WorldWideScience

Sample records for multiple sar images

  1. Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing

    Fan Zhang

    2016-04-01

    Full Text Available With the development of synthetic aperture radar (SAR technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO. However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

  2. Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing.

    Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin

    2016-04-07

    With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

  3. Polarimetric SAR Image Classification Using Multiple-feature Fusion and Ensemble Learning

    Sun Xun

    2016-12-01

    Full Text Available In this paper, we propose a supervised classification algorithm for Polarimetric Synthetic Aperture Radar (PolSAR images using multiple-feature fusion and ensemble learning. First, we extract different polarimetric features, including extended polarimetric feature space, Hoekman, Huynen, H/alpha/A, and fourcomponent scattering features of PolSAR images. Next, we randomly select two types of features each time from all feature sets to guarantee the reliability and diversity of later ensembles and use a support vector machine as the basic classifier for predicting classification results. Finally, we concatenate all prediction probabilities of basic classifiers as the final feature representation and employ the random forest method to obtain final classification results. Experimental results at the pixel and region levels show the effectiveness of the proposed algorithm.

  4. SAR image dataset of military ground targets with multiple poses for ATR

    Belloni, Carole; Balleri, Alessio; Aouf, Nabil; Merlet, Thomas; Le Caillec, Jean-Marc

    2017-10-01

    Automatic Target Recognition (ATR) is the task of automatically detecting and classifying targets. Recognition using Synthetic Aperture Radar (SAR) images is interesting because SAR images can be acquired at night and under any weather conditions, whereas optical sensors operating in the visible band do not have this capability. Existing SAR ATR algorithms have mostly been evaluated using the MSTAR dataset.1 The problem with the MSTAR is that some of the proposed ATR methods have shown good classification performance even when targets were hidden,2 suggesting the presence of a bias in the dataset. Evaluations of SAR ATR techniques are currently challenging due to the lack of publicly available data in the SAR domain. In this paper, we present a high resolution SAR dataset consisting of images of a set of ground military target models taken at various aspect angles, The dataset can be used for a fair evaluation and comparison of SAR ATR algorithms. We applied the Inverse Synthetic Aperture Radar (ISAR) technique to echoes from targets rotating on a turntable and illuminated with a stepped frequency waveform. The targets in the database consist of four variants of two 1.7m-long models of T-64 and T-72 tanks. The gun, the turret position and the depression angle are varied to form 26 different sequences of images. The emitted signal spanned the frequency range from 13 GHz to 18 GHz to achieve a bandwidth of 5 GHz sampled with 4001 frequency points. The resolution obtained with respect to the size of the model targets is comparable to typical values obtained using SAR airborne systems. Single polarized images (Horizontal-Horizontal) are generated using the backprojection algorithm.3 A total of 1480 images are produced using a 20° integration angle. The images in the dataset are organized in a suggested training and testing set to facilitate a standard evaluation of SAR ATR algorithms.

  5. A Fast Multiple Sampling Method for Low-Noise CMOS Image Sensors With Column-Parallel 12-bit SAR ADCs

    Min-Kyu Kim

    2015-12-01

    Full Text Available This paper presents a fast multiple sampling method for low-noise CMOS image sensor (CIS applications with column-parallel successive approximation register analog-to-digital converters (SAR ADCs. The 12-bit SAR ADC using the proposed multiple sampling method decreases the A/D conversion time by repeatedly converting a pixel output to 4-bit after the first 12-bit A/D conversion, reducing noise of the CIS by one over the square root of the number of samplings. The area of the 12-bit SAR ADC is reduced by using a 10-bit capacitor digital-to-analog converter (DAC with four scaled reference voltages. In addition, a simple up/down counter-based digital processing logic is proposed to perform complex calculations for multiple sampling and digital correlated double sampling. To verify the proposed multiple sampling method, a 256 × 128 pixel array CIS with 12-bit SAR ADCs was fabricated using 0.18 μm CMOS process. The measurement results shows that the proposed multiple sampling method reduces each A/D conversion time from 1.2 μs to 0.45 μs and random noise from 848.3 μV to 270.4 μV, achieving a dynamic range of 68.1 dB and an SNR of 39.2 dB.

  6. Multiple Input - Multiple Output (MIMO) SAR

    National Aeronautics and Space Administration — This effort will research and implement advanced Multiple-Input Multiple-Output (MIMO) Synthetic Aperture Radar (SAR) techniques which have the potential to improve...

  7. Bistatic SAR: Imagery & Image Products.

    Yocky, David A.; Wahl, Daniel E.; Jakowatz, Charles V,

    2014-10-01

    While typical SAR imaging employs a co-located (monostatic) RADAR transmitter and receiver, bistatic SAR imaging separates the transmitter and receiver locations. The transmitter and receiver geometry determines if the scattered signal is back scatter, forward scatter, or side scatter. The monostatic SAR image is backscatter. Therefore, depending on the transmitter/receiver collection geometry, the captured imagery may be quite different that that sensed at the monostatic SAR. This document presents imagery and image products formed from captured signals during the validation stage of the bistatic SAR research. Image quality and image characteristics are discussed first. Then image products such as two-color multi-view (2CMV) and coherent change detection (CCD) are presented.

  8. WEIBULL MULTIPLICATIVE MODEL AND MACHINE LEARNING MODELS FOR FULL-AUTOMATIC DARK-SPOT DETECTION FROM SAR IMAGES

    A. Taravat

    2013-09-01

    Full Text Available As a major aspect of marine pollution, oil release into the sea has serious biological and environmental impacts. Among remote sensing systems (which is a tool that offers a non-destructive investigation method, synthetic aperture radar (SAR can provide valuable synoptic information about the position and size of the oil spill due to its wide area coverage and day/night, and all-weather capabilities. In this paper we present a new automated method for oil-spill monitoring. A new approach is based on the combination of Weibull Multiplicative Model and machine learning techniques to differentiate between dark spots and the background. First, the filter created based on Weibull Multiplicative Model is applied to each sub-image. Second, the sub-image is segmented by two different neural networks techniques (Pulsed Coupled Neural Networks and Multilayer Perceptron Neural Networks. As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approaches were tested on 20 ENVISAT and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall dataset, the average accuracies of 94.05 % and 95.20 % were obtained for PCNN and MLP methods, respectively. The average computational time for dark-spot detection with a 256 × 256 image in about 4 s for PCNN segmentation using IDL software which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust and effective. The proposed approach can be applied to the future spaceborne SAR images.

  9. Weibull Multiplicative Model and Machine Learning Models for Full-Automatic Dark-Spot Detection from SAR Images

    Taravat, A.; Del Frate, F.

    2013-09-01

    As a major aspect of marine pollution, oil release into the sea has serious biological and environmental impacts. Among remote sensing systems (which is a tool that offers a non-destructive investigation method), synthetic aperture radar (SAR) can provide valuable synoptic information about the position and size of the oil spill due to its wide area coverage and day/night, and all-weather capabilities. In this paper we present a new automated method for oil-spill monitoring. A new approach is based on the combination of Weibull Multiplicative Model and machine learning techniques to differentiate between dark spots and the background. First, the filter created based on Weibull Multiplicative Model is applied to each sub-image. Second, the sub-image is segmented by two different neural networks techniques (Pulsed Coupled Neural Networks and Multilayer Perceptron Neural Networks). As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approaches were tested on 20 ENVISAT and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall dataset, the average accuracies of 94.05 % and 95.20 % were obtained for PCNN and MLP methods, respectively. The average computational time for dark-spot detection with a 256 × 256 image in about 4 s for PCNN segmentation using IDL software which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust and effective. The proposed approach can be applied to the future spaceborne SAR images.

  10. Prototype Theory Based Feature Representation for PolSAR Images

    Huang Xiaojing; Yang Xiangli; Huang Pingping; Yang Wen

    2016-01-01

    This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory. Then, regularized logistic regression is used to predict similarities between a test sample and each prototype set. Finally, the PolSAR image feature representation is obtained by ensemble projection. Experimental results of an unsupervised classification of PolSAR images show that our...

  11. Convolutional Neural Networks for SAR Image Segmentation

    Malmgren-Hansen, David; Nobel-Jørgensen, Morten

    2015-01-01

    Segmentation of Synthetic Aperture Radar (SAR) images has several uses, but it is a difficult task due to a number of properties related to SAR images. In this article we show how Convolutional Neural Networks (CNNs) can easily be trained for SAR image segmentation with good results. Besides...

  12. Imaging in severe acute respiratory syndrome (SARS)

    Antonio, G.E.; Wong, K.T.; Chu, W.C.W.; Hui, D.S.C.; Cheng, F.W.T.; Yuen, E.H.Y.; Chung, S.S.C.; Fok, T.F.; Sung, J.J.Y.; Ahuja, A.T.

    2003-01-01

    Severe acute respiratory syndrome (SARS) is a highly infectious disease caused by a novel coronavirus, and has become pandemic within a short period of time. Imaging plays an important role in the diagnosis, management and follow-up of patients with SARS. The current status of imaging in SARS is presented in this review

  13. ANALYSIS OF MULTIPATH PIXELS IN SAR IMAGES

    J. W. Zhao

    2016-06-01

    Full Text Available As the received radar signal is the sum of signal contributions overlaid in one single pixel regardless of the travel path, the multipath effect should be seriously tackled as the multiple bounce returns are added to direct scatter echoes which leads to ghost scatters. Most of the existing solution towards the multipath is to recover the signal propagation path. To facilitate the signal propagation simulation process, plenty of aspects such as sensor parameters, the geometry of the objects (shape, location, orientation, mutual position between adjacent buildings and the physical parameters of the surface (roughness, correlation length, permittivitywhich determine the strength of radar signal backscattered to the SAR sensor should be given in previous. However, it's not practical to obtain the highly detailed object model in unfamiliar area by field survey as it's a laborious work and time-consuming. In this paper, SAR imaging simulation based on RaySAR is conducted at first aiming at basic understanding of multipath effects and for further comparison. Besides of the pre-imaging simulation, the product of the after-imaging, which refers to radar images is also taken into consideration. Both Cosmo-SkyMed ascending and descending SAR images of Lupu Bridge in Shanghai are used for the experiment. As a result, the reflectivity map and signal distribution map of different bounce level are simulated and validated by 3D real model. The statistic indexes such as the phase stability, mean amplitude, amplitude dispersion, coherence and mean-sigma ratio in case of layover are analyzed with combination of the RaySAR output.

  14. Precision Rectification of Airborne SAR Image

    Dall, Jørgen; Liao, M.; Zhang, Zhe

    1997-01-01

    A simple and direct procedure for the rectification of a certain class of airborne SAR data is presented. The relief displacements of SAR data are effectively removed by means of a digital elevation model and the image is transformed to the ground coordinate system. SAR data from the Danish EMISAR...

  15. Image based SAR product simulation for analysis

    Domik, G.; Leberl, F.

    1987-01-01

    SAR product simulation serves to predict SAR image gray values for various flight paths. Input typically consists of a digital elevation model and backscatter curves. A new method is described of product simulation that employs also a real SAR input image for image simulation. This can be denoted as 'image-based simulation'. Different methods to perform this SAR prediction are presented and advantages and disadvantages discussed. Ascending and descending orbit images from NASA's SIR-B experiment were used for verification of the concept: input images from ascending orbits were converted into images from a descending orbit; the results are compared to the available real imagery to verify that the prediction technique produces meaningful image data.

  16. Deep learning for SAR image formation

    Mason, Eric; Yonel, Bariscan; Yazici, Birsen

    2017-04-01

    The recent success of deep learning has lead to growing interest in applying these methods to signal processing problems. This paper explores the applications of deep learning to synthetic aperture radar (SAR) image formation. We review deep learning from a perspective relevant to SAR image formation. Our objective is to address SAR image formation in the presence of uncertainties in the SAR forward model. We present a recurrent auto-encoder network architecture based on the iterative shrinkage thresholding algorithm (ISTA) that incorporates SAR modeling. We then present an off-line training method using stochastic gradient descent and discuss the challenges and key steps of learning. Lastly, we show experimentally that our method can be used to form focused images in the presence of phase uncertainties. We demonstrate that the resulting algorithm has faster convergence and decreased reconstruction error than that of ISTA.

  17. Geometric calibration of ERS satellite SAR images

    Mohr, Johan Jacob; Madsen, Søren Nørvang

    2001-01-01

    Geometric calibration of the European Remote Sensing (ERS) Satellite synthetic aperture radar (SAR) slant range images is important in relation to mapping areas without ground reference points and also in relation to automated processing. The relevant SAR system parameters are discussed...

  18. Attribute Learning for SAR Image Classification

    Chu He

    2017-04-01

    Full Text Available This paper presents a classification approach based on attribute learning for high spatial resolution Synthetic Aperture Radar (SAR images. To explore the representative and discriminative attributes of SAR images, first, an iterative unsupervised algorithm is designed to cluster in the low-level feature space, where the maximum edge response and the ratio of mean-to-variance are included; a cross-validation step is applied to prevent overfitting. Second, the most discriminative clustering centers are sorted out to construct an attribute dictionary. By resorting to the attribute dictionary, a representation vector describing certain categories in the SAR image can be generated, which in turn is used to perform the classifying task. The experiments conducted on TerraSAR-X images indicate that those learned attributes have strong visual semantics, which are characterized by bright and dark spots, stripes, or their combinations. The classification method based on these learned attributes achieves better results.

