probe provides closer imaging, high sensitivity, and very high resolution predominately 2D view of the prostate and immediate surroundings. The probe is operated in conjunction with the outside imager and a fast data acquisition system to provide very high resolution reconstruction of the prostate and surrounding tissue and organs.

  3. Improving spatial resolution in quantum imaging beyond the Rayleigh diffraction limit using multiphoton W entangled states

    Energy Technology Data Exchange (ETDEWEB)

    Wen Jianming, E-mail: jianming.wen@gmail.co [National Laboratory of Solid State Microstructures and Department of Physics, Nanjing University, Nanjing 210093 (China); Department of Physics, University of Arkansas, Fayetteville, AR 72701 (United States); Du, Shengwang [Department of Physics, Hong Kong University of Science and Technology, Clear Bay (Hong Kong); Xiao Min [National Laboratory of Solid State Microstructures and Department of Physics, Nanjing University, Nanjing 210093 (China); Department of Physics, University of Arkansas, Fayetteville, AR 72701 (United States); School of Modern Engineering and Applied Science, Nanjing University, Nanjing 210093 (China)

    2010-08-23

    Using multiphoton entangled states, we demonstrate improving spatial imaging resolution beyond the Rayleigh diffraction limit in the quantum imaging process. In particular, we examine resolution enhancement using triphoton W state and a factor of 2 is achievable as with the use of the Greenberger-Horne-Zeilinger state, compared to using a classical-light source.

  4. High resolution Cerenkov light imaging of induced positron distribution in proton therapy

    Energy Technology Data Exchange (ETDEWEB)

    Yamamoto, Seiichi, E-mail: s-yama@met.nagoya-u.ac.jp; Fujii, Kento; Morishita, Yuki; Okumura, Satoshi; Komori, Masataka [Radiological and Medical Laboratory Sciences, Nagoya University Graduate School of Medicine, Aichi 461-8673 (Japan); Toshito, Toshiyuki [Department of Proton Therapy Physics, Nagoya Proton Therapy Center, Nagoya City West Medical Center, Aichi 462-8508 (Japan)

    2014-11-01

    Purpose: In proton therapy, imaging of the positron distribution produced by fragmentation during or soon after proton irradiation is a useful method to monitor the proton range. Although positron emission tomography (PET) is typically used for this imaging, its spatial resolution is limited. Cerenkov light imaging is a new molecular imaging technology that detects the visible photons that are produced from high-speed electrons using a high sensitivity optical camera. Because its inherent spatial resolution is much higher than PET, the authors can measure more precise information of the proton-induced positron distribution with Cerenkov light imaging technology. For this purpose, they conducted Cerenkov light imaging of induced positron distribution in proton therapy. Methods: First, the authors evaluated the spatial resolution of our Cerenkov light imaging system with a {sup 22}Na point source for the actual imaging setup. Then the transparent acrylic phantoms (100 × 100 × 100 mm{sup 3}) were irradiated with two different proton energies using a spot scanning proton therapy system. Cerenkov light imaging of each phantom was conducted using a high sensitivity electron multiplied charge coupled device (EM-CCD) camera. Results: The Cerenkov light’s spatial resolution for the setup was 0.76 ± 0.6 mm FWHM. They obtained high resolution Cerenkov light images of the positron distributions in the phantoms for two different proton energies and made fused images of the reference images and the Cerenkov light images. The depths of the positron distribution in the phantoms from the Cerenkov light images were almost identical to the simulation results. The decay curves derived from the region-of-interests (ROIs) set on the Cerenkov light images revealed that Cerenkov light images can be used for estimating the half-life of the radionuclide components of positrons. Conclusions: High resolution Cerenkov light imaging of proton-induced positron distribution was possible. The

  5. High resolution Cerenkov light imaging of induced positron distribution in proton therapy

    International Nuclear Information System (INIS)

    Yamamoto, Seiichi; Fujii, Kento; Morishita, Yuki; Okumura, Satoshi; Komori, Masataka; Toshito, Toshiyuki

    2014-01-01

    Purpose: In proton therapy, imaging of the positron distribution produced by fragmentation during or soon after proton irradiation is a useful method to monitor the proton range. Although positron emission tomography (PET) is typically used for this imaging, its spatial resolution is limited. Cerenkov light imaging is a new molecular imaging technology that detects the visible photons that are produced from high-speed electrons using a high sensitivity optical camera. Because its inherent spatial resolution is much higher than PET, the authors can measure more precise information of the proton-induced positron distribution with Cerenkov light imaging technology. For this purpose, they conducted Cerenkov light imaging of induced positron distribution in proton therapy. Methods: First, the authors evaluated the spatial resolution of our Cerenkov light imaging system with a 22 Na point source for the actual imaging setup. Then the transparent acrylic phantoms (100 × 100 × 100 mm 3 ) were irradiated with two different proton energies using a spot scanning proton therapy system. Cerenkov light imaging of each phantom was conducted using a high sensitivity electron multiplied charge coupled device (EM-CCD) camera. Results: The Cerenkov light’s spatial resolution for the setup was 0.76 ± 0.6 mm FWHM. They obtained high resolution Cerenkov light images of the positron distributions in the phantoms for two different proton energies and made fused images of the reference images and the Cerenkov light images. The depths of the positron distribution in the phantoms from the Cerenkov light images were almost identical to the simulation results. The decay curves derived from the region-of-interests (ROIs) set on the Cerenkov light images revealed that Cerenkov light images can be used for estimating the half-life of the radionuclide components of positrons. Conclusions: High resolution Cerenkov light imaging of proton-induced positron distribution was possible. The authors

  6. How nonlinear optics can merge interferometry for high resolution imaging

    Science.gov (United States)

    Ceus, D.; Reynaud, F.; Tonello, A.; Delage, L.; Grossard, L.

    2017-11-01

    High resolution stellar interferometers are very powerful efficient instruments to get a better knowledge of our Universe through the spatial coherence analysis of the light. For this purpose, the optical fields collected by each telescope Ti are mixed together. From the interferometric pattern, two expected information called the contrast Cij and the phase information φij are extracted. These information lead to the Vij, called the complex visibility, with Vij=Cijexp(jφij). For each telescope doublet TiTj, it is possible to get a complex visibility Vij. The Zernike Van Cittert theorem gives a relationship between the intensity distribution of the object observed and the complex visibility. The combination of the acquired complex visibilities and a reconstruction algorithm allows imaging reconstruction. To avoid lots of technical difficulties related to infrared optics (components transmission, thermal noises, thermal cooling…), our team proposes to explore the possibility of using nonlinear optical techniques. This is a promising alternative detection technique for detecting infrared optical signals. This way, we experimentally demonstrate that frequency conversion does not result in additional bias on the interferometric data supplied by a stellar interferometer. In this presentation, we report on wavelength conversion of the light collected by each telescope from the infrared domain to the visible. The interferometric pattern is observed in the visible domain with our, so called, upconversion interferometer. Thereby, one can benefit from mature optical components mainly used in optical telecommunications (waveguide, coupler, multiplexer…) and efficient low-noise detection schemes up to the single-photon counting level.