  19. AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREAS

    Y. Xiang

    2017-09-01

    Full Text Available Due to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for multiview high resolution SAR images is proposed in the paper, which consists of three main modules. First, both the reference image and the sensed image are segmented into two parts, urban areas and nonurban areas. Urban areas caused by double or multiple scattering in a SAR image have a tendency to show higher local mean and local variance values compared with general homogeneous regions due to the complex structural information. Based on this criterion, building areas are extracted. After obtaining the target regions, L-shape structures are detected using the SAR phase congruency model and Hough transform. The double bounce scatterings formed by wall and ground are shown as strong L- or T-shapes, which are usually taken as the most reliable indicator for building detection. According to the assumption that buildings are rectangular and flat models, planimetric buildings are delineated using the L-shapes, then the reconstructed target areas are obtained. For the orignal areas and the reconstructed target areas, the SAR-SIFT matching algorithm is implemented. Finally, correct corresponding points are extracted by the fast sample consensus (FSC and the transformation model is also derived. The experimental results on a pair of multiview TerraSAR images with 1-m resolution show that the proposed approach gives a robust and precise registration performance, compared with the orignal SAR-SIFT method.

  20. Automatic Coregistration for Multiview SAR Images in Urban Areas

    Xiang, Y.; Kang, W.; Wang, F.; You, H.

    2017-09-01

    Due to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for multiview high resolution SAR images is proposed in the paper, which consists of three main modules. First, both the reference image and the sensed image are segmented into two parts, urban areas and nonurban areas. Urban areas caused by double or multiple scattering in a SAR image have a tendency to show higher local mean and local variance values compared with general homogeneous regions due to the complex structural information. Based on this criterion, building areas are extracted. After obtaining the target regions, L-shape structures are detected using the SAR phase congruency model and Hough transform. The double bounce scatterings formed by wall and ground are shown as strong L- or T-shapes, which are usually taken as the most reliable indicator for building detection. According to the assumption that buildings are rectangular and flat models, planimetric buildings are delineated using the L-shapes, then the reconstructed target areas are obtained. For the orignal areas and the reconstructed target areas, the SAR-SIFT matching algorithm is implemented. Finally, correct corresponding points are extracted by the fast sample consensus (FSC) and the transformation model is also derived. The experimental results on a pair of multiview TerraSAR images with 1-m resolution show that the proposed approach gives a robust and precise registration performance, compared with the orignal SAR-SIFT method.

  1. AUTOMATIC INTERPRETATION OF HIGH RESOLUTION SAR IMAGES: FIRST RESULTS OF SAR IMAGE SIMULATION FOR SINGLE BUILDINGS

    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.

  2. CFAR Edge Detector for Polarimetric SAR Images

    Schou, Jesper; Skriver, Henning; Nielsen, Allan Aasbjerg

    2003-01-01

    Finding the edges between different regions in an image is one of the fundamental steps of image analysis, and several edge detectors suitable for the special statistics of synthetic aperture radar (SAR) intensity images have previously been developed. In this paper, a new edge detector for polar...

  3. Relevant Scatterers Characterization in SAR Images

    Chaabouni, Houda; Datcu, Mihai

    2006-11-01

    Recognizing scenes in a single look meter resolution Synthetic Aperture Radar (SAR) images, requires the capability to identify relevant signal signatures in condition of variable image acquisition geometry, arbitrary objects poses and configurations. Among the methods to detect relevant scatterers in SAR images, we can mention the internal coherence. The SAR spectrum splitted in azimuth generates a series of images which preserve high coherence only for particular object scattering. The detection of relevant scatterers can be done by correlation study or Independent Component Analysis (ICA) methods. The present article deals with the state of the art for SAR internal correlation analysis and proposes further extensions using elements of inference based on information theory applied to complex valued signals. The set of azimuth looks images is analyzed using mutual information measures and an equivalent channel capacity is derived. The localization of the "target" requires analysis in a small image window, thus resulting in imprecise estimation of the second order statistics of the signal. For a better precision, a Hausdorff measure is introduced. The method is applied to detect and characterize relevant objects in urban areas.

  4. An Advanced Rotation Invariant Descriptor for SAR Image Registration

    Yuming Xiang

    2017-07-01

    Full Text Available The Scale-Invariant Feature Transform (SIFT algorithm and its many variants have been widely used in Synthetic Aperture Radar (SAR image registration. The SIFT-like algorithms maintain rotation invariance by assigning a dominant orientation for each keypoint, while the calculation of dominant orientation is not robust due to the effect of speckle noise in SAR imagery. In this paper, we propose an advanced local descriptor for SAR image registration to achieve rotation invariance without assigning a dominant orientation. Based on the improved intensity orders, we first divide a circular neighborhood into several sub-regions. Second, rotation-invariant ratio orientation histograms of each sub-region are proposed by accumulating the ratio values of different directions in a rotation-invariant coordinate system. The proposed descriptor is composed of the concatenation of the histograms of each sub-region. In order to increase the distinctiveness of the proposed descriptor, multiple image neighborhoods are aggregated. Experimental results on several satellite SAR images have shown an improvement in the matching performance over other state-of-the-art algorithms.

  5. SAR Image Classification Based on Its Texture Features

    LI Pingxiang; FANG Shenghui

    2003-01-01

    SAR images not only have the characteristics of all-ay, all-eather, but also provide object information which is different from visible and infrared sensors. However, SAR images have some faults, such as more speckles and fewer bands. The authors conducted the experiments of texture statistics analysis on SAR image features in order to improve the accuracy of SAR image interpretation.It is found that the texture analysis is an effective method for improving the accuracy of the SAR image interpretation.

  6. The Radiometric Measurement Quantity for SAR Images

    Döring, Björn J.; Schwerdt, Marco

    2013-01-01

    A Synthetic Aperture Radar (SAR) system measures among other quantities the terrain radar reflectivity. After image calibration, the pixel intensities are commonly expressed in terms of radar cross sections (for point targets) or as backscatter coefficients (for distributed targets), which are directly related. This paper argues that pixel intensities are not generally proportional to radar cross section or derived physical quantities. The paper further proposes to replace the inaccurate term...

  7. Two dimensional estimates from ocean SAR images

    J. M. Le Caillec

    1996-01-01

    Full Text Available Synthetic Aperture Radar (SAR images of the ocean yield a lot of information on the sea-state surface providing that the mapping process between the surface and the image is clearly defined. However it is well known that SAR images exhibit non-gaussian statistics and that the motion of the scatterers on the surface, while the image is being formed, may yield to nonlinearities. The detection and quantification of these nonlinearities are made possible by using Higher Order Spectra (HOS methods and more specifically, bispectrum estimation. The development of the latter method allowed us to find phase relations between different parts of the image and to recognise their level of coupling, i.e. if and how waves of different wavelengths interacted nonlinearly. This information is quite important as the usual models assume strong nonlinearities when the waves are propagating in the azimuthal direction (i.e. along the satellite track and almost no nonlinearities when propagating in the range direction. In this paper, the mapping of the ocean surface to the SAR image is reinterpreted and a specific model (i.e. a Second Order Volterra Model is introduced. The nonlinearities are thus explained as either produced by a nonlinear system or due to waves propagating into selected directions (azimuth or range and interacting during image formation. It is shown that quadratic nonlinearities occur for waves propagating near the range direction while for those travelling in the azimuthal direction the nonlinearities, when present, are mostly due to wave interactions but are almost completely removed by the filtering effect coming from the surface motion itself (azimuth cut-off. An inherent quadratic interaction filtering (azimuth high pass filter is also present. But some other effects, apparently nonlinear, are not detected with the methods described here, meaning that either the usual relation developed for the Ocean-to-SAR transform is somewhat incomplete

  8. Polarimetric SAR image classification based on discriminative dictionary learning model

    Sang, Cheng Wei; Sun, Hong

    2018-03-01

    Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.

  9. Synthetic aperture design for increased SAR image rate

    Bielek, Timothy P [Albuquerque, NM; Thompson, Douglas G [Albuqerque, NM; Walker, Bruce C [Albuquerque, NM

    2009-03-03

    High resolution SAR images of a target scene at near video rates can be produced by using overlapped, but nevertheless, full-size synthetic apertures. The SAR images, which respectively correspond to the apertures, can be analyzed in sequence to permit detection of movement in the target scene.

  10. Multi-look polarimetric SAR image filtering using simulated annealing

    Schou, Jesper

    2000-01-01

    Based on a previously published algorithm capable of estimating the radar cross-section in synthetic aperture radar (SAR) intensity images, a new filter is presented utilizing multi-look polarimetric SAR images. The underlying mean covariance matrix is estimated from the observed sample covariance...

  11. Autofocus algorithm for curvilinear SAR imaging

    Bleszynski, E.; Bleszynski, M.; Jaroszewicz, T.

    2012-05-01

    We describe an approach to autofocusing for large apertures on curved SAR trajectories. It is a phase-gradient type method in which phase corrections compensating trajectory perturbations are estimated not directly from the image itself, but rather on the basis of partial" SAR data { functions of the slow and fast times { recon- structed (by an appropriate forward-projection procedure) from windowed scene patches, of sizes comparable to distances between distinct targets or localized features of the scene. The resulting partial data" can be shown to contain the same information on the phase perturbations as that in the original data, provided the frequencies of the perturbations do not exceed a quantity proportional to the patch size. The algorithm uses as input a sequence of conventional scene images based on moderate-size subapertures constituting the full aperture for which the phase corrections are to be determined. The subaperture images are formed with pixel sizes comparable to the range resolution which, for the optimal subaperture size, should be also approximately equal the cross-range resolution. The method does not restrict the size or shape of the synthetic aperture and can be incorporated in the data collection process in persistent sensing scenarios. The algorithm has been tested on the publicly available set of GOTCHA data, intentionally corrupted by random-walk-type trajectory uctuations (a possible model of errors caused by imprecise inertial navigation system readings) of maximum frequencies compatible with the selected patch size. It was able to eciently remove image corruption for apertures of sizes up to 360 degrees.

  12. The Establishment of the SAR images database System Based on Oracle and ArcSDE

    Zhou, Jijin; Li, Zhen; Chen, Quan; Tian, Bangsen

    2014-01-01

    Synthetic aperture radar is a kind of microwave imaging system, and has the advantages of multi-band, multi-polarization and multi-angle. At present, there is no SAR images database system based on typical features. For solving problems in interpretation and identification, a new SAR images database system of the typical features is urgent in the current development need. In this article, a SAR images database system based on Oracle and ArcSDE was constructed. The main works involving are as follows: (1) SAR image data was calibrated and corrected geometrically and geometrically. Besides, the fully polarimetric image was processed as the coherency matrix[T] to preserve the polarimetric information. (2) After analyzing multiple space borne SAR images, the metadata table was defined as: IMAGEID; Name of features; Latitude and Longitude; Sensor name; Range and Azimuth resolution etc. (3) Through the comparison between GeoRaster and ArcSDE, result showed ArcSDE is a more appropriate technology to store images in a central database. The System stores and manages multisource SAR image data well, reflects scattering, geometry, polarization, band and angle characteristics, and combines with analysis of the managed objects and service objects of the database as well as focuses on constructing SAR image system in the aspects of data browse and data retrieval. According the analysis of characteristics of SAR images such as scattering, polarization, incident angle and wave band information, different weights can be given to these characteristics. Then an interpreted tool is formed to provide an efficient platform for interpretation

  13. Guided SAR image despeckling with probabilistic non local weights

    Gokul, Jithin; Nair, Madhu S.; Rajan, Jeny

    2017-12-01

    SAR images are generally corrupted by granular disturbances called speckle, which makes visual analysis and detail extraction a difficult task. Non Local despeckling techniques with probabilistic similarity has been a recent trend in SAR despeckling. To achieve effective speckle suppression without compromising detail preservation, we propose an improvement for the existing Generalized Guided Filter with Bayesian Non-Local Means (GGF-BNLM) method. The proposed method (Guided SAR Image Despeckling with Probabilistic Non Local Weights) replaces parametric constants based on heuristics in GGF-BNLM method with dynamically derived values based on the image statistics for weight computation. Proposed changes make GGF-BNLM method adaptive and as a result, significant improvement is achieved in terms of performance. Experimental analysis on SAR images shows excellent speckle reduction without compromising feature preservation when compared to GGF-BNLM method. Results are also compared with other state-of-the-art and classic SAR depseckling techniques to demonstrate the effectiveness of the proposed method.

  14. RESEARCH ON AIRBORNE SAR IMAGING BASED ON ESC ALGORITHM

    X. T. Dong

    2017-09-01

    Full Text Available Due to the ability of flexible, accurate, and fast obtaining abundant information, airborne SAR is significant in the field of Earth Observation and many other applications. Optimally the flight paths are straight lines, but in reality it is not the case since some portion of deviation from the ideal path is impossible to avoid. A small disturbance from the ideal line will have a major effect on the signal phase, dramatically deteriorating the quality of SAR images and data. Therefore, to get accurate echo information and radar images, it is essential to measure and compensate for nonlinear motion of antenna trajectories. By means of compensating each flying trajectory to its reference track, MOCO method corrects linear phase error and quadratic phase error caused by nonlinear antenna trajectories. Position and Orientation System (POS data is applied to acquiring accuracy motion attitudes and spatial positions of antenna phase centre (APC. In this paper, extend chirp scaling algorithm (ECS is used to deal with echo data of airborne SAR. An experiment is done using VV-Polarization raw data of C-band airborne SAR. The quality evaluations of compensated SAR images and uncompensated SAR images are done in the experiment. The former always performs better than the latter. After MOCO processing, azimuth ambiguity is declined, peak side lobe ratio (PSLR effectively improves and the resolution of images is improved obviously. The result shows the validity and operability of the imaging process for airborne SAR.

  15. Research on Airborne SAR Imaging Based on Esc Algorithm

    Dong, X. T.; Yue, X. J.; Zhao, Y. H.; Han, C. M.

    2017-09-01

    Due to the ability of flexible, accurate, and fast obtaining abundant information, airborne SAR is significant in the field of Earth Observation and many other applications. Optimally the flight paths are straight lines, but in reality it is not the case since some portion of deviation from the ideal path is impossible to avoid. A small disturbance from the ideal line will have a major effect on the signal phase, dramatically deteriorating the quality of SAR images and data. Therefore, to get accurate echo information and radar images, it is essential to measure and compensate for nonlinear motion of antenna trajectories. By means of compensating each flying trajectory to its reference track, MOCO method corrects linear phase error and quadratic phase error caused by nonlinear antenna trajectories. Position and Orientation System (POS) data is applied to acquiring accuracy motion attitudes and spatial positions of antenna phase centre (APC). In this paper, extend chirp scaling algorithm (ECS) is used to deal with echo data of airborne SAR. An experiment is done using VV-Polarization raw data of C-band airborne SAR. The quality evaluations of compensated SAR images and uncompensated SAR images are done in the experiment. The former always performs better than the latter. After MOCO processing, azimuth ambiguity is declined, peak side lobe ratio (PSLR) effectively improves and the resolution of images is improved obviously. The result shows the validity and operability of the imaging process for airborne SAR.

  16. SAR image effects on coherence and coherence estimation.

    Bickel, Douglas Lloyd

    2014-01-01

    Radar coherence is an important concept for imaging radar systems such as synthetic aperture radar (SAR). This document quantifies some of the effects in SAR which modify the coherence. Although these effects can disrupt the coherence within a single SAR image, this report will focus on the coherence between separate images, such as for coherent change detection (CCD) processing. There have been other presentations on aspects of this material in the past. The intent of this report is to bring various issues that affect the coherence together in a single report to support radar engineers in making decisions about these matters.

  17. Improved SAR Image Coregistration Using Pixel-Offset Series

    Wang, Teng

    2014-03-14

    Synthetic aperture radar (SAR) image coregistration is a key procedure before interferometric SAR (InSAR) time-series analysis can be started. However, many geophysical data sets suffer from severe decorrelation problems due to a variety of reasons, making precise coregistration a nontrivial task. Here, we present a new strategy that uses a pixel-offset series of detected subimage patches dominated by point-like targets (PTs) to improve SAR image coregistrations. First, all potentially coherent image pairs are coregistered in a conventional way. In this step, we propose a coregistration quality index for each image to rank its relative “significance” within the data set and to select a reference image for the SAR data set. Then, a pixel-offset series of detected PTs is made from amplitude maps to improve the geometrical mapping functions. Finally, all images are resampled depending on the pixel offsets calculated from the updated geometrical mapping functions. We used images from a rural region near the North Anatolian Fault in eastern Turkey to test the proposed method, and clear coregistration improvements were found based on amplitude stability. This enhanced the fact that the coregistration strategy should therefore lead to improved InSAR time-series analysis results.

  18. Improved SAR Image Coregistration Using Pixel-Offset Series

    Wang, Teng; Jonsson, Sigurjon; Hanssen, Ramon F.

    2014-01-01

    Synthetic aperture radar (SAR) image coregistration is a key procedure before interferometric SAR (InSAR) time-series analysis can be started. However, many geophysical data sets suffer from severe decorrelation problems due to a variety of reasons, making precise coregistration a nontrivial task. Here, we present a new strategy that uses a pixel-offset series of detected subimage patches dominated by point-like targets (PTs) to improve SAR image coregistrations. First, all potentially coherent image pairs are coregistered in a conventional way. In this step, we propose a coregistration quality index for each image to rank its relative “significance” within the data set and to select a reference image for the SAR data set. Then, a pixel-offset series of detected PTs is made from amplitude maps to improve the geometrical mapping functions. Finally, all images are resampled depending on the pixel offsets calculated from the updated geometrical mapping functions. We used images from a rural region near the North Anatolian Fault in eastern Turkey to test the proposed method, and clear coregistration improvements were found based on amplitude stability. This enhanced the fact that the coregistration strategy should therefore lead to improved InSAR time-series analysis results.

  19. 3D Tomographic SAR Imaging in Densely Vegetated Mountainous Rural Areas in China and Sweden

    Feng, L.; Muller, J. P., , Prof

    2017-12-01

    3D SAR Tomography (TomoSAR) and 4D SAR Differential Tomography (Diff-TomoSAR) exploit multi-baseline SAR data stacks to create an important new innovation of SAR Interferometry, to unscramble complex scenes with multiple scatterers mapped into the same SAR cell. In addition to this 3-D shape reconstruction and deformation solution in complex urban/infrastructure areas, and recent cryospheric ice investigations, emerging tomographic remote sensing applications include forest applications, e.g. tree height and biomass estimation, sub-canopy topographic mapping, and even search, rescue and surveillance. However, these scenes are characterized by temporal decorrelation of scatterers, orbital, tropospheric and ionospheric phase distortion and an open issue regarding possible height blurring and accuracy losses for TomoSAR applications particularly in densely vegetated mountainous rural areas. Thus, it is important to develop solutions for temporal decorrelation, orbital, tropospheric and ionospheric phase distortion.We report here on 3D imaging (especially in vertical layers) over densely vegetated mountainous rural areas using 3-D SAR imaging (SAR tomography) derived from data stacks of X-band COSMO-SkyMed Spotlight and L band ALOS-1 PALSAR data stacks over Dujiangyan Dam, Sichuan, China and L and P band airborne SAR data (BioSAR 2008 - ESA) in the Krycklan river catchment, Northern Sweden. The new TanDEM-X 12m DEM is used to assist co - registration of all the data stacks over China first. Then, atmospheric correction is being assessed using weather model data such as ERA-I, MERRA, MERRA-2, WRF; linear phase-topography correction and MODIS spectrometer correction will be compared and ionospheric correction methods are discussed to remove tropospheric and ionospheric delay. Then the new TomoSAR method with the TanDEM-X 12m DEM is described to obtain the number of scatterers inside each pixel, the scattering amplitude and phase of each scatterer and finally extract

  20. Wavelet Filter Banks for Super-Resolution SAR Imaging

    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. Enhancement of SAR images using fuzzy shrinkage technique

    This paper presents speckle noise reduction in SAR images using a combination of curvelet and fuzzy logic technique to restore speckle-affected images. This method overcomes the limitation of discontinuity in hard threshold and permanent deviation in soft threshold. First, it decomposes noise image into different ...

  2. SAR image formation with azimuth interpolation after azimuth transform

    Doerry,; Armin W. , Martin; Grant D. , Holzrichter; Michael, W [Albuquerque, NM

    2008-07-08

    Two-dimensional SAR data can be processed into a rectangular grid format by subjecting the SAR data to a Fourier transform operation, and thereafter to a corresponding interpolation operation. Because the interpolation operation follows the Fourier transform operation, the interpolation operation can be simplified, and the effect of interpolation errors can be diminished. This provides for the possibility of both reducing the re-grid processing time, and improving the image quality.

  3. Fast Superpixel Segmentation Algorithm for PolSAR Images

    Zhang Yue

    2017-10-01

    Full Text Available As a pre-processing technique, superpixel segmentation algorithms should be of high computational efficiency, accurate boundary adherence and regular shape in homogeneous regions. A fast superpixel segmentation algorithm based on Iterative Edge Refinement (IER has shown to be applicable on optical images. However, it is difficult to obtain the ideal results when IER is applied directly to PolSAR images due to the speckle noise and small or slim regions in PolSAR images. To address these problems, in this study, the unstable pixel set is initialized as all the pixels in the PolSAR image instead of the initial grid edge pixels. In the local relabeling of the unstable pixels, the fast revised Wishart distance is utilized instead of the Euclidean distance in CIELAB color space. Then, a post-processing procedure based on dissimilarity measure is empolyed to remove isolated small superpixels as well as to retain the strong point targets. Finally, extensive experiments based on a simulated image and a real-world PolSAR image from Airborne Synthetic Aperture Radar (AirSAR are conducted, showing that the proposed algorithm, compared with three state-of-the-art methods, performs better in terms of several commonly used evaluation criteria with high computational efficiency, accurate boundary adherence, and homogeneous regularity.

  4. Individual Building Extraction from TerraSAR-X Images Based on Ontological Semantic Analysis

    Rong Gui

    2016-08-01

    Full Text Available Accurate building information plays a crucial role for urban planning, human settlements and environmental management. Synthetic aperture radar (SAR images, which deliver images with metric resolution, allow for analyzing and extracting detailed information on urban areas. In this paper, we consider the problem of extracting individual buildings from SAR images based on domain ontology. By analyzing a building scattering model with different orientations and structures, the building ontology model is set up to express multiple characteristics of individual buildings. Under this semantic expression framework, an object-based SAR image segmentation method is adopted to provide homogeneous image objects, and three categories of image object features are extracted. Semantic rules are implemented by organizing image object features, and the individual building objects expression based on an ontological semantic description is formed. Finally, the building primitives are used to detect buildings among the available image objects. Experiments on TerraSAR-X images of Foshan city, China, with a spatial resolution of 1.25 m × 1.25 m, have shown the total extraction rates are above 84%. The results indicate the ontological semantic method can exactly extract flat-roof and gable-roof buildings larger than 250 pixels with different orientations.

  5. Multi-image Matching of Airborne SAR Imagery by SANCC

    DING Hao

    2015-03-01

    Full Text Available In order to improve accuracy of SAR matching, a multi-image matching method based on sum of adaptive normalized cross-correlation (SANCC is proposed. It utilizes geometrical and radiometric information of multi-baselinesynthetic aperture radar (SARimages effectively. Firstly, imaging parameters, platform parameters and approximate digital surface model (DSM are used to predict matching line. Secondly, similarity and proximity in Gestalt theory are introduced to SANCC, and SANCC measures of potential matching points along the matching line are calculated. Thirdly, multi-image matching results and object coordinates of matching points are obtained by winner-take-all (WTA optimization strategy. The approach has been demonstrated with airborne SAR images acquired by a Chinese airborne SAR system (CASMSAR system. The experimental results indicate that the proposed algorithm is effective for providing dense and accuracy matching points, reducing the number of mismatches caused by repeated textures, and offering a better solution to match in poor textured areas.

  6. Restoration of polarimetric SAR images using simulated annealing

    Schou, Jesper; Skriver, Henning

    2001-01-01

    approach favoring one of the objectives. An algorithm for estimating the radar cross-section (RCS) for intensity SAR images has previously been proposed in the literature based on Markov random fields and the stochastic optimization method simulated annealing. A new version of the algorithm is presented......Filtering synthetic aperture radar (SAR) images ideally results in better estimates of the parameters characterizing the distributed targets in the images while preserving the structures of the nondistributed targets. However, these objectives are normally conflicting, often leading to a filtering...

  7. Synthetic SAR Image Generation using Sensor, Terrain and Target Models

    Kusk, Anders; Abulaitijiang, Adili; Dall, Jørgen

    2016-01-01

    A tool to generate synthetic SAR images of objects set on a clutter background is described. The purpose is to generate images for training Automatic Target Recognition and Identification algorithms. The tool employs a commercial electromagnetic simulation program to calculate radar cross section...

  8. Enhancement of SAR images using fuzzy shrinkage technique in ...

    Shivakumara Swamy Puranik Math

    2017-08-03

    Aug 3, 2017 ... not use threshold approach only by proper selection of shrinking parameter the speckle in SAR image is ... but cost estimation of hyper-parameters will be high. The ..... To find the effectiveness of the proposed image in a.

  9. G0-WISHART Distribution Based Classification from Polarimetric SAR Images

    Hu, G. C.; Zhao, Q. H.

    2017-09-01

    Enormous scientific and technical developments have been carried out to further improve the remote sensing for decades, particularly Polarimetric Synthetic Aperture Radar(PolSAR) technique, so classification method based on PolSAR images has getted much more attention from scholars and related department around the world. The multilook polarmetric G0-Wishart model is a more flexible model which describe homogeneous, heterogeneous and extremely heterogeneous regions in the image. Moreover, the polarmetric G0-Wishart distribution dose not include the modified Bessel function of the second kind. It is a kind of simple statistical distribution model with less parameter. To prove its feasibility, a process of classification has been tested with the full-polarized Synthetic Aperture Radar (SAR) image by the method. First, apply multilook polarimetric SAR data process and speckle filter to reduce speckle influence for classification result. Initially classify the image into sixteen classes by H/A/α decomposition. Using the ICM algorithm to classify feature based on the G0-Wshart distance. Qualitative and quantitative results show that the proposed method can classify polaimetric SAR data effectively and efficiently.

  10. IMAGE ENHANCEMENT AND SPECKLE REDUCTION OF FULL POLARIMETRIC SAR DATA BY GAUSSIAN MARKOV RANDOM FIELD

    M. Mahdian

    2013-09-01

    Full Text Available In recent years, the use of Polarimetric Synthetic Aperture Radar (PolSAR data in different applications dramatically has been increased. In SAR imagery an interference phenomenon with random behavior exists which is called speckle noise. The interpretation of data encounters some troubles due to the presence of speckle which can be considered as a multiplicative noise affecting all coherent imaging systems. Indeed, speckle degrade radiometric resolution of PolSAR images, therefore it is needful to perform speckle filtering on the SAR data type. Markov Random Field (MRF has proven to be a powerful method for drawing out eliciting contextual information from remotely sensed images. In the present paper, a probability density function (PDF, which is fitted well with the PolSAR data based on the goodness-of-fit test, is first obtained for the pixel-wise analysis. Then the contextual smoothing is achieved with the MRF method. This novel speckle reduction method combines an advanced statistical distribution with spatial contextual information for PolSAR data. These two parts of information are combined based on weighted summation of pixel-wise and contextual models. This approach not only preserves edge information in the images, but also improves signal-to-noise ratio of the results. The method maintains the mean value of original signal in the homogenous areas and preserves the edges of features in the heterogeneous regions. Experiments on real medium resolution ALOS data from Tehran, and also high resolution full polarimetric SAR data over the Oberpfaffenhofen test-site in Germany, demonstrate the effectiveness of the algorithm compared with well-known despeckling methods.