  7. Rearranging the lenslet array of the compact passive interference imaging system with high resolution

    Science.gov (United States)

    Liu, Gang; Wen, Desheng; Song, Zongxi

    2017-10-01

    With the development of aeronautics and astronautics, higher resolution requirement of the telescope was necessary. However, the increase in resolution of conventional telescope required larger apertures, whose size, weight and power consumption could be prohibitively expensive. This limited the further development of the telescope. This paper introduced a new imaging technology using interference—Compact Passive Interference Imaging Technology with High Resolution, and proposed a rearranging method for the arrangement of the lenslet array to obtain continuously object spatial frequency.

  8. A tilted fiber-optic plate coupled CCD detector for high resolution neutron imaging

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jongyul; Cho, Gyuseong [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Kim, Jongyul; Hwy, Limchang; Kim, Taejoo; Lee, Kyehong [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Lee, Seungwook [Pusan National Univ., Pusan (Korea, Republic of)

    2013-05-15

    One of these efforts is that a tilted scintillator geometry and lens coupled CCD detector for neutron imaging system were used to improve spatial resolution in one dimension. The increased spatial resolution in one dimension was applied to fuel cell study. However, a lens coupled CCD detector has lower sensitivity than a fiber-optic plate coupled CCD detector due to light loss. In this research, a tilted detector using fiber-optic plate coupled CCD detector was developed to improve resolution and sensitivity. In addition, a tilted detector can prevent an image sensor from direct radiation damage. Neutron imaging has been used for fuel cell study, lithium ion battery study, and many scientific applications. High quality neutron imaging is demanded for more detailed studies of applications, and spatial resolution should be considered to get high quality neutron imaging. Therefore, there were many efforts to improve spatial resolution.

  9. Super-resolution convolutional neural network for the improvement of the image quality of magnified images in chest radiographs

    Science.gov (United States)

    Umehara, Kensuke; Ota, Junko; Ishimaru, Naoki; Ohno, Shunsuke; Okamoto, Kentaro; Suzuki, Takanori; Shirai, Naoki; Ishida, Takayuki

    2017-02-01

    Single image super-resolution (SR) method can generate a high-resolution (HR) image from a low-resolution (LR) image by enhancing image resolution. In medical imaging, HR images are expected to have a potential to provide a more accurate diagnosis with the practical application of HR displays. In recent years, the super-resolution convolutional neural network (SRCNN), which is one of the state-of-the-art deep learning based SR methods, has proposed in computer vision. In this study, we applied and evaluated the SRCNN scheme to improve the image quality of magnified images in chest radiographs. For evaluation, a total of 247 chest X-rays were sampled from the JSRT database. The 247 chest X-rays were divided into 93 training cases with non-nodules and 152 test cases with lung nodules. The SRCNN was trained using the training dataset. With the trained SRCNN, the HR image was reconstructed from the LR one. We compared the image quality of the SRCNN and conventional image interpolation methods, nearest neighbor, bilinear and bicubic interpolations. For quantitative evaluation, we measured two image quality metrics, peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). In the SRCNN scheme, PSNR and SSIM were significantly higher than those of three interpolation methods (pmethods without any obvious artifacts. These preliminary results indicate that the SRCNN scheme significantly outperforms conventional interpolation algorithms for enhancing image resolution and that the use of the SRCNN can yield substantial improvement of the image quality of magnified images in chest radiographs.

  10. Crowdsourcing Rapid Assessment of Collapsed Buildings Early after the Earthquake Based on Aerial Remote Sensing Image: A Case Study of Yushu Earthquake

    Directory of Open Access Journals (Sweden)

    Shuai Xie

    2016-09-01

    Full Text Available Remote sensing (RS images play a significant role in disaster emergency response. Web2.0 changes the way data are created, making it possible for the public to participate in scientific issues. In this paper, an experiment is designed to evaluate the reliability of crowdsourcing buildings collapse assessment in the early time after an earthquake based on aerial remote sensing image. The procedure of RS data pre-processing and crowdsourcing data collection is presented. A probabilistic model including maximum likelihood estimation (MLE, Bayes’ theorem and expectation-maximization (EM algorithm are applied to quantitatively estimate the individual error-rate and “ground truth” according to multiple participants’ assessment results. An experimental area of Yushu earthquake is provided to present the results contributed by participants. Following the results, some discussion is provided regarding accuracy and variation among participants. The features of buildings labeled as the same damage type are found highly consistent. This suggests that the building damage assessment contributed by crowdsourcing can be treated as reliable samples. This study shows potential for a rapid building collapse assessment through crowdsourcing and quantitatively inferring “ground truth” according to crowdsourcing data in the early time after the earthquake based on aerial remote sensing image.

  11. National Land Imaging Requirements (NLIR) Pilot Project summary report: summary of moderate resolution imaging user requirements

    Science.gov (United States)

    Vadnais, Carolyn; Stensaas, Gregory

    2014-01-01

    Under the National Land Imaging Requirements (NLIR) Project, the U.S. Geological Survey (USGS) is developing a functional capability to obtain, characterize, manage, maintain and prioritize all Earth observing (EO) land remote sensing user requirements. The goal is a better understanding of community needs that can be supported with land remote sensing resources, and a means to match needs with appropriate solutions in an effective and efficient way. The NLIR Project is composed of two components. The first component is focused on the development of the Earth Observation Requirements Evaluation System (EORES) to capture, store and analyze user requirements, whereas, the second component is the mechanism and processes to elicit and document the user requirements that will populate the EORES. To develop the second component, the requirements elicitation methodology was exercised and refined through a pilot project conducted from June to September 2013. The pilot project focused specifically on applications and user requirements for moderate resolution imagery (5–120 meter resolution) as the test case for requirements development. The purpose of this summary report is to provide a high-level overview of the requirements elicitation process that was exercised through the pilot project and an early analysis of the moderate resolution imaging user requirements acquired to date to support ongoing USGS sustainable land imaging study needs. The pilot project engaged a limited set of Federal Government users from the operational and research communities and therefore the information captured represents only a subset of all land imaging user requirements. However, based on a comparison of results, trends, and analysis, the pilot captured a strong baseline of typical applications areas and user needs for moderate resolution imagery. Because these results are preliminary and represent only a sample of users and application areas, the information from this report should only

  12. Portable multiwire proportional chamber imaging system for high resolution 125I imaging

    International Nuclear Information System (INIS)

    Lazewatsky, J.L.; Lanza, R.C.; Murray, B.W.; Bolon, C.; Burns, R.E.; Szulc, M.