  11. Detecting and Georegistering Moving Ground Targets in Airborne QuickSAR via Keystoning and Multiple-Phase Center Interferometry

    R. P. Perry

    2008-03-01

    Full Text Available SAR images experience significant range walk and, without some form of motion compensation, can be quite blurred. The MITRE-developed Keystone formatting simultaneously and automatically compensates for range walk due to the radial velocity component of each moving target, independent of the number of targets or the value of each target's radial velocity with respect to the ground. Target radial motion also causes moving targets in synthetic aperture radar images to appear at locations offset from their true instantaneous locations on the ground. In a multichannel radar, the interferometric phase values associated with all nonmoving points on the ground appear as a continuum of phase differences while the moving targets appear as interferometric phase discontinuities. By multiple threshold comparisons and grouping of pixels within the intensity and the phase images, we show that it is possible to reliably detect and accurately georegister moving targets within short-duration SAR (QuickSAR images.

  12. Spacial Variation in SAR Images of Different Resolution for Agricultural Fields

    Sandholt, Inge; Skriver, Henning

    1999-01-01

    The spatial variation in two types of Synthetic Aperture Radar (SAR) images covering agricultural fields is analysed. C-band polarimetric SAR data from the Danish airborne SAR, EMISAR, have been compared to space based ERS-1 C-band SAR with respect to scale and effect of polarization. The general...

  13. Compressed Sensing mm-Wave SAR for Non-Destructive Testing Applications Using Multiple Weighted Side Information

    Mathias Becquaert

    2018-05-01

    Full Text Available This work explores an innovative strategy for increasing the efficiency of compressed sensing applied on mm-wave SAR sensing using multiple weighted side information. The approach is tested on synthetic and on real non-destructive testing measurements performed on a 3D-printed object with defects while taking advantage of multiple previous SAR images of the object with different degrees of similarity. The tested algorithm attributes autonomously weights to the side information at two levels: (1 between the components inside the side information and (2 between the different side information. The reconstruction is thereby almost immune to poor quality side information while exploiting the relevant components hidden inside the added side information. The presented results prove that, in contrast to common compressed sensing, good SAR image reconstruction is achieved at subsampling rates far below the Nyquist rate. Moreover, the algorithm is shown to be much more robust for low quality side information compared to coherent background subtraction.

  14. Space Radar Image of West Texas - SAR scan

    1999-01-01

    This radar image of the Midland/Odessa region of West Texas, demonstrates an experimental technique, called ScanSAR, that allows scientists to rapidly image large areas of the Earth's surface. The large image covers an area 245 kilometers by 225 kilometers (152 miles by 139 miles). It was obtained by the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) flying aboard the space shuttle Endeavour on October 5, 1994. The smaller inset image is a standard SIR-C image showing a portion of the same area, 100 kilometers by 57 kilometers (62 miles by 35 miles) and was taken during the first flight of SIR-C on April 14, 1994. The bright spots on the right side of the image are the cities of Odessa (left) and Midland (right), Texas. The Pecos River runs from the top center to the bottom center of the image. Along the left side of the image are, from top to bottom, parts of the Guadalupe, Davis and Santiago Mountains. North is toward the upper right. Unlike conventional radar imaging, in which a radar continuously illuminates a single ground swath as the space shuttle passes over the terrain, a Scansar radar illuminates several adjacent ground swaths almost simultaneously, by 'scanning' the radar beam across a large area in a rapid sequence. The adjacent swaths, typically about 50 km (31 miles) wide, are then merged during ground processing to produce a single large scene. Illumination for this L-band scene is from the top of the image. The beams were scanned from the top of the scene to the bottom, as the shuttle flew from left to right. This scene was acquired in about 30 seconds. A normal SIR-C image is acquired in about 13 seconds. The ScanSAR mode will likely be used on future radar sensors to construct regional and possibly global radar images and topographic maps. The ScanSAR processor is being designed for 1996 implementation at NASA's Alaska SAR Facility, located at the University of Alaska Fairbanks, and will produce digital images from the

  15. Combined acquisition technique (CAT for neuroimaging of multiple sclerosis at low specific absorption rates (SAR.

    Armin Biller

    Full Text Available PURPOSE: To compare a novel combined acquisition technique (CAT of turbo-spin-echo (TSE and echo-planar-imaging (EPI with conventional TSE. CAT reduces the electromagnetic energy load transmitted for spin excitation. This radiofrequency (RF burden is limited by the specific absorption rate (SAR for patient safety. SAR limits restrict high-field MRI applications, in particular. MATERIAL AND METHODS: The study was approved by the local Medical Ethics Committee. Written informed consent was obtained from all participants. T2- and PD-weighted brain images of n = 40 Multiple Sclerosis (MS patients were acquired by CAT and TSE at 3 Tesla. Lesions were recorded by two blinded, board-certificated neuroradiologists. Diagnostic equivalence of CAT and TSE to detect MS lesions was evaluated along with their SAR, sound pressure level (SPL and sensations of acoustic noise, heating, vibration and peripheral nerve stimulation. RESULTS: Every MS lesion revealed on TSE was detected by CAT according to both raters (Cohen's kappa of within-rater/across-CAT/TSE lesion detection κCAT = 1.00, at an inter-rater lesion detection agreement of κLES = 0.82. CAT reduced the SAR burden significantly compared to TSE (p<0.001. Mean SAR differences between TSE and CAT were 29.0 (± 5.7 % for the T2-contrast and 32.7 (± 21.9 % for the PD-contrast (expressed as percentages of the effective SAR limit of 3.2 W/kg for head examinations. Average SPL of CAT was no louder than during TSE. Sensations of CAT- vs. TSE-induced heating, noise and scanning vibrations did not differ. CONCLUSION: T2-/PD-CAT is diagnostically equivalent to TSE for MS lesion detection yet substantially reduces the RF exposure. Such SAR reduction facilitates high-field MRI applications at 3 Tesla or above and corresponding protocol standardizations but CAT can also be used to scan faster, at higher resolution or with more slices. According to our data, CAT is no more uncomfortable than TSE scanning.

  16. SAR Data Fusion Imaging Method Oriented to Target Feature Extraction

    Yang Wei

    2015-02-01

    Full Text Available To deal with the difficulty for target outlines extracting precisely due to neglect of target scattering characteristic variation during the processing of high-resolution space-borne SAR data, a novel fusion imaging method is proposed oriented to target feature extraction. Firstly, several important aspects that affect target feature extraction and SAR image quality are analyzed, including curved orbit, stop-and-go approximation, atmospheric delay, and high-order residual phase error. Furthermore, the corresponding compensation methods are addressed as well. Based on the analysis, the mathematical model of SAR echo combined with target space-time spectrum is established for explaining the space-time-frequency change rule of target scattering characteristic. Moreover, a fusion imaging strategy and method under high-resolution and ultra-large observation angle range conditions are put forward to improve SAR quality by fusion processing in range-doppler and image domain. Finally, simulations based on typical military targets are used to verify the effectiveness of the fusion imaging method.

  17. Information theoretic bounds for compressed sensing in SAR imaging

    Jingxiong, Zhang; Ke, Yang; Jianzhong, Guo

    2014-01-01

    Compressed sensing (CS) is a new framework for sampling and reconstructing sparse signals from measurements significantly fewer than those prescribed by Nyquist rate in the Shannon sampling theorem. This new strategy, applied in various application areas including synthetic aperture radar (SAR), relies on two principles: sparsity, which is related to the signals of interest, and incoherence, which refers to the sensing modality. An important question in CS-based SAR system design concerns sampling rate necessary and sufficient for exact or approximate recovery of sparse signals. In the literature, bounds of measurements (or sampling rate) in CS have been proposed from the perspective of information theory. However, these information-theoretic bounds need to be reviewed and, if necessary, validated for CS-based SAR imaging, as there are various assumptions made in the derivations of lower and upper bounds on sub-Nyquist sampling rates, which may not hold true in CS-based SAR imaging. In this paper, information-theoretic bounds of sampling rate will be analyzed. For this, the SAR measurement system is modeled as an information channel, with channel capacity and rate-distortion characteristics evaluated to enable the determination of sampling rates required for recovery of sparse scenes. Experiments based on simulated data will be undertaken to test the theoretic bounds against empirical results about sampling rates required to achieve certain detection error probabilities

  18. Generalized internal multiple imaging

    Zuberi, Mohammad Akbar Hosain

    2014-12-04

    Various examples are provided for generalized internal multiple imaging (GIMI). In one example, among others, a method includes generating a higher order internal multiple image using a background Green\\'s function and rendering the higher order internal multiple image for presentation. In another example, a system includes a computing device and a generalized internal multiple imaging (GIMI) application executable in the computing device. The GIMI application includes logic that generates a higher order internal multiple image using a background Green\\'s function and logic that renders the higher order internal multiple image for display on a display device. In another example, a non-transitory computer readable medium has a program executable by processing circuitry that generates a higher order internal multiple image using a background Green\\'s function and renders the higher order internal multiple image for display on a display device.

  19. Generalized internal multiple imaging

    Zuberi, Mohammad Akbar Hosain; Alkhalifah, Tariq

    2014-01-01

    Various examples are provided for generalized internal multiple imaging (GIMI). In one example, among others, a method includes generating a higher order internal multiple image using a background Green's function and rendering the higher order internal multiple image for presentation. In another example, a system includes a computing device and a generalized internal multiple imaging (GIMI) application executable in the computing device. The GIMI application includes logic that generates a higher order internal multiple image using a background Green's function and logic that renders the higher order internal multiple image for display on a display device. In another example, a non-transitory computer readable medium has a program executable by processing circuitry that generates a higher order internal multiple image using a background Green's function and renders the higher order internal multiple image for display on a display device.

  20. THz-SAR Vibrating Target Imaging via the Bayesian Method

    Bin Deng

    2017-01-01

    Full Text Available Target vibration bears important information for target recognition, and terahertz, due to significant micro-Doppler effects, has strong advantages for remotely sensing vibrations. In this paper, the imaging characteristics of vibrating targets with THz-SAR are at first analyzed. An improved algorithm based on an excellent Bayesian approach, that is, the expansion-compression variance-component (ExCoV method, has been proposed for reconstructing scattering coefficients of vibrating targets, which provides more robust and efficient initialization and overcomes the deficiencies of sidelobes as well as artifacts arising from the traditional correlation method. A real vibration measurement experiment of idle cars was performed to validate the range model. Simulated SAR data of vibrating targets and a tank model in a real background in 220 GHz show good performance at low SNR. Rapidly evolving high-power terahertz devices will offer viable THz-SAR application at a distance of several kilometers.

  1. A SAR IMAGE REGISTRATION METHOD BASED ON SIFT ALGORITHM

    W. Lu

    2017-09-01

    Full Text Available In order to improve the stability and rapidity of synthetic aperture radar (SAR images matching, an effective method was presented. Firstly, the adaptive smoothing filtering was employed for image denoising in image processing based on Wallis filtering to avoid the follow-up noise is amplified. Secondly, feature points were extracted by a simplified SIFT algorithm. Finally, the exact matching of the images was achieved with these points. Compared with the existing methods, it not only maintains the richness of features, but a-lso reduces the noise of the image. The simulation results show that the proposed algorithm can achieve better matching effect.

  2. SAR Imaging through the Earth’s Ionosphere

    2013-11-06

    Xiaoqing Pi, Anthony Freeman, Bruce Chapman, Paul Rosen, and Zhenhong Li . Imaging ionospheric inhomogeneities using spaceborne synthetic aperture radar. J...resolution SAR phase correction. IEEE Trans. Aerosp. Electron. Syst., 30(3):827–835, 1994. [30] Lianlin Li and Fang Li . Ionosphere tomography based on...Manduchi and G. A. Mian . Accuracy analysis for correlation-based image registartion algorithms. In Proceedings of the 1993 IEEE International

  3. Combined Acquisition Technique (CAT) for Neuroimaging of Multiple Sclerosis at Low Specific Absorption Rates (SAR)

    Biller, Armin; Choli, Morwan; Blaimer, Martin; Breuer, Felix A.; Jakob, Peter M.; Bartsch, Andreas J.

    2014-01-01

    Purpose To compare a novel combined acquisition technique (CAT) of turbo-spin-echo (TSE) and echo-planar-imaging (EPI) with conventional TSE. CAT reduces the electromagnetic energy load transmitted for spin excitation. This radiofrequency (RF) burden is limited by the specific absorption rate (SAR) for patient safety. SAR limits restrict high-field MRI applications, in particular. Material and Methods The study was approved by the local Medical Ethics Committee. Written informed consent was obtained from all participants. T2- and PD-weighted brain images of n = 40 Multiple Sclerosis (MS) patients were acquired by CAT and TSE at 3 Tesla. Lesions were recorded by two blinded, board-certificated neuroradiologists. Diagnostic equivalence of CAT and TSE to detect MS lesions was evaluated along with their SAR, sound pressure level (SPL) and sensations of acoustic noise, heating, vibration and peripheral nerve stimulation. Results Every MS lesion revealed on TSE was detected by CAT according to both raters (Cohen’s kappa of within-rater/across-CAT/TSE lesion detection κCAT = 1.00, at an inter-rater lesion detection agreement of κLES = 0.82). CAT reduced the SAR burden significantly compared to TSE (pCAT were 29.0 (±5.7) % for the T2-contrast and 32.7 (±21.9) % for the PD-contrast (expressed as percentages of the effective SAR limit of 3.2 W/kg for head examinations). Average SPL of CAT was no louder than during TSE. Sensations of CAT- vs. TSE-induced heating, noise and scanning vibrations did not differ. Conclusion T2−/PD-CAT is diagnostically equivalent to TSE for MS lesion detection yet substantially reduces the RF exposure. Such SAR reduction facilitates high-field MRI applications at 3 Tesla or above and corresponding protocol standardizations but CAT can also be used to scan faster, at higher resolution or with more slices. According to our data, CAT is no more uncomfortable than TSE scanning. PMID:24608106

  4. Tie Points Extraction for SAR Images Based on Differential Constraints

    Xiong, X.; Jin, G.; Xu, Q.; Zhang, H.

    2018-04-01

    Automatically extracting tie points (TPs) on large-size synthetic aperture radar (SAR) images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC) algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC) algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

  5. TIE POINTS EXTRACTION FOR SAR IMAGES BASED ON DIFFERENTIAL CONSTRAINTS

    X. Xiong

    2018-04-01

    Full Text Available Automatically extracting tie points (TPs on large-size synthetic aperture radar (SAR images is still challenging because the efficiency and correct ratio of the image matching need to be improved. This paper proposes an automatic TPs extraction method based on differential constraints for large-size SAR images obtained from approximately parallel tracks, between which the relative geometric distortions are small in azimuth direction and large in range direction. Image pyramids are built firstly, and then corresponding layers of pyramids are matched from the top to the bottom. In the process, the similarity is measured by the normalized cross correlation (NCC algorithm, which is calculated from a rectangular window with the long side parallel to the azimuth direction. False matches are removed by the differential constrained random sample consensus (DC-RANSAC algorithm, which appends strong constraints in azimuth direction and weak constraints in range direction. Matching points in the lower pyramid images are predicted with the local bilinear transformation model in range direction. Experiments performed on ENVISAT ASAR and Chinese airborne SAR images validated the efficiency, correct ratio and accuracy of the proposed method.

  6. Object Georeferencing in UAV-Based SAR Terrain Images

    Łabowski Michał

    2016-12-01

    Full Text Available Synthetic aperture radars (SAR allow to obtain high resolution terrain images comparable with the resolution of optical methods. Radar imaging is independent on the weather conditions and the daylight. The process of analysis of the SAR images consists primarily of identifying of interesting objects. The ability to determine their geographical coordinates can increase usability of the solution from a user point of view. The paper presents a georeferencing method of the radar terrain images. The presented images were obtained from the SAR system installed on board an Unmanned Aerial Vehicle (UAV. The system was developed within a project under acronym WATSAR realized by the Military University of Technology and WB Electronics S.A. The source of the navigation data was an INS/GNSS system integrated by the Kalman filter with a feed-backward correction loop. The paper presents the terrain images obtained during flight tests and results of selected objects georeferencing with an assessment of the accuracy of the method.

  7. Imaging manifestations of the cavitation in pulmonary parenchyma of SARS

    Yuan Chunwang; Zhao Dawei; Wang Wei; Jia Cuiyu; Bai Chunsheng

    2004-01-01

    Objective: To investigate the imaging appearances of cavitation in pulmonary parenchyma and the clinical features of the cases of SARS. Methods: Chest imaging films and clinical data of 180 patients with clinically confirmed SARS were analyzed retrospectively. The imaging manifestations of cavitation and the clinical features of the patients were observed and evaluated. Results: Of 180 patients, cavitations were showed in 5 (2.8%), which were all found through X-ray or CT scanning. Most of them were round or irregular, and had thick wall. The 5 patients all had been in hospital and treated with more dosage antibiotics, antivirus medicines and glucocorticoid for long time, the glucocorticoid was used for 25-65 d, and in the first 10-15 days the dosage was 160-240 mg per day. In hospitalization, one of them had been diagnosed diabetes mellitus, four had increased fasting blood sugar, the counts of white blood cells [(14.1-20.4) x 10 9 /L] increased significantly, the percent of neutrophils might increased also. Meanwhile, there was a continue increase of lactate dehydrogenase (228.00-475.00 U/L), glutamic dehydrogenase (10.08-60.00 U/L) and hydroxybutyrate dehydrogenase (190.00-444.00 U/L) in lab examination. Conclusion: SARS can cause cavitation in pulmonary parenchyma in posterior process of the disease. CT scanning can find the cavitation earlier and accurately, catching the imaging features of them is helpful in differential diagnosis, guiding therapy and estimating prognosis

  8. SAR image regularization with fast approximate discrete minimization.

    Denis, Loïc; Tupin, Florence; Darbon, Jérôme; Sigelle, Marc

    2009-07-01

    Synthetic aperture radar (SAR) images, like other coherent imaging modalities, suffer from speckle noise. The presence of this noise makes the automatic interpretation of images a challenging task and noise reduction is often a prerequisite for successful use of classical image processing algorithms. Numerous approaches have been proposed to filter speckle noise. Markov random field (MRF) modelization provides a convenient way to express both data fidelity constraints and desirable properties of the filtered image. In this context, total variation minimization has been extensively used to constrain the oscillations in the regularized image while preserving its edges. Speckle noise follows heavy-tailed distributions, and the MRF formulation leads to a minimization problem involving nonconvex log-likelihood terms. Such a minimization can be performed efficiently by computing minimum cuts on weighted graphs. Due to memory constraints, exact minimization, although theoretically possible, is not achievable on large images required by remote sensing applications. The computational burden of the state-of-the-art algorithm for approximate minimization (namely the alpha -expansion) is too heavy specially when considering joint regularization of several images. We show that a satisfying solution can be reached, in few iterations, by performing a graph-cut-based combinatorial exploration of large trial moves. This algorithm is applied to joint regularization of the amplitude and interferometric phase in urban area SAR images.

  9. SAR Target Recognition Based on Multi-feature Multiple Representation Classifier Fusion

    Zhang Xinzheng

    2017-10-01

    Full Text Available In this paper, we present a Synthetic Aperture Radar (SAR image target recognition algorithm based on multi-feature multiple representation learning classifier fusion. First, it extracts three features from the SAR images, namely principal component analysis, wavelet transform, and Two-Dimensional Slice Zernike Moments (2DSZM features. Second, we harness the sparse representation classifier and the cooperative representation classifier with the above-mentioned features to get six predictive labels. Finally, we adopt classifier fusion to obtain the final recognition decision. We researched three different classifier fusion algorithms in our experiments, and the results demonstrate thatusing Bayesian decision fusion gives thebest recognition performance. The method based on multi-feature multiple representation learning classifier fusion integrates the discrimination of multi-features and combines the sparse and cooperative representation classification performance to gain complementary advantages and to improve recognition accuracy. The experiments are based on the Moving and Stationary Target Acquisition and Recognition (MSTAR database,and they demonstrate the effectiveness of the proposed approach.

  10. Advanced InSAR imaging for dune mapping

    Havivi, Shiran; August, Yitzhak; Blumberg, Dan G.; Rotman, Stanley R.

    2015-04-01

    Aeolian morphologies are formed in the presence of sufficient wind energy and available particles. These processes occur naturally or are further enhanced or reduced by human intervention. The dimensions of change are dependent primarily on the wind energy and surface properties. Since the 1970's, remote sensing imagery both optical and radar, are used for documentation and interpretation of the geomorphologic changes of sand dunes. Remote sensing studies of Aeolian morphologies is mostly useful to document major changes, yet, subtle changes, occurring in a period of days or months in scales of centimeters, are very difficult to detect in imagery. Interferometric Synthetic Aperture Radar (InSAR) is an imaging technique for measuring Earth's surface topography and deformation. InSAR images are produced by measuring the radar phase difference between two separated antennas that view the same surface area. Classical InSAR is based on high coherence between two images or more. The output (interferogram) can show subtle changes with an accuracy of several millimeters to centimeters. Very little work has been done on measuring or identifying the changes in dunes using InSAR. The reason is that dunes tend to be less coherent than firm, stable, surfaces. This research aims to demonstrate how interferometric decorrelation, or, coherence change detection, can be used for identifying dune instability. We hypothesize and demonstrate that the loss of radar coherence over time on dunes can be used as an indication of the dune's instability. When SAR images are acquired at sufficiently close intervals one can measure the time it takes to lose coherence and associate this time with geomorphic stability. To achieve our goals, the Nitzanim coastal dunes along the Mediterranean, 40 km south of Tel-Aviv, Israel, were chosen as a case study. The dunes in this area are of varying levels of stability and vegetation cover and have been monitored meteorologically, geomorphologically and

  11. Circular SAR Optimization Imaging Method of Buildings

    Wang Jian-feng

    2015-12-01

    Full Text Available The Circular Synthetic Aperture Radar (CSAR can obtain the entire scattering properties of targets because of its great ability of 360° observation. In this study, an optimal orientation of the CSAR imaging algorithm of buildings is proposed by applying a combination of coherent and incoherent processing techniques. FEKO software is used to construct the electromagnetic scattering modes and simulate the radar echo. The FEKO imaging results are compared with the isotropic scattering results. On comparison, the optimal azimuth coherent accumulation angle of CSAR imaging of buildings is obtained. Practically, the scattering directions of buildings are unknown; therefore, we divide the 360° echo of CSAR into many overlapped and few angle echoes corresponding to the sub-aperture and then perform an imaging procedure on each sub-aperture. Sub-aperture imaging results are applied to obtain the all-around image using incoherent fusion techniques. The polarimetry decomposition method is used to decompose the all-around image and further retrieve the edge information of buildings successfully. The proposed method is validated with P-band airborne CSAR data from Sichuan, China.

  12. Generalized internal multiple imaging

    Zuberi, M. A. H.; Alkhalifah, Tariq Ali

    2014-01-01

    Internal multiples deteriorate the image when the imaging procedure assumes only single scattering, especially if the velocity model does not have sharp contrasts to reproduce such scattering in the Green’s function through forward modeling

  13. Generalized internal multiple imaging

    Zuberi, M. A. H.

    2014-08-05

    Internal multiples deteriorate the image when the imaging procedure assumes only single scattering, especially if the velocity model does not have sharp contrasts to reproduce such scattering in the Green’s function through forward modeling. If properly imaged, internal multiples (internally scattered energy) can enhance the seismic image. Conventionally, to image internal multiples, accurate, sharp contrasts in the velocity model are required to construct a Green’s function with all the scattered energy. As an alternative, we have developed a generalized internal multiple imaging procedure that images any order internal scattering using the background Green’s function (from the surface to each image point), constructed from a smooth velocity model, usually used for conventional imaging. For the first-order internal multiples, the approach consisted of three steps, in which we first back propagated the recorded surface seismic data using the background Green’s function, then crosscorrelated the back-propagated data with the recorded data, and finally crosscorrelated the result with the original background Green’s function. This procedure images the contribution of the recorded first-order internal multiples, and it is almost free of the single-scattering recorded energy. The cost includes one additional crosscorrelation over the conventional single-scattering imaging application. We generalized this method to image internal multiples of any order separately. The resulting images can be added to the conventional single-scattering image, obtained, e.g., from Kirchhoff or reverse-time migration, to enhance the image. Application to synthetic data with reflectors illuminated by multiple scattering (double scattering) demonstrated the effectiveness of the approach.

  14. Accurate Analysis of Target Characteristic in Bistatic SAR Images: A Dihedral Corner Reflectors Case.

    Ao, Dongyang; Li, Yuanhao; Hu, Cheng; Tian, Weiming

    2017-12-22

    The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS) in the synthetic aperture radar (SAR) images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures.

  15. Road detection in SAR images using a tensor voting algorithm

    Shen, Dajiang; Hu, Chun; Yang, Bing; Tian, Jinwen; Liu, Jian

    2007-11-01

    In this paper, the problem of the detection of road networks in Synthetic Aperture Radar (SAR) images is addressed. Most of the previous methods extract the road by detecting lines and network reconstruction. Traditional algorithms such as MRFs, GA, Level Set, used in the progress of reconstruction are iterative. The tensor voting methodology we proposed is non-iterative, and non-sensitive to initialization. Furthermore, the only free parameter is the size of the neighborhood, related to the scale. The algorithm we present is verified to be effective when it's applied to the road extraction using the real Radarsat Image.

  16. Scalable Track Detection in SAR CCD Images

    Chow, James G [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Quach, Tu-Thach [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-03-01

    Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images ta ken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are often too simple to capture natural track features such as continuity and parallelism. We present a simple convolutional network architecture consisting of a series of 3-by-3 convolutions to detect tracks. The network is trained end-to-end to learn natural track features entirely from data. The network is computationally efficient and improves the F-score on a standard dataset to 0.988, up fr om 0.907 obtained by the current state-of-the-art method.

  17. AUTOMATIC CALCULATION OF OIL SLICK AREA FROM MULTIPLE SAR ACQUISITIONS FOR DEEPWATER HORIZON OIL SPILL

    B. Osmanoğlu

    2012-07-01

    Full Text Available The Deepwater Horizon oil spill occurred in the Gulf of Mexico in April 2010 and became the largest accidental marine oil spill in history. Oil leaked continuously between April 20th and July 15th of 2010, releasing about 780, 000m3 of crude oil into the Gulf of Mexico. The oil spill caused extensive economical and ecological damage to the areas it reached, affecting the marine and wildlife habitats along with fishing and tourism industries. For oil spill mitigation efforts, it is important to determine the areal extent, and most recent position of the contaminated area. Satellitebased oil pollution monitoring systems are being used for monitoring and in hazard response efforts. Due to their high accuracy, frequent acquisitions, large area coverage and day-and-night operation Synthetic Aperture Radar (SAR satellites are a major contributer of monitoring marine environments for oil spill detection. We developed a new algorithm for determining the extent of the oil spill from multiple SAR images, that are acquired with short temporal intervals using different sensors. Combining the multi-polarization data from Radarsat-2 (C-band, Envisat ASAR (C-band and Alos-PALSAR (L-band sensors, we calculate the extent of the oil spill with higher accuracy than what is possible from only one image. Short temporal interval between acquisitions (hours to days allow us to eliminate artifacts and increase accuracy. Our algorithm works automatically without any human intervention to deliver products in a timely manner in time critical operations. Acquisitions using different SAR sensors are radiometrically calibrated and processed individually to obtain oil spill area extent. Furthermore the algorithm provides probability maps of the areas that are classified as oil slick. This probability information is then combined with other acquisitions to estimate the combined probability map for the spill.