    1976-01-01

    A dedicated multiwire proportional chamber system designed to image 125 I labeled venous thrombi is described. The chamber is filled with a Kr-Co 2 gas mixture at one atmosphere pressure and utilizes an externally mounted delay line readout. A pair of crossed x-ray grids form a collimator which yields an optimum system efficiency of 3.1 x 10 -4 for a fixed spatial resolution of 0.74 cm. The chamber is further designed to be lightweight and portable for in-hospital use

  13. Magnetoacoustic Imaging of Electrical Conductivity of Biological Tissues at a Spatial Resolution Better than 2 mm

    OpenAIRE

    Hu, Gang; He, Bin

    2011-01-01

    Magnetoacoustic tomography with magnetic induction (MAT-MI) is an emerging approach for noninvasively imaging electrical impedance properties of biological tissues. The MAT-MI imaging system measures ultrasound waves generated by the Lorentz force, having been induced by magnetic stimulation, which is related to the electrical conductivity distribution in tissue samples. MAT-MI promises to provide fine spatial resolution for biological tissue imaging as compared to ultrasound resolution. In t...

  14. Using Adobe Acrobat to create high-resolution line art images.

    Science.gov (United States)

    Woo, Hyoun Sik; Lee, Jeong Min

    2009-08-01

    The purpose of this article is to introduce a method for using Adobe Acrobat to make high-resolution and high-quality line art images. High-resolution and high-quality line art images for radiology journal submission can be generated using Adobe Acrobat as a steppingstone, and the customized PDF conversion settings can be used for converting hybrid images, including both bitmap and vector components.

  15. Extracting a Good Quality Frontal Face Image from a Low-Resolution Video Sequence

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Moeslund, Thomas B.

    2011-01-01

    Feeding low-resolution and low-quality images, from inexpensive surveillance cameras, to systems like, e.g., face recognition, produces erroneous and unstable results. Therefore, there is a need for a mechanism to bridge the gap between on one hand low-resolution and low-quality images......, we use a learning-based super-resolution algorithm applied to the result of the reconstruction-based part to improve the quality by another factor of two. This results in an improvement factor of four for the entire system. The proposed system has been tested on 122 low-resolution sequences from two...... different databases. The experimental results show that the proposed system can indeed produce a high-resolution and good quality frontal face image from low-resolution video sequences....

  16. High-resolution MR imaging of wrist cartilage

    International Nuclear Information System (INIS)

    Rominger, M.B.; Bernreuter, W.K.; Listinsky, J.J.; Lee, D.H.; Kenney, P.J.; Colgin, S.L.

    1991-01-01

    This paper reports that cartilage is an important prognostic factor in arthritis. MR imaging can demonstrate both articular cartilage and subchondral bone. Our purpose was to compare various sequences, for wrist cartilage imaging and determine how extensive damage must be before it is detectable with MR imaging. Six cadaver wrists were imaged before and after arthroscopic cartilage injury (coronal and axial T1- and T2-weighted SE sequences, 3-mm sections; SPGR 45 degrees flip angle volume images with fat saturation. 1.2-mm sections; plus T1-weighted coronal images with fat saturation after injury; General Electric Signa, 1.5 T, with transmit-receive extremity coil). Twenty-two defects were created arthroscopically. Five normal volunteers were imaged for comparison. The greatest contrast among bone, cartilage, and synovial fluid was achieved with T1-weighted fat-suppressed SE image and SPGR. Gradient-recalled volume sequences generated very thin sections but were susceptible to artifact

  17. Linearized inversion frameworks toward high-resolution seismic imaging

    KAUST Repository

    Aldawood, Ali

    2016-01-01

    installed along the earth surface or down boreholes. Seismic imaging is a powerful tool to map these reflected and scattered energy back to their subsurface scattering or reflection points. Seismic imaging is conventionally based on the single

  18. Developpement of an original aerial-based inventory method: first steps towards the use of mini Unmanned Areal Vehicle in elephant inventory

    OpenAIRE

    Lisein, Jonathan; Vermeulen, Cédric; Bouché, Philippe; Lejeune, Philippe

    2012-01-01

    This research aims at developping a new methodology for counting large mammals by means of an unmanned aerial vehicle. Test flights have been performed in the game ranch of Nazinga (Burkina Faso) during the month of february 2012. Aerial images shows that elephant detection is quite feasible. The systems still requires a lot of improvements in order to be able to cover bigger surfaces for a given pixels resolution. Nevertheless, this method seems very promissing and could advantageously repla...

  19. Textural Segmentation of High-Resolution Sidescan Sonar Images

    National Research Council Canada - National Science Library

    Kalcic, Maria; Bibee, Dale

    1995-01-01

    .... The high resolution of the 455 kHz sonar imagery also provides much information about the surficial bottom sediments, however their acoustic scattering properties are not well understood at high frequencies...

  20. Multiband super-resolution imaging of graded-index photonic crystal flat lens

    Science.gov (United States)

    Xie, Jianlan; Wang, Junzhong; Ge, Rui; Yan, Bei; Liu, Exian; Tan, Wei; Liu, Jianjun

    2018-05-01

    Multiband super-resolution imaging of point source is achieved by a graded-index photonic crystal flat lens. With the calculations of six bands in common photonic crystal (CPC) constructed with scatterers of different refractive indices, it can be found that the super-resolution imaging of point source can be realized by different physical mechanisms in three different bands. In the first band, the imaging of point source is based on far-field condition of spherical wave while in the second band, it is based on the negative effective refractive index and exhibiting higher imaging quality than that of the CPC. However, in the fifth band, the imaging of point source is mainly based on negative refraction of anisotropic equi-frequency surfaces. The novel method of employing different physical mechanisms to achieve multiband super-resolution imaging of point source is highly meaningful for the field of imaging.

  1. Adapting astronomical source detection software to help detect animals in thermal images obtained by unmanned aerial systems

    Science.gov (United States)

    Longmore, S. N.; Collins, R. P.; Pfeifer, S.; Fox, S. E.; Mulero-Pazmany, M.; Bezombes, F.; Goodwind, A.; de Juan Ovelar, M.; Knapen, J. H.; Wich, S. A.

    2017-02-01

    In this paper we describe an unmanned aerial system equipped with a thermal-infrared camera and software pipeline that we have developed to monitor animal populations for conservation purposes. Taking a multi-disciplinary approach to tackle this problem, we use freely available astronomical source detection software and the associated expertise of astronomers, to efficiently and reliably detect humans and animals in aerial thermal-infrared footage. Combining this astronomical detection software with existing machine learning algorithms into a single, automated, end-to-end pipeline, we test the software using aerial video footage taken in a controlled, field-like environment. We demonstrate that the pipeline works reliably and describe how it can be used to estimate the completeness of different observational datasets to objects of a given type as a function of height, observing conditions etc. - a crucial step in converting video footage to scientifically useful information such as the spatial distribution and density of different animal species. Finally, having demonstrated the potential utility of the system, we describe the steps we are taking to adapt the system for work in the field, in particular systematic monitoring of endangered species at National Parks around the world.

  2. Super-resolution imaging of subcortical white matter using stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI)

    Science.gov (United States)

    Hainsworth, A. H.; Lee, S.; Patel, A.; Poon, W. W.; Knight, A. E.

    2018-01-01

    Aims The spatial resolution of light microscopy is limited by the wavelength of visible light (the ‘diffraction limit’, approximately 250 nm). Resolution of sub-cellular structures, smaller than this limit, is possible with super resolution methods such as stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI). We aimed to resolve subcellular structures (axons, myelin sheaths and astrocytic processes) within intact white matter, using STORM and SOFI. Methods Standard cryostat-cut sections of subcortical white matter from donated human brain tissue and from adult rat and mouse brain were labelled, using standard immunohistochemical markers (neurofilament-H, myelin-associated glycoprotein, glial fibrillary acidic protein, GFAP). Image sequences were processed for STORM (effective pixel size 8–32 nm) and for SOFI (effective pixel size 80 nm). Results In human, rat and mouse, subcortical white matter high-quality images for axonal neurofilaments, myelin sheaths and filamentous astrocytic processes were obtained. In quantitative measurements, STORM consistently underestimated width of axons and astrocyte processes (compared with electron microscopy measurements). SOFI provided more accurate width measurements, though with somewhat lower spatial resolution than STORM. Conclusions Super resolution imaging of intact cryo-cut human brain tissue is feasible. For quantitation, STORM can under-estimate diameters of thin fluorescent objects. SOFI is more robust. The greatest limitation for super-resolution imaging in brain sections is imposed by sample preparation. We anticipate that improved strategies to reduce autofluorescence and to enhance fluorophore performance will enable rapid expansion of this approach. PMID:28696566

  3. Super-resolution imaging of subcortical white matter using stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI).

    Science.gov (United States)

    Hainsworth, A H; Lee, S; Foot, P; Patel, A; Poon, W W; Knight, A E

    2017-07-11

    The spatial resolution of light microscopy is limited by the wavelength of visible light (the 'diffraction limit', approximately 250 nm). Resolution of sub-cellular structures, smaller than this limit, is possible with super resolution methods such as stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI). We aimed to resolve subcellular structures (axons, myelin sheaths and astrocytic processes) within intact white matter, using STORM and SOFI. Standard cryostat-cut sections of subcortical white matter from donated human brain tissue and from adult rat and mouse brain were labelled, using standard immunohistochemical markers (neurofilament-H, myelin-associated glycoprotein, glial fibrillary acidic protein, GFAP). Image sequences were processed for STORM (effective pixel size 8-32 nm) and for SOFI (effective pixel size 80 nm). In human, rat and mouse, subcortical white matter high-quality images for axonal neurofilaments, myelin sheaths and filamentous astrocytic processes were obtained. In quantitative measurements, STORM consistently underestimated width of axons and astrocyte processes (compared with electron microscopy measurements). SOFI provided more accurate width measurements, though with somewhat lower spatial resolution than STORM. Super resolution imaging of intact cryo-cut human brain tissue is feasible. For quantitation, STORM can under-estimate diameters of thin fluorescent objects. SOFI is more robust. The greatest limitation for super-resolution imaging in brain sections is imposed by sample preparation. We anticipate that improved strategies to reduce autofluorescence and to enhance fluorophore performance will enable rapid expansion of this approach. © 2017 British Neuropathological Society.

  4. Facial identification in very low-resolution images simulating prosthetic vision.

    Science.gov (United States)

    Chang, M H; Kim, H S; Shin, J H; Park, K S

    2012-08-01

    Familiar facial identification is important to blind or visually impaired patients and can be achieved using a retinal prosthesis. Nevertheless, there are limitations in delivering the facial images with a resolution sufficient to distinguish facial features, such as eyes and nose, through multichannel electrode arrays used in current visual prostheses. This study verifies the feasibility of familiar facial identification under low-resolution prosthetic vision and proposes an edge-enhancement method to deliver more visual information that is of higher quality. We first generated a contrast-enhanced image and an edge image by applying the Sobel edge detector and blocked each of them by averaging. Then, we subtracted the blocked edge image from the blocked contrast-enhanced image and produced a pixelized image imitating an array of phosphenes. Before subtraction, every gray value of the edge images was weighted as 50% (mode 2), 75% (mode 3) and 100% (mode 4). In mode 1, the facial image was blocked and pixelized with no further processing. The most successful identification was achieved with mode 3 at every resolution in terms of identification index, which covers both accuracy and correct response time. We also found that the subjects recognized a distinctive face especially more accurately and faster than the other given facial images even under low-resolution prosthetic vision. Every subject could identify familiar faces even in very low-resolution images. And the proposed edge-enhancement method seemed to contribute to intermediate-stage visual prostheses.