  18. Improved SAR Amplitude Image Offset Measurements for Deriving Three-Dimensional Coseismic Displacements

    Wang, Teng; Jonsson, Sigurjon

    2015-01-01

    Offsets of synthetic aperture radar (SAR) images have played an important role in deriving complete three-dimensional (3-D) surface displacement fields in geoscientific applications. However, offset maps often suffer from multiple outliers and patch-like artifacts, because the standard offset-measurement method is a regular moving-window operation that does not consider the scattering characteristics of the ground. Here, we show that by focusing the offset measurements on predetected strong reflectors, the reliability and accuracy of SAR offsets can be significantly improved. Application to the 2011 Van (Turkey) earthquake reveals a clear deformation signal from an otherwise decorrelated interferogram, making derivation of the 3-D coseismic displacement field possible. Our proposed method can improve mapping of coseismic deformation and other ground displacements, such as glacier flow and landslide movement when strong reflectors exist.

  19. Improved SAR Amplitude Image Offset Measurements for Deriving Three-Dimensional Coseismic Displacements

    Wang, Teng

    2015-02-03

    Offsets of synthetic aperture radar (SAR) images have played an important role in deriving complete three-dimensional (3-D) surface displacement fields in geoscientific applications. However, offset maps often suffer from multiple outliers and patch-like artifacts, because the standard offset-measurement method is a regular moving-window operation that does not consider the scattering characteristics of the ground. Here, we show that by focusing the offset measurements on predetected strong reflectors, the reliability and accuracy of SAR offsets can be significantly improved. Application to the 2011 Van (Turkey) earthquake reveals a clear deformation signal from an otherwise decorrelated interferogram, making derivation of the 3-D coseismic displacement field possible. Our proposed method can improve mapping of coseismic deformation and other ground displacements, such as glacier flow and landslide movement when strong reflectors exist.

  20. Fusion method of SAR and optical images for urban object extraction

    Jia, Yonghong; Blum, Rick S.; Li, Fangfang

    2007-11-01

    A new image fusion method of SAR, Panchromatic (Pan) and multispectral (MS) data is proposed. First of all, SAR texture is extracted by ratioing the despeckled SAR image to its low pass approximation, and is used to modulate high pass details extracted from the available Pan image by means of the á trous wavelet decomposition. Then, high pass details modulated with the texture is applied to obtain the fusion product by HPFM (High pass Filter-based Modulation) fusion method. A set of image data including co-registered Landsat TM, ENVISAT SAR and SPOT Pan is used for the experiment. The results demonstrate accurate spectral preservation on vegetated regions, bare soil, and also on textured areas (buildings and road network) where SAR texture information enhances the fusion product, and the proposed approach is effective for image interpret and classification.

  1. SIMULATION OF SHIP GENERATED TURBULENT AND VORTICAL WAKE IMAGING BY SAR

    Wang Aiming; Zhu Minhui

    2004-01-01

    Synthetic Aperture Radar (SAR) imaging of ocean surface features is studied. The simulation of the turbulent and vortical features generated by a moving ship and SAR imaging of these wakes is carried out. The turbulent wake damping the ocean surface capillary waves may be partially responsible for the suppression of surface waves near the ship track. The vortex pair generating a change in the lateral flow field behind the ship may be partially responsible for an enhancement of the waves near the edges of the smooth area. These hydrodynamic phenomena as well as the changes of radar backscatter generated by turbulence and vortex are simulated.An SAR imaging model is then used on such ocean surface features to provide SAR images.Comparison of two ships' simulated SAR images shows that the wake features are different for various ship parameters.

  2. Segmentation of Polarimetric SAR Images Usig Wavelet Transformation and Texture Features

    Rezaeian, A.; Homayouni, S.; Safari, A.

    2015-12-01

    Polarimetric Synthetic Aperture Radar (PolSAR) sensors can collect useful observations from earth's surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR) are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT). Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM) and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

  3. SEGMENTATION OF POLARIMETRIC SAR IMAGES USIG WAVELET TRANSFORMATION AND TEXTURE FEATURES

    A. Rezaeian

    2015-12-01

    Full Text Available Polarimetric Synthetic Aperture Radar (PolSAR sensors can collect useful observations from earth’s surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT. Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

  4. An Efficient SAR Image Segmentation Framework Using Transformed Nonlocal Mean and Multi-Objective Clustering in Kernel Space

    Dongdong Yang

    2015-02-01

    Full Text Available Synthetic aperture radar (SAR image segmentation usually involves two crucial issues: suitable speckle noise removing technique and effective image segmentation methodology. Here, an efficient SAR image segmentation method considering both of the two aspects is presented. As for the first issue, the famous nonlocal mean (NLM filter is introduced in this study to suppress the multiplicative speckle noise in SAR image. Furthermore, to achieve a higher denoising accuracy, the local neighboring pixels in the searching window are projected into a lower dimensional subspace by principal component analysis (PCA. Thus, the nonlocal mean filter is implemented in the subspace. Afterwards, a multi-objective clustering algorithm is proposed using the principals of artificial immune system (AIS and kernel-induced distance measures. The multi-objective clustering has been shown to discover the data distribution with different characteristics and the kernel methods can improve its robustness to noise and outliers. Experiments demonstrate that the proposed method is able to partition the SAR image robustly and accurately than the conventional approaches.

  5. On Signal Modeling of Moon-Based Synthetic Aperture Radar (SAR Imaging of Earth

    Zhen Xu

    2018-03-01

    Full Text Available The Moon-based Synthetic Aperture Radar (Moon-Based SAR, using the Moon as a platform, has a great potential to offer global-scale coverage of the earth’s surface with a high revisit cycle and is able to meet the scientific requirements for climate change study. However, operating in the lunar orbit, Moon-Based SAR imaging is confined within a complex geometry of the Moon-Based SAR, Moon, and Earth, where both rotation and revolution have effects. The extremely long exposure time of Moon-Based SAR presents a curved moving trajectory and the protracted time-delay in propagation makes the “stop-and-go” assumption no longer valid. Consequently, the conventional SAR imaging technique is no longer valid for Moon-Based SAR. This paper develops a Moon-Based SAR theory in which a signal model is derived. The Doppler parameters in the context of lunar revolution with the removal of ‘stop-and-go’ assumption are first estimated, and then characteristics of Moon-Based SAR imaging’s azimuthal resolution are analyzed. In addition, a signal model of Moon-Based SAR and its two-dimensional (2-D spectrum are further derived. Numerical simulation using point targets validates the signal model and enables Doppler parameter estimation for image focusing.

  6. Bone scintigraphy in post-SARS patients and compared with magnetic resonance imaging

    Wang Qian; Huang Lili; Qin Shuling

    2004-01-01

    Objective: To study the characteristics of bone scintigraphy in post-SARS patients and evaluate the usefulness of bone scintigraphy in the prediction of avascular osteonecrosis (AVN) comparing with the MR imaging.. Methods: Our study included 66 patients who were diagnosed as SARS based on the diagnostic criteria issued by the Ministry of Health of China (MHC), including 46 women and 20 men. Their ages ranged from 19 to 63 years (mean, 31.6±0.1 years). All of the patients were treated with methyprednisonlone, rabavirin, broad spectrum antimicrobials and supportive therapy. Dosage of methyprednisonlone was 80∼800 mg/d for 4-72 days. Of them, varied seat of joint pain occurred in 47 patients 3 to 18 weeks after the onset of SARS. Since multiple joints were involved in many patients, bone scintigraphy was performed for screening AVN. The other 19 patients without of evident joint pain were also examined as their demand. Informed consents were obtained in all of the examined patients. No previously joint pain or trauma history was found in this group of patients. Of the 66 patients, planer X-ray was performed in 34 of the symptomatic patients previous to the scintigraphy, but it was negative in all. MR examination was performed in 54 patients before or after the scintigraphy, and the interval between two the tests was average of 8 days (range, 0 to 30 days). In addition, 27 consecutive cases aged lower than 45 years (mean, 40.4±0.8 years) with breast cancer who underwent bone scintigraphy for screening metastastic disease and had negative results were also involved as a control group. Whole body skeletal scintigraphy was performed 3 hours after intravenous administration of technetium-99m methylene-diphosphonate 740 MBq. Increased uptake lesion seen in the limb joints was defined as positive, but 'hot patella' sign was considered to be non diagnostic value. When a lesion was found in the whole body imaging, corresponding regional image was further taken. Two

  7. Multi-Pixel Simultaneous Classification of PolSAR Image Using Convolutional Neural Networks

    Xu, Xin; Gui, Rong; Pu, Fangling

    2018-01-01

    Convolutional neural networks (CNN) have achieved great success in the optical image processing field. Because of the excellent performance of CNN, more and more methods based on CNN are applied to polarimetric synthetic aperture radar (PolSAR) image classification. Most CNN-based PolSAR image classification methods can only classify one pixel each time. Because all the pixels of a PolSAR image are classified independently, the inherent interrelation of different land covers is ignored. We use a fixed-feature-size CNN (FFS-CNN) to classify all pixels in a patch simultaneously. The proposed method has several advantages. First, FFS-CNN can classify all the pixels in a small patch simultaneously. When classifying a whole PolSAR image, it is faster than common CNNs. Second, FFS-CNN is trained to learn the interrelation of different land covers in a patch, so it can use the interrelation of land covers to improve the classification results. The experiments of FFS-CNN are evaluated on a Chinese Gaofen-3 PolSAR image and other two real PolSAR images. Experiment results show that FFS-CNN is comparable with the state-of-the-art PolSAR image classification methods. PMID:29510499

  8. Robust tie points selection for InSAR image coregistration

    Skanderi, Takieddine; Chabira, Boulerbah; Afifa, Belkacem; Belhadj Aissa, Aichouche

    2013-10-01

    Image coregistration is an important step in SAR interferometry which is a well known method for DEM generation and surface displacement monitoring. A practical and widely used automatic coregistration algorithm is based on selecting a number of tie points in the master image and looking for the correspondence of each point in the slave image using correlation technique. The characteristics of these points, their number and their distribution have a great impact on the reliability of the estimated transformation. In this work, we present a method for automatic selection of suitable tie points that are well distributed over the common area without decreasing the desired tie points' number. First we select candidate points using Harris operator. Then from these points we select tie points depending on their cornerness measure (the highest first). Once a tie point is selected, its correspondence is searched for in the slave image, if the similarity measure maximum is less than a given threshold or it is at the border of the search window, this point is discarded and we proceed to the next Harris point, else, the cornerness of the remaining candidates Harris points are multiplied by a spatially radially increasing function centered at the selected point to disadvantage the points in a neighborhood of a radius determined from the size of the common area and the desired number of points. This is repeated until the desired number of points is selected. Results of an ERS1/2 tandem pair are presented and discussed.

  9. Improved GO/PO method and its application to wideband SAR image of conducting objects over rough surface

    Jiang, Wang-Qiang; Zhang, Min; Nie, Ding; Jiao, Yong-Chang

    2018-04-01

    To simulate the multiple scattering effect of target in synthetic aperture radar (SAR) image, the hybrid method GO/PO method, which combines the geometrical optics (GO) and physical optics (PO), is employed to simulate the scattering field of target. For ray tracing is time-consuming, the Open Graphics Library (OpenGL) is usually employed to accelerate the process of ray tracing. Furthermore, the GO/PO method is improved for the simulation in low pixel situation. For the improved GO/PO method, the pixels are arranged corresponding to the rectangular wave beams one by one, and the GO/PO result is the sum of the contribution values of all the rectangular wave beams. To get high-resolution SAR image, the wideband echo signal is simulated which includes information of many electromagnetic (EM) waves with different frequencies. Finally, the improved GO/PO method is used to simulate the SAR image of targets above rough surface. And the effects of reflected rays and the size of pixel matrix on the SAR image are also discussed.

  10. Detectability Analysis of Road Vehicles in Radarsat-2 Fully Polarimetric SAR Images for Traffic Monitoring

    Bo Zhang

    2017-02-01

    Full Text Available By acquiring information over a wide area regardless of weather conditions and solar illumination, space-borne Synthetic Aperture Radar (SAR has the potential to be a promising application for traffic monitoring. However, the backscatter character of a vehicle in a SAR image is unstable and varies with image parameters, such as aspect and incidence angle. To investigate vehicle detectability in SAR images for traffic monitoring applications, images of four common types of vehicles in China were acquired using the fully polarimetric (FP SAR of Radarsat-2 in our experiments. Methods for measuring a vehicle’s aspect angle and backscatter intensity are introduced. The experimental FP SAR images are used to analyze the detectability, which is affected by factors such as vehicle size, vehicle shape, and aspect angle. Moreover, a new metric to improve vehicle detectability in FP SAR images is proposed and compared with the well-known intensity metric. The experimental results show that shape is a crucial factor in affecting the backscatter intensity of vehicles, which also oscillates with varying aspect angle. If the size of a vehicle is smaller than the SAR image resolution, using the intensity metric would result in low detectability. However, it could be improved in an FP SAR image by using the proposed metric. Compared with the intensity metric, the overall detectability is improved from 72% to 90% in our experiments. Therefore, this study indicates that FP SAR images have the ability to detect stationary vehicles on the road and are meaningful for traffic monitoring.