  5. Effects of Resolution, Range, and Image Contrast on Target Acquisition Performance.

    Science.gov (United States)

    Hollands, Justin G; Terhaar, Phil; Pavlovic, Nada J

    2018-05-01

    We sought to determine the joint influence of resolution, target range, and image contrast on the detection and identification of targets in simulated naturalistic scenes. Resolution requirements for target acquisition have been developed based on threshold values obtained using imaging systems, when target range was fixed, and image characteristics were determined by the system. Subsequent work has examined the influence of factors like target range and image contrast on target acquisition. We varied the resolution and contrast of static images in two experiments. Participants (soldiers) decided whether a human target was located in the scene (detection task) or whether a target was friendly or hostile (identification task). Target range was also varied (50-400 m). In Experiment 1, 30 participants saw color images with a single target exemplar. In Experiment 2, another 30 participants saw monochrome images containing different target exemplars. The effects of target range and image contrast were qualitatively different above and below 6 pixels per meter of target for both tasks in both experiments. Target detection and identification performance were a joint function of image resolution, range, and contrast for both color and monochrome images. The beneficial effects of increasing resolution for target acquisition performance are greater for closer (larger) targets.

  6. Target-oriented retrieval of subsurface wave fields - Pushing the resolution limits in seismic imaging

    Science.gov (United States)

    Vasconcelos, Ivan; Ozmen, Neslihan; van der Neut, Joost; Cui, Tianci

    2017-04-01

    Travelling wide-bandwidth seismic waves have long been used as a primary tool in exploration seismology because they can probe the subsurface over large distances, while retaining relatively high spatial resolution. The well-known Born resolution limit often seems to be the lower bound on spatial imaging resolution in real life examples. In practice, data acquisition cost, time constraints and other factors can worsen the resolution achieved by wavefield imaging. Could we obtain images whose resolution beats the Born limits? Would it be practical to achieve it, and what are we missing today to achieve this? In this talk, we will cover aspects of linear and nonlinear seismic imaging to understand elements that play a role in obtaining "super-resolved" seismic images. New redatuming techniques, such as the Marchenko method, enable the retrieval of subsurface fields that include multiple scattering interactions, while requiring relatively little knowledge of model parameters. Together with new concepts in imaging, such as Target-Enclosing Extended Images, these new redatuming methods enable new targeted imaging frameworks. We will make a case as to why target-oriented approaches to reconstructing subsurface-domain wavefields from surface data may help in increasing the resolving power of seismic imaging, and in pushing the limits on parameter estimation. We will illustrate this using a field data example. Finally, we will draw connections between seismic and other imaging modalities, and discuss how this framework could be put to use in other applications

  7. High resolution PET breast imager with improved detection efficiency

    Science.gov (United States)

    Majewski, Stanislaw

    2010-06-08

    A highly efficient PET breast imager for detecting lesions in the entire breast including those located close to the patient's chest wall. The breast imager includes a ring of imaging modules surrounding the imaged breast. Each imaging module includes a slant imaging light guide inserted between a gamma radiation sensor and a photodetector. The slant light guide permits the gamma radiation sensors to be placed in close proximity to the skin of the chest wall thereby extending the sensitive region of the imager to the base of the breast. Several types of photodetectors are proposed for use in the detector modules, with compact silicon photomultipliers as the preferred choice, due to its high compactness. The geometry of the detector heads and the arrangement of the detector ring significantly reduce dead regions thereby improving detection efficiency for lesions located close to the chest wall.

  8. Finsler geometry on higher order tensor fields and applications to high angular resolution diffusion imaging

    NARCIS (Netherlands)

    Astola, L.J.; Florack, L.M.J.

    2011-01-01

    We study 3D-multidirectional images, using Finsler geometry. The application considered here is in medical image analysis, specifically in High Angular Resolution Diffusion Imaging (HARDI) (Tuch et al. in Magn. Reson. Med. 48(6):1358–1372, 2004) of the brain. The goal is to reveal the architecture

  9. Finsler geometry on higher order tensor fields and applications to high angular resolution diffusion imaging.

    NARCIS (Netherlands)

    Astola, L.; Florack, L.

    2011-01-01

    We study 3D-multidirectional images, using Finsler geometry. The application considered here is in medical image analysis, specifically in High Angular Resolution Diffusion Imaging (HARDI) (Tuch et al. in Magn. Reson. Med. 48(6):1358–1372, 2004) of the brain. The goal is to reveal the architecture

  10. Finsler geometry on higher order tensor fields and applications to high angular resolution diffusion imaging

    NARCIS (Netherlands)

    Astola, L.J.; Florack, L.M.J.

    2010-01-01

    We study 3D-multidirectional images, using Finsler geometry. The application considered here is in medical image analysis, specifically in High Angular Resolution Diffusion Imaging (HARDI) [24] of the brain. The goal is to reveal the architecture of the neural fibers in brain white matter. To the

  11. Super-resolution processing for pulsed neutron imaging system using a high-speed camera

    International Nuclear Information System (INIS)

    Ishizuka, Ken; Kai, Tetsuya; Shinohara, Takenao; Segawa, Mariko; Mochiki, Koichi

    2015-01-01

    Super-resolution and center-of-gravity processing improve the resolution of neutron-transmitted images. These processing methods calculate the center-of-gravity pixel or sub-pixel of the neutron point converted into light by a scintillator. The conventional neutron-transmitted image is acquired using a high-speed camera by integrating many frames when a transmitted image with one frame is not provided. It succeeds in acquiring the transmitted image and calculating a spectrum by integrating frames of the same energy. However, because a high frame rate is required for neutron resonance absorption imaging, the number of pixels of the transmitted image decreases, and the resolution decreases to the limit of the camera performance. Therefore, we attempt to improve the resolution by integrating the frames after applying super-resolution or center-of-gravity processing. The processed results indicate that center-of-gravity processing can be effective in pulsed-neutron imaging with a high-speed camera. In addition, the results show that super-resolution processing is effective indirectly. A project to develop a real-time image data processing system has begun, and this system will be used at J-PARC in JAEA. (author)

  12. High resolution axicon-based endoscopic FD OCT imaging with a large depth range

    Science.gov (United States)

    Lee, Kye-Sung; Hurley, William; Deegan, John; Dean, Scott; Rolland, Jannick P.

    2010-02-01

    Endoscopic imaging in tubular structures, such as the tracheobronchial tree, could benefit from imaging optics with an extended depth of focus (DOF). This optics could accommodate for varying sizes of tubular structures across patients and along the tree within a single patient. In the paper, we demonstrate an extended DOF without sacrificing resolution showing rotational images in biological tubular samples with 2.5 μm axial resolution, 10 ìm lateral resolution, and > 4 mm depth range using a custom designed probe.

  13. Detection of pulmonary nodules on lung X-ray images. Studies on multi-resolutional filter and energy subtraction images

    International Nuclear Information System (INIS)

    Sawada, Akira; Sato, Yoshinobu; Kido, Shoji; Tamura, Shinichi

    1999-01-01

    The purpose of this work is to prove the effectiveness of an energy subtraction image for the detection of pulmonary nodules and the effectiveness of multi-resolutional filter on an energy subtraction image to detect pulmonary nodules. Also we study influential factors to the accuracy of detection of pulmonary nodules from viewpoints of types of images, types of digital filters and types of evaluation methods. As one type of images, we select an energy subtraction image, which removes bones such as ribs from the conventional X-ray image by utilizing the difference of X-ray absorption ratios at different energy between bones and soft tissue. Ribs and vessels are major causes of CAD errors in detection of pulmonary nodules and many researches have tried to solve this problem. So we select conventional X-ray images and energy subtraction X-ray images as types of images, and at the same time select ∇ 2 G (Laplacian of Guassian) filter, Min-DD (Minimum Directional Difference) filter and our multi-resolutional filter as types of digital filters. Also we select two evaluation methods and prove the effectiveness of an energy subtraction image, the effectiveness of Min-DD filter on a conventional X-ray image and the effectiveness of multi-resolutional filter on an energy subtraction image. (author)

  14. Influence of the interaction volume on the kinetic energy resolution of a velocity map imaging spectrometer

    International Nuclear Information System (INIS)

    Zhang Peng; Feng Zheng-Peng; Luo Si-Qiang; Wang Zhe

    2016-01-01

    We investigate the influence of the interaction volume on the energy resolution of a velocity map imaging spectrometer. The simulation results show that the axial interaction size has a significant influence on the resolution. This influence is increased for a higher kinetic energy. We further show that the radial interaction size has a minor influence on the energy resolution for the electron or ion with medium energy, but it is crucial for the resolution of the electron or ion with low kinetic energy. By tracing the flight trajectories we show how the electron or ion energy resolution is influenced by the interaction size. (paper)

  15. Droplet Image Super Resolution Based on Sparse Representation and Kernel Regression

    Science.gov (United States)

    Zou, Zhenzhen; Luo, Xinghong; Yu, Qiang

    2018-05-01

    Microgravity and containerless conditions, which are produced via electrostatic levitation combined with a drop tube, are important when studying the intrinsic properties of new metastable materials. Generally, temperature and image sensors can be used to measure the changes of sample temperature, morphology and volume. Then, the specific heat, surface tension, viscosity changes and sample density can be obtained. Considering that the falling speed of the material sample droplet is approximately 31.3 m/s when it reaches the bottom of a 50-meter-high drop tube, a high-speed camera with a collection rate of up to 106 frames/s is required to image the falling droplet. However, at the high-speed mode, very few pixels, approximately 48-120, will be obtained in each exposure time, which results in low image quality. Super-resolution image reconstruction is an algorithm that provides finer details than the sampling grid of a given imaging device by increasing the number of pixels per unit area in the image. In this work, we demonstrate the application of single image-resolution reconstruction in the microgravity and electrostatic levitation for the first time. Here, using the image super-resolution method based on sparse representation, a low-resolution droplet image can be reconstructed. Employed Yang's related dictionary model, high- and low-resolution image patches were combined with dictionary training, and high- and low-resolution-related dictionaries were obtained. The online double-sparse dictionary training algorithm was used in the study of related dictionaries and overcome the shortcomings of the traditional training algorithm with small image patch. During the stage of image reconstruction, the algorithm of kernel regression is added, which effectively overcomes the shortcomings of the Yang image's edge blurs.

  16. Super resolution reconstruction of μ-CT image of rock sample using neighbour embedding algorithm

    Science.gov (United States)

    Wang, Yuzhu; Rahman, Sheik S.; Arns, Christoph H.

    2018-03-01

    X-ray computed tomography (μ-CT) is considered to be the most effective way to obtain the inner structure of rock sample without destructions. However, its limited resolution hampers its ability to probe sub-micro structures which is critical for flow transportation of rock sample. In this study, we propose an innovative methodology to improve the resolution of μ-CT image using neighbour embedding algorithm where low frequency information is provided by μ-CT image itself while high frequency information is supplemented by high resolution scanning electron microscopy (SEM) image. In order to obtain prior for reconstruction, a large number of image patch pairs contain high- and low- image patches are extracted from the Gaussian image pyramid generated by SEM image. These image patch pairs contain abundant information about tomographic evolution of local porous structures under different resolution spaces. Relying on the assumption of self-similarity of porous structure, this prior information can be used to supervise the reconstruction of high resolution μ-CT image effectively. The experimental results show that the proposed method is able to achieve the state-of-the-art performance.

  17. Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network.

    Science.gov (United States)

    Du, Xiaofeng; Qu, Xiaobo; He, Yifan; Guo, Di

    2018-03-06

    Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods.

  18. Pan-neuronal calcium imaging with cellular resolution in freely swimming zebrafish.

    Science.gov (United States)

    Kim, Dal Hyung; Kim, Jungsoo; Marques, João C; Grama, Abhinav; Hildebrand, David G C; Gu, Wenchao; Li, Jennifer M; Robson, Drew N

    2017-11-01

    Calcium imaging with cellular resolution typically requires an animal to be tethered under a microscope, which substantially restricts the range of behaviors that can be studied. To expand the behavioral repertoire amenable to imaging, we have developed a tracking microscope that enables whole-brain calcium imaging with cellular resolution in freely swimming larval zebrafish. This microscope uses infrared imaging to track a target animal in a behavior arena. On the basis of the predicted trajectory of the animal, we applied optimal control theory to a motorized stage system to cancel brain motion in three dimensions. We combined this motion-cancellation system with differential illumination focal filtering, a variant of HiLo microscopy, which enabled us to image the brain of a freely swimming larval zebrafish for more than an hour. This work expands the repertoire of natural behaviors that can be studied with cellular-resolution calcium imaging to potentially include spatial navigation, social behavior, feeding and reward.