  11. Effect of Antenna Pointing Errors on SAR Imaging Considering the Change of the Point Target Location

    Zhang, Xin; Liu, Shijie; Yu, Haifeng; Tong, Xiaohua; Huang, Guoman

    2018-04-01

    Towards spaceborne spotlight SAR, the antenna is regulated by the SAR system with specific regularity, so the shaking of the internal mechanism is inevitable. Moreover, external environment also has an effect on the stability of SAR platform. Both of them will cause the jitter of the SAR platform attitude. The platform attitude instability will introduce antenna pointing error on both the azimuth and range directions, and influence the acquisition of SAR original data and ultimate imaging quality. In this paper, the relations between the antenna pointing errors and the three-axis attitude errors are deduced, then the relations between spaceborne spotlight SAR imaging of the point target and antenna pointing errors are analysed based on the paired echo theory, meanwhile, the change of the azimuth antenna gain is considered as the spotlight SAR platform moves ahead. The simulation experiments manifest the effects on spotlight SAR imaging caused by antenna pointing errors are related to the target location, that is, the pointing errors of the antenna beam will severely influence the area far away from the scene centre of azimuth direction in the illuminated scene.

  12. Hybrid Geometric Calibration Method for Multi-Platform Spaceborne SAR Image with Sparse Gcps

    Lv, G.; Tang, X.; Ai, B.; Li, T.; Chen, Q.

    2018-04-01

    Geometric calibration is able to provide high-accuracy geometric coordinates of spaceborne SAR image through accurate geometric parameters in the Range-Doppler model by ground control points (GCPs). However, it is very difficult to obtain GCPs that covering large-scale areas, especially in the mountainous regions. In addition, the traditional calibration method is only used for single platform SAR images and can't support the hybrid geometric calibration for multi-platform images. To solve the above problems, a hybrid geometric calibration method for multi-platform spaceborne SAR images with sparse GCPs is proposed in this paper. First, we calibrate the master image that contains GCPs. Secondly, the point tracking algorithm is used to obtain the tie points (TPs) between the master and slave images. Finally, we calibrate the slave images using TPs as the GCPs. We take the Beijing-Tianjin- Hebei region as an example to study SAR image hybrid geometric calibration method using 3 TerraSAR-X images, 3 TanDEM-X images and 5 GF-3 images covering more than 235 kilometers in the north-south direction. Geometric calibration of all images is completed using only 5 GCPs. The GPS data extracted from GNSS receiver are used to assess the plane accuracy after calibration. The results after geometric calibration with sparse GCPs show that the geometric positioning accuracy is 3 m for TSX/TDX images and 7.5 m for GF-3 images.

  13. SAR image classification based on CNN in real and simulation datasets

    Peng, Lijiang; Liu, Ming; Liu, Xiaohua; Dong, Liquan; Hui, Mei; Zhao, Yuejin

    2018-04-01

    Convolution neural network (CNN) has made great success in image classification tasks. Even in the field of synthetic aperture radar automatic target recognition (SAR-ATR), state-of-art results has been obtained by learning deep representation of features on the MSTAR benchmark. However, the raw data of MSTAR have shortcomings in training a SAR-ATR model because of high similarity in background among the SAR images of each kind. This indicates that the CNN would learn the hierarchies of features of backgrounds as well as the targets. To validate the influence of the background, some other SAR images datasets have been made which contains the simulation SAR images of 10 manufactured targets such as tank and fighter aircraft, and the backgrounds of simulation SAR images are sampled from the whole original MSTAR data. The simulation datasets contain the dataset that the backgrounds of each kind images correspond to the one kind of backgrounds of MSTAR targets or clutters and the dataset that each image shares the random background of whole MSTAR targets or clutters. In addition, mixed datasets of MSTAR and simulation datasets had been made to use in the experiments. The CNN architecture proposed in this paper are trained on all datasets mentioned above. The experimental results shows that the architecture can get high performances on all datasets even the backgrounds of the images are miscellaneous, which indicates the architecture can learn a good representation of the targets even though the drastic changes on background.

  14. High Resolution SAR Imaging Employing Geometric Features for Extracting Seismic Damage of Buildings

    Cui, L. P.; Wang, X. P.; Dou, A. X.; Ding, X.

    2018-04-01

    Synthetic Aperture Radar (SAR) image is relatively easy to acquire but difficult for interpretation. This paper probes how to identify seismic damage of building using geometric features of SAR. The SAR imaging geometric features of buildings, such as the high intensity layover, bright line induced by double bounce backscattering and dark shadow is analysed, and show obvious differences texture features of homogeneity, similarity and entropy in combinatorial imaging geometric regions between the un-collapsed and collapsed buildings in airborne SAR images acquired in Yushu city damaged by 2010 Ms7.1 Yushu, Qinghai, China earthquake, which implicates a potential capability to discriminate collapsed and un-collapsed buildings from SAR image. Study also shows that the proportion of highlight (layover & bright line) area (HA) is related to the seismic damage degree, thus a SAR image damage index (SARDI), which related to the ratio of HA to the building occupation are of building in a street block (SA), is proposed. While HA is identified through feature extraction with high-pass and low-pass filtering of SAR image in frequency domain. A partial region with 58 natural street blocks in the Yushu City are selected as study area. Then according to the above method, HA is extracted, SARDI is then calculated and further classified into 3 classes. The results show effective through validation check with seismic damage classes interpreted artificially from post-earthquake airborne high resolution optical image, which shows total classification accuracy 89.3 %, Kappa coefficient 0.79 and identical to the practical seismic damage distribution. The results are also compared and discussed with the building damage identified from SAR image available by other authors.

  15. a Statistical Texture Feature for Building Collapse Information Extraction of SAR Image

    Li, L.; Yang, H.; Chen, Q.; Liu, X.

    2018-04-01

    Synthetic Aperture Radar (SAR) has become one of the most important ways to extract post-disaster collapsed building information, due to its extreme versatility and almost all-weather, day-and-night working capability, etc. In view of the fact that the inherent statistical distribution of speckle in SAR images is not used to extract collapsed building information, this paper proposed a novel texture feature of statistical models of SAR images to extract the collapsed buildings. In the proposed feature, the texture parameter of G0 distribution from SAR images is used to reflect the uniformity of the target to extract the collapsed building. This feature not only considers the statistical distribution of SAR images, providing more accurate description of the object texture, but also is applied to extract collapsed building information of single-, dual- or full-polarization SAR data. The RADARSAT-2 data of Yushu earthquake which acquired on April 21, 2010 is used to present and analyze the performance of the proposed method. In addition, the applicability of this feature to SAR data with different polarizations is also analysed, which provides decision support for the data selection of collapsed building information extraction.

  16. TESTING THE GENERALIZATION EFFICIENCY OF OIL SLICK CLASSIFICATION ALGORITHM USING MULTIPLE SAR DATA FOR DEEPWATER HORIZON OIL SPILL

    C. Ozkan

    2012-07-01

    Full Text Available Marine oil spills due to releases of crude oil from tankers, offshore platforms, drilling rigs and wells, etc. are seriously affecting the fragile marine and coastal ecosystem and cause political and environmental concern. A catastrophic explosion and subsequent fire in the Deepwater Horizon oil platform caused the platform to burn and sink, and oil leaked continuously between April 20th and July 15th of 2010, releasing about 780,000 m3 of crude oil into the Gulf of Mexico. Today, space-borne SAR sensors are extensively used for the detection of oil spills in the marine environment, as they are independent from sun light, not affected by cloudiness, and more cost-effective than air patrolling due to covering large areas. In this study, generalization extent of an object based classification algorithm was tested for oil spill detection using multiple SAR imagery data. Among many geometrical, physical and textural features, some more distinctive ones were selected to distinguish oil and look alike objects from each others. The tested classifier was constructed from a Multilayer Perception Artificial Neural Network trained by ABC, LM and BP optimization algorithms. The training data to train the classifier were constituted from SAR data consisting of oil spill originated from Lebanon in 2007. The classifier was then applied to the Deepwater Horizon oil spill data in the Gulf of Mexico on RADARSAT-2 and ALOS PALSAR images to demonstrate the generalization efficiency of oil slick classification algorithm.

  17. Coseismic displacements from SAR image offsets between different satellite sensors: Application to the 2001 Bhuj (India) earthquake

    Wang, Teng

    2015-09-05

    Synthetic aperture radar (SAR) image offset tracking is increasingly being used for measuring ground displacements, e.g., due to earthquakes and landslide movement. However, this technique has been applied only to images acquired by the same or identical satellites. Here we propose a novel approach for determining offsets between images acquired by different satellite sensors, extending the usability of existing SAR image archives. The offsets are measured between two multiimage reflectivity maps obtained from different SAR data sets, which provide significantly better results than with single preevent and postevent images. Application to the 2001 Mw7.6 Bhuj earthquake reveals, for the first time, its near-field deformation using multiple preearthquake ERS and postearthquake Envisat images. The rupture model estimated from these cross-sensor offsets and teleseismic waveforms shows a compact fault slip pattern with fairly short rise times (<3 s) and a large stress drop (20 MPa), explaining the intense shaking observed in the earthquake.

  18. Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity Estimation

    Maria Daniela Graziano

    2016-06-01

    Full Text Available A new algorithm for ship wake detection is developed with the aim of ship heading and velocity estimation. It exploits the Radon transform and utilizes merit indexes in the intensity domain to validate the detected linear features as real components of the ship wake. Finally, ship velocity is estimated by state-of-the-art techniques of azimuth shift and Kelvin arm wavelength. The algorithm is applied to 13 X-band SAR images from the TerraSAR-X and COSMO/SkyMed missions with different polarization and incidence angles. Results show that the vast majority of wake features are correctly detected and validated also in critical situations, i.e., when multiple wake appearances or dark areas not related to wake features are imaged. The ship route estimations are validated with truth-at-sea in seven cases. Finally, it is also verified that the algorithm does not detect wakes in the surroundings of 10 ships without wake appearances.

  19. Accurate Analysis of Target Characteristic in Bistatic SAR Images: A Dihedral Corner Reflectors Case

    Dongyang Ao

    2017-12-01

    Full Text Available The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS in the synthetic aperture radar (SAR images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures.

  20. Accurate Analysis of Target Characteristic in Bistatic SAR Images: A Dihedral Corner Reflectors Case

    Ao, Dongyang; Hu, Cheng; Tian, Weiming

    2017-01-01

    The dihedral corner reflectors are the basic geometric structure of many targets and are the main contributions of radar cross section (RCS) in the synthetic aperture radar (SAR) images. In stealth technologies, the elaborate design of the dihedral corners with different opening angles is a useful approach to reduce the high RCS generated by multiple reflections. As bistatic synthetic aperture sensors have flexible geometric configurations and are sensitive to the dihedral corners with different opening angles, they specially fit for the stealth target detections. In this paper, the scattering characteristic of dihedral corner reflectors is accurately analyzed in bistatic synthetic aperture images. The variation of RCS with the changing opening angle is formulated and the method to design a proper bistatic radar for maximizing the detection capability is provided. Both the results of the theoretical analysis and the experiments show the bistatic SAR could detect the dihedral corners, under a certain bistatic angle which is related to the geometry of target structures. PMID:29271917

  1. Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN

    Guo, Hao; Wu, Danni; An, Jubai

    2017-01-01

    Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred f...

  2. Pixel Classification of SAR ice images using ANFIS-PSO Classifier

    G. Vasumathi

    2016-12-01

    Full Text Available Synthetic Aperture Radar (SAR is playing a vital role in taking extremely high resolution radar images. It is greatly used to monitor the ice covered ocean regions. Sea monitoring is important for various purposes which includes global climate systems and ship navigation. Classification on the ice infested area gives important features which will be further useful for various monitoring process around the ice regions. Main objective of this paper is to classify the SAR ice image that helps in identifying the regions around the ice infested areas. In this paper three stages are considered in classification of SAR ice images. It starts with preprocessing in which the speckled SAR ice images are denoised using various speckle removal filters; comparison is made on all these filters to find the best filter in speckle removal. Second stage includes segmentation in which different regions are segmented using K-means and watershed segmentation algorithms; comparison is made between these two algorithms to find the best in segmenting SAR ice images. The last stage includes pixel based classification which identifies and classifies the segmented regions using various supervised learning classifiers. The algorithms includes Back propagation neural networks (BPN, Fuzzy Classifier, Adaptive Neuro Fuzzy Inference Classifier (ANFIS classifier and proposed ANFIS with Particle Swarm Optimization (PSO classifier; comparison is made on all these classifiers to propose which classifier is best suitable for classifying the SAR ice image. Various evaluation metrics are performed separately at all these three stages.

  3. Wind mapping offshore in coastal Mediterranean area using SAR images

    Calaudi, Rosamaria; Arena, Felice; Badger, Merete

    Satellite observations of the ocean surface from Synthetic Aperture Radars (SAR) provide information about the spatial wind variability over large areas. This is of special interest in the Mediterranean, where spatial wind information is only provided by sparse buoys, often with long periods...... of missing data. Here, we focus on evaluating the use of SAR for offshore wind mapping. Preliminary results from the analysis of SAR-based ocean winds in Mediterranean areas show interesting large scale wind flow features consistent with results from previous studies using numerical models and space borne...

  4. A Novel 3D Imaging Method for Airborne Downward-Looking Sparse Array SAR Based on Special Squint Model

    Xiaozhen Ren

    2014-01-01

    Full Text Available Three-dimensional (3D imaging technology based on antenna array is one of the most important 3D synthetic aperture radar (SAR high resolution imaging modes. In this paper, a novel 3D imaging method is proposed for airborne down-looking sparse array SAR based on the imaging geometry and the characteristic of echo signal. The key point of the proposed algorithm is the introduction of a special squint model in cross track processing to obtain accurate focusing. In this special squint model, point targets with different cross track positions have different squint angles at the same range resolution cell, which is different from the conventional squint SAR. However, after theory analysis and formulation deduction, the imaging procedure can be processed with the uniform reference function, and the phase compensation factors and algorithm realization procedure are demonstrated in detail. As the method requires only Fourier transform and multiplications and thus avoids interpolations, it is computationally efficient. Simulations with point scatterers are used to validate the method.