  19. Improved Resolution Optical Time Stretch Imaging Based on High Efficiency In-Fiber Diffraction.

    Science.gov (United States)

    Wang, Guoqing; Yan, Zhijun; Yang, Lei; Zhang, Lin; Wang, Chao

    2018-01-12

    Most overlooked challenges in ultrafast optical time stretch imaging (OTSI) are sacrificed spatial resolution and higher optical loss. These challenges are originated from optical diffraction devices used in OTSI, which encode image into spectra of ultrashort optical pulses. Conventional free-space diffraction gratings, as widely used in existing OTSI systems, suffer from several inherent drawbacks: limited diffraction efficiency in a non-Littrow configuration due to inherent zeroth-order reflection, high coupling loss between free-space gratings and optical fibers, bulky footprint, and more importantly, sacrificed imaging resolution due to non-full-aperture illumination for individual wavelengths. Here we report resolution-improved and diffraction-efficient OTSI using in-fiber diffraction for the first time to our knowledge. The key to overcome the existing challenges is a 45° tilted fiber grating (TFG), which serves as a compact in-fiber diffraction device offering improved diffraction efficiency (up to 97%), inherent compatibility with optical fibers, and improved imaging resolution owning to almost full-aperture illumination for all illumination wavelengths. 50 million frames per second imaging of fast moving object at 46 m/s with improved imaging resolution has been demonstrated. This conceptually new in-fiber diffraction design opens the way towards cost-effective, compact and high-resolution OTSI systems for image-based high-throughput detection and measurement.

  20. High-resolution storage phosphor imaging of the chest: Comparison with conventional screen-film systems

    International Nuclear Information System (INIS)

    Fuhrman, C.R.; Good, B.; Feist, J.; Gur, D.; Darby, J.

    1987-01-01

    An experimental high-resolution storage phosphor imaging system (Eastman Kodak) has been used to evaluate the image quality and impact on diagnostic interpretation of storage phosphor images relative to conventional screen-film images of the same patients. The elements of the system include a high-resolution laser scanner (4K X 5K X 12 bit); an image processing system; and a high-resolution (4K X 5K X 12 bit) laser printer. Each case was digitally printed onto film in two different formats: a full-size (14 X 14-inch) and a half-size format of four processed, minified images (7 X 7-inches each). The multiformat image includes an original, an unsharp-masked, a reversed (black bone) unsharp-masked, and a high-contrast unsharp-masked image. The results of this preliminary study (11 cases, eight readers) clearly indicate that after minimal adjustment, radiologists do not object to making diagnoses from minified images. Unsharp masked images were considered preferable to unprocessed images, and processed storage phosphor images were rated significantly better than conventional film images

  1. Experimental and rendering-based investigation of laser radar cross sections of small unmanned aerial vehicles

    Science.gov (United States)

    Laurenzis, Martin; Bacher, Emmanuel; Christnacher, Frank

    2017-12-01

    Laser imaging systems are prominent candidates for detection and tracking of small unmanned aerial vehicles (UAVs) in current and future security scenarios. Laser reflection characteristics for laser imaging (e.g., laser gated viewing) of small UAVs are investigated to determine their laser radar cross section (LRCS) by analyzing the intensity distribution of laser reflection in high resolution images. For the first time, LRCSs are determined in a combined experimental and computational approaches by high resolution laser gated viewing and three-dimensional rendering. An optimized simple surface model is calculated taking into account diffuse and specular reflectance properties based on the Oren-Nayar and the Cook-Torrance reflectance models, respectively.

  2. A fast and automatic mosaic method for high-resolution satellite images

    Science.gov (United States)

    Chen, Hongshun; He, Hui; Xiao, Hongyu; Huang, Jing

    2015-12-01

    We proposed a fast and fully automatic mosaic method for high-resolution satellite images. First, the overlapped rectangle is computed according to geographical locations of the reference and mosaic images and feature points on both the reference and mosaic images are extracted by a scale-invariant feature transform (SIFT) algorithm only from the overlapped region. Then, the RANSAC method is used to match feature points of both images. Finally, the two images are fused into a seamlessly panoramic image by the simple linear weighted fusion method or other method. The proposed method is implemented in C++ language based on OpenCV and GDAL, and tested by Worldview-2 multispectral images with a spatial resolution of 2 meters. Results show that the proposed method can detect feature points efficiently and mosaic images automatically.

  3. Multiple-image hiding using super resolution reconstruction in high-frequency domains

    Science.gov (United States)

    Li, Xiao-Wei; Zhao, Wu-Xiang; Wang, Jun; Wang, Qiong-Hua

    2017-12-01

    In this paper, a robust multiple-image hiding method using the computer-generated integral imaging and the modified super-resolution reconstruction algorithm is proposed. In our work, the host image is first transformed into frequency domains by cellular automata (CA), to assure the quality of the stego-image, the secret images are embedded into the CA high-frequency domains. The proposed method has the following advantages: (1) robustness to geometric attacks because of the memory-distributed property of elemental images, (2) increasing quality of the reconstructed secret images as the scheme utilizes the modified super-resolution reconstruction algorithm. The simulation results show that the proposed multiple-image hiding method outperforms other similar hiding methods and is robust to some geometric attacks, e.g., Gaussian noise and JPEG compression attacks.

  4. Large-Scale Multi-Resolution Representations for Accurate Interactive Image and Volume Operations

    KAUST Repository

    Sicat, Ronell B.

    2015-11-25

    The resolutions of acquired image and volume data are ever increasing. However, the resolutions of commodity display devices remain limited. This leads to an increasing gap between data and display resolutions. To bridge this gap, the standard approach is to employ output-sensitive operations on multi-resolution data representations. Output-sensitive operations facilitate interactive applications since their required computations are proportional only to the size of the data that is visible, i.e., the output, and not the full size of the input. Multi-resolution representations, such as image mipmaps, and volume octrees, are crucial in providing these operations direct access to any subset of the data at any resolution corresponding to the output. Despite its widespread use, this standard approach has some shortcomings in three important application areas, namely non-linear image operations, multi-resolution volume rendering, and large-scale image exploration. This dissertation presents new multi-resolution representations for large-scale images and volumes that address these shortcomings. Standard multi-resolution representations require low-pass pre-filtering for anti- aliasing. However, linear pre-filters do not commute with non-linear operations. This becomes problematic when applying non-linear operations directly to any coarse resolution levels in standard representations. Particularly, this leads to inaccurate output when applying non-linear image operations, e.g., color mapping and detail-aware filters, to multi-resolution images. Similarly, in multi-resolution volume rendering, this leads to inconsistency artifacts which manifest as erroneous differences in rendering outputs across resolution levels. To address these issues, we introduce the sparse pdf maps and sparse pdf volumes representations for large-scale images and volumes, respectively. These representations sparsely encode continuous probability density functions (pdfs) of multi-resolution pixel

  5. High-resolution seismic imaging of the Sohagpur Gondwana basin ...

    Indian Academy of Sciences (India)

    The quality of the high-resolution seismic data depends mainly on the data ..... metric rift geometry. Based on the .... Biswas S K 2003 Regional tectonic framework of the .... Sheth H C, Ray J S, Ray R, Vanderkluysen L, Mahoney J. J, Kumar A ...

  6. Optimisation of the image resolution of a positron emission tomograph

    International Nuclear Information System (INIS)

    Ziemons, K.

    1993-10-01

    The resolution and the respective signal-to-noise ratios of reconstructed pictures were a point of main interest of the work for optimisation of PET systems. Monte-Carlo modelling calculations were applied to derive possible improvements of the technical design or performance of the PET system. (DG) [de

  7. High Spectral Resolution, High Cadence, Imaging X-ray Microcalorimeters for Solar Physics - Phase 2 Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Microcalorimeter x-ray instruments are non-dispersive, high spectral resolution, broad-band, high cadence imaging spectrometers. We have been developing these...

  8. Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) Global Mapped Data

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth...

  9. Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Chlorophyll (CHL) Global Mapped Data

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth...

  10. Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index Land Reflectance Global Binned Data

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth...

  11. Gas scintillation glass GEM detector for high-resolution X-ray imaging and CT

    Energy Technology Data Exchange (ETDEWEB)

    Fujiwara, T., E-mail: fujiwara-t@aist.go.jp [Research Institute for Measurement and Analytical Instrumentation, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki 305-8568 (Japan); Mitsuya, Y. [Nuclear Professional School, The University of Tokyo, Tokai, Naka, Ibaraki 319-1188 (Japan); Fushie, T. [Radiment Lab. Inc., Setagaya, Tokyo 156-0044 (Japan); Murata, K.; Kawamura, A.; Koishikawa, A. [XIT Co., Naruse, Machida, Tokyo 194-0045 (Japan); Toyokawa, H. [Research Institute for Measurement and Analytical Instrumentation, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki 305-8568 (Japan); Takahashi, H. [Institute of Engineering Innovation, School of Engineering, The University of Tokyo, Bunkyo, Tokyo 113-8654 (Japan)

    2017-04-01

    A high-spatial-resolution X-ray-imaging gaseous detector has been developed with a single high-gas-gain glass gas electron multiplier (G-GEM), scintillation gas, and optical camera. High-resolution X-ray imaging of soft elements is performed with a spatial resolution of 281 µm rms and an effective area of 100×100 mm. In addition, high-resolution X-ray 3D computed tomography (CT) is successfully demonstrated with the gaseous detector. It shows high sensitivity to low-energy X-rays, which results in high-contrast radiographs of objects containing elements with low atomic numbers. In addition, the high yield of scintillation light enables fast X-ray imaging, which is an advantage for constructing CT images with low-energy X-rays.

  12. High resolution radio-imager for biology and micro-dosimetry

    International Nuclear Information System (INIS)

    Aubineau-Laniece, I.; Charon, Y.; Laniece, P.; Mastrippolito, R.; Pinot, L.; Valentin, L.

    1999-01-01

    We have developed a self triggered intensified CCD (STIC) for real time high spatial resolution a and b imaging. This device is, in particular, of great interest for quantitative autoradiography of radiolabeled biochemical species with low level activity. (authors)

  13. High-resolution satellite image segmentation using Hölder exponents

    Indian Academy of Sciences (India)

    Keywords. High resolution image; texture analysis; segmentation; IKONOS; Hölder exponent; cluster. ... are that. • it can be used as a tool to measure the roughness ... uses reinforcement learning to learn the reward values of ..... The numerical.

  14. Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Photosynthetically Available Radiation (PAR) Global Binned Data, reprocesing v2018

    Data.gov (United States)

    National Aeronautics and Space Administration — MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument aboard the Terra (EOS AM) and Aqua (EOS PM) satellites. Terra's orbit around the Earth...

  15. Ultra-High-Resolution Computed Tomography of the Lung: Image Quality of a Prototype Scanner

    OpenAIRE

    Kakinuma, Ryutaro; Moriyama, Noriyuki; Muramatsu, Yukio; Gomi, Shiho; Suzuki, Masahiro; Nagasawa, Hirobumi; Kusumoto, Masahiko; Aso, Tomohiko; Muramatsu, Yoshihisa; Tsuchida, Takaaki; Tsuta, Koji; Maeshima, Akiko Miyagi; Tochigi, Naobumi; Watanabe, Shun-ichi; Sugihara, Naoki

    2015-01-01

    Purpose: The image noise and image quality of a prototype ultra-high-resolution computed tomography (U-HRCT) scanner was evaluated and compared with those of conventional high-resolution CT (C-HRCT) scanners. Materials and Methods: This study was approved by the institutional review board. A U-HRCT scanner prototype with 0.25 mm × 4 rows and operating at 120 mAs was used. The C-HRCT images were obtained using a 0.5 mm × 16 or 0.5 mm × 64 detector-row CT scanner operating at 150 mAs. Images fr...

  16. Tablet disintegration studied by high-resolution real-time magnetic resonance imaging.

    OpenAIRE

    Quodbach, J.; Moussavi, A.; Tammer, R.; Frahm, J.; Kleinebudde, P.

    2014-01-01

    The present work employs recent advances in high-resolution real-time magnetic resonance imaging (MRI) to investigate the disintegration process of tablets containing disintegrants. A temporal resolution of 75 ms and a spatial resolution of 80 x 80 m with a section thickness of only 600 m were achieved. The histograms of MRI videos were quantitatively analyzed with MATLAB. The mechanisms of action of six commercially available disintegrants, the influence of relative tablet density, and the i...

  17. All-passive pixel super-resolution of time-stretch imaging

    Science.gov (United States)

    Chan, Antony C. S.; Ng, Ho-Cheung; Bogaraju, Sharat C. V.; So, Hayden K. H.; Lam, Edmund Y.; Tsia, Kevin K.

    2017-03-01

    Based on image encoding in a serial-temporal format, optical time-stretch imaging entails a stringent requirement of state-of-the-art fast data acquisition unit in order to preserve high image resolution at an ultrahigh frame rate — hampering the widespread utilities of such technology. Here, we propose a pixel super-resolution (pixel-SR) technique tailored for time-stretch imaging that preserves pixel resolution at a relaxed sampling rate. It harnesses the subpixel shifts between image frames inherently introduced by asynchronous digital sampling of the continuous time-stretch imaging process. Precise pixel registration is thus accomplished wi