  5. RAMP AMM-1 SAR Image Mosaic of Antarctica

    National Aeronautics and Space Administration — In 1997, the Canadian RADARSAT-1 satellite was rotated in orbit so that its Synthetic Aperture Radar (SAR) antenna looked south towards Antarctica. This permitted...

  6. APPLICATION OF FUSION WITH SAR AND OPTICAL IMAGES IN LAND USE CLASSIFICATION BASED ON SVM

    C. Bao

    2012-07-01

    Full Text Available As the increment of remote sensing data with multi-space resolution, multi-spectral resolution and multi-source, data fusion technologies have been widely used in geological fields. Synthetic Aperture Radar (SAR and optical camera are two most common sensors presently. The multi-spectral optical images express spectral features of ground objects, while SAR images express backscatter information. Accuracy of the image classification could be effectively improved fusing the two kinds of images. In this paper, Terra SAR-X images and ALOS multi-spectral images were fused for land use classification. After preprocess such as geometric rectification, radiometric rectification noise suppression and so on, the two kind images were fused, and then SVM model identification method was used for land use classification. Two different fusion methods were used, one is joining SAR image into multi-spectral images as one band, and the other is direct fusing the two kind images. The former one can raise the resolution and reserve the texture information, and the latter can reserve spectral feature information and improve capability of identifying different features. The experiment results showed that accuracy of classification using fused images is better than only using multi-spectral images. Accuracy of classification about roads, habitation and water bodies was significantly improved. Compared to traditional classification method, the method of this paper for fused images with SVM classifier could achieve better results in identifying complicated land use classes, especially for small pieces ground features.

  7. Multiple alignment analysis on phylogenetic tree of the spread of SARS epidemic using distance method

    Amiroch, S.; Pradana, M. S.; Irawan, M. I.; Mukhlash, I.

    2017-09-01

    Multiple Alignment (MA) is a particularly important tool for studying the viral genome and determine the evolutionary process of the specific virus. Application of MA in the case of the spread of the Severe acute respiratory syndrome (SARS) epidemic is an interesting thing because this virus epidemic a few years ago spread so quickly that medical attention in many countries. Although there has been a lot of software to process multiple sequences, but the use of pairwise alignment to process MA is very important to consider. In previous research, the alignment between the sequences to process MA algorithm, Super Pairwise Alignment, but in this study used a dynamic programming algorithm Needleman wunchs simulated in Matlab. From the analysis of MA obtained and stable region and unstable which indicates the position where the mutation occurs, the system network topology that produced the phylogenetic tree of the SARS epidemic distance method, and system area networks mutation.

  8. Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling

    Yu, Ze; Lin, Peng; Xiao, Peng; Kang, Lihong; Li, Chunsheng

    2016-01-01

    Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range and azimuth. As a result, efficient and precise imaging becomes difficult. This paper analyzes and models spatial variance for GEO SAR in the time and frequency domains. A novel algorithm for GEO SAR imaging with a resolution of 2 m in both the ground cross-range and range directions is proposed, which is composed of five steps. The first is to eliminate linear azimuth variance through the first azimuth time scaling. The second is to achieve RCM correction and range compression. The third is to correct residual azimuth variance by the second azimuth time-frequency scaling. The fourth and final steps are to accomplish azimuth focusing and correct geometric distortion. The most important innovation of this algorithm is implementation of the time-frequency scaling to correct high-order azimuth variance. As demonstrated by simulation results, this algorithm can accomplish GEO SAR imaging with good and uniform imaging quality over the entire swath. PMID:27428974

  9. (Non-) homomorphic approaches to denoise intensity SAR images with non-local means and stochastic distances

    Penna, Pedro A. A.; Mascarenhas, Nelson D. A.

    2018-02-01

    The development of new methods to denoise images still attract researchers, who seek to combat the noise with the minimal loss of resolution and details, like edges and fine structures. Many algorithms have the goal to remove additive white Gaussian noise (AWGN). However, it is not the only type of noise which interferes in the analysis and interpretation of images. Therefore, it is extremely important to expand the filters capacity to different noise models present in li-terature, for example the multiplicative noise called speckle that is present in synthetic aperture radar (SAR) images. The state-of-the-art algorithms in remote sensing area work with similarity between patches. This paper aims to develop two approaches using the non local means (NLM), developed for AWGN. In our research, we expanded its capacity for intensity SAR ima-ges speckle. The first approach is grounded on the use of stochastic distances based on the G0 distribution without transforming the data to the logarithm domain, like homomorphic transformation. It takes into account the speckle and backscatter to estimate the parameters necessary to compute the stochastic distances on NLM. The second method uses a priori NLM denoising with a homomorphic transformation and applies the inverse Gamma distribution to estimate the parameters that were used into NLM with stochastic distances. The latter method also presents a new alternative to compute the parameters for the G0 distribution. Finally, this work compares and analyzes the synthetic and real results of the proposed methods with some recent filters of the literature.

  10. Feature Fusion Based Road Extraction for HJ-1-C SAR Image

    Lu Ping-ping

    2014-06-01

    Full Text Available Road network extraction in SAR images is one of the key tasks of military and civilian technologies. To solve the issues of road extraction of HJ-1-C SAR images, a road extraction algorithm is proposed based on the integration of ratio and directional information. Due to the characteristic narrow dynamic range and low signal to noise ratio of HJ-1-C SAR images, a nonlinear quantization and an image filtering method based on a multi-scale autoregressive model are proposed here. A road extraction algorithm based on information fusion, which considers ratio and direction information, is also proposed. By processing Radon transformation, main road directions can be extracted. Cross interferences can be suppressed, and the road continuity can then be improved by the main direction alignment and secondary road extraction. The HJ-1-C SAR image acquired in Wuhan, China was used to evaluate the proposed method. The experimental results show good performance with correctness (80.5% and quality (70.1% when applied to a SAR image with complex content.

  11. Deep kernel learning method for SAR image target recognition

    Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

    2017-10-01

    With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

  12. First Image Products from EcoSAR - Osa Peninsula, Costa Rica

    Osmanoglu, Batuhan; Lee, SeungKuk; Rincon, Rafael; Fatuyinbo, Lola; Bollian, Tobias; Ranson, Jon

    2016-01-01

    Designed especially for forest ecosystem studies, EcoSAR employs state-of-the-art digital beamforming technology to generate wide-swath, high-resolution imagery. EcoSARs dual antenna single-pass imaging capability eliminates temporal decorrelation from polarimetric and interferometric analysis, increasing the signal strength and simplifying models used to invert forest structure parameters. Antennae are physically separated by 25 meters providing single pass interferometry. In this mode the radar is most sensitive to topography. With 32 active transmit and receive channels, EcoSARs digital beamforming is an order of magnitude more versatile than the digital beamforming employed on the upcoming NISAR mission. EcoSARs long wavelength (P-band, 435 MHz, 69 cm) measurements can be used to simulate data products for ESAs future BIOMASS mission, allowing scientists to develop algorithms before the launch of the satellite. EcoSAR can also be deployed to collect much needed data where BIOMASS satellite wont be allowed to collect data (North America, Europe and Arctic), filling in the gaps to keep a watchful eye on the global carbon cycle. EcoSAR can play a vital role in monitoring, reporting and verification schemes of internationals programs such as UN-REDD (United Nations Reducing Emissions from Deforestation and Degradation) benefiting global society. EcoSAR was developed and flown with support from NASA Earth Sciences Technology Offices Instrument Incubator Program.

  13. Azimuth Ambiguities Removal in Littoral Zones Based on Multi-Temporal SAR Images

    Xiangguang Leng

    2017-08-01

    Full Text Available Synthetic aperture radar (SAR is one of the most important techniques for ocean monitoring. Azimuth ambiguities are a real problem in SAR images today, which can cause performance degradation in SAR ocean applications. In particular, littoral zones can be strongly affected by land-based sources, whereas they are usually regions of interest (ROI. Given the presence of complexity and diversity in littoral zones, azimuth ambiguities removal is a tough problem. As SAR sensors can have a repeat cycle, multi-temporal SAR images provide new insight into this problem. A method for azimuth ambiguities removal in littoral zones based on multi-temporal SAR images is proposed in this paper. The proposed processing chain includes co-registration, local correlation, binarization, masking, and restoration steps. It is designed to remove azimuth ambiguities caused by fixed land-based sources. The idea underlying the proposed method is that sea surface is dynamic, whereas azimuth ambiguities caused by land-based sources are constant. Thus, the temporal consistence of azimuth ambiguities is higher than sea clutter. It opens up the possibilities to use multi-temporal SAR data to remove azimuth ambiguities. The design of the method and the experimental procedure are based on images from the Sentinel data hub of Europe Space Agency (ESA. Both Interferometric Wide Swath (IW and Stripmap (SM mode images are taken into account to validate the proposed method. This paper also presents two RGB composition methods for better azimuth ambiguities visualization. Experimental results show that the proposed method can remove azimuth ambiguities in littoral zones effectively.

  14. STUDY ON THE CLASSIFICATION OF GAOFEN-3 POLARIMETRIC SAR IMAGES USING DEEP NEURAL NETWORK

    J. Zhang

    2018-04-01

    Full Text Available Polarimetric Synthetic Aperture Radar(POLSAR) imaging principle determines that the image quality will be affected by speckle noise. So the recognition accuracy of traditional image classification methods will be reduced by the effect of this interference. Since the date of submission, Deep Convolutional Neural Network impacts on the traditional image processing methods and brings the field of computer vision to a new stage with the advantages of a strong ability to learn deep features and excellent ability to fit large datasets. Based on the basic characteristics of polarimetric SAR images, the paper studied the types of the surface cover by using the method of Deep Learning. We used the fully polarimetric SAR features of different scales to fuse RGB images to the GoogLeNet model based on convolution neural network Iterative training, and then use the trained model to test the classification of data validation.First of all, referring to the optical image, we mark the surface coverage type of GF-3 POLSAR image with 8m resolution, and then collect the samples according to different categories. To meet the GoogLeNet model requirements of 256 × 256 pixel image input and taking into account the lack of full-resolution SAR resolution, the original image should be pre-processed in the process of resampling. In this paper, POLSAR image slice samples of different scales with sampling intervals of 2 m and 1 m to be trained separately and validated by the verification dataset. Among them, the training accuracy of GoogLeNet model trained with resampled 2-m polarimetric SAR image is 94.89 %, and that of the trained SAR image with resampled 1 m is 92.65 %.

  15. Study on the Classification of GAOFEN-3 Polarimetric SAR Images Using Deep Neural Network

    Zhang, J.; Zhang, J.; Zhao, Z.

    2018-04-01

    Polarimetric Synthetic Aperture Radar (POLSAR) imaging principle determines that the image quality will be affected by speckle noise. So the recognition accuracy of traditional image classification methods will be reduced by the effect of this interference. Since the date of submission, Deep Convolutional Neural Network impacts on the traditional image processing methods and brings the field of computer vision to a new stage with the advantages of a strong ability to learn deep features and excellent ability to fit large datasets. Based on the basic characteristics of polarimetric SAR images, the paper studied the types of the surface cover by using the method of Deep Learning. We used the fully polarimetric SAR features of different scales to fuse RGB images to the GoogLeNet model based on convolution neural network Iterative training, and then use the trained model to test the classification of data validation.First of all, referring to the optical image, we mark the surface coverage type of GF-3 POLSAR image with 8m resolution, and then collect the samples according to different categories. To meet the GoogLeNet model requirements of 256 × 256 pixel image input and taking into account the lack of full-resolution SAR resolution, the original image should be pre-processed in the process of resampling. In this paper, POLSAR image slice samples of different scales with sampling intervals of 2 m and 1 m to be trained separately and validated by the verification dataset. Among them, the training accuracy of GoogLeNet model trained with resampled 2-m polarimetric SAR image is 94.89 %, and that of the trained SAR image with resampled 1 m is 92.65 %.

  16. Offshore Wind Resource Estimation in Mediterranean Area Using SAR Images

    Calaudi, Rosamaria; Arena, Felice; Badger, Merete

    Satellite observations of the ocean surface from Synthetic Aperture Radars (SAR) provide information about the spatial wind variability over large areas. This is of special interest in the Mediterranean, where spatial wind information is only provided by sparse buoys, often with long periods of m...

  17. Mechanisms of SAR Imaging of Shallow Water Topography of the Subei Bank

    Shuangshang Zhang

    2017-11-01

    Full Text Available In this study, the C-band radar backscatter features of the shallow water topography of Subei Bank in the Southern Yellow Sea are statistically investigated using 25 ENVISAT (Environmental Satellite ASAR (advanced synthetic aperture radar and ERS-2 (European Remote-Sensing Satellite-2 SAR images acquired between 2006 and 2010. Different bathymetric features are found on SAR imagery under different sea states. Under low to moderate wind speeds (3.1~6.3 m/s, the wide bright patterns with an average width of 6 km are shown and correspond to sea surface imprints of tidal channels formed by two adjacent sand ridges, while the sand ridges appear as narrower (only 1 km wide, fingerlike, quasi-linear features on SAR imagery in high winds (5.4~13.9 m/s. Two possible SAR imaging mechanisms of coastal bathymetry are proposed in the case where the flow is parallel to the major axes of tidal channels or sand ridges. When the surface Ekman current is opposite to the mean tidal flow, two vortexes will converge at the central line of the tidal channel in the upper layer and form a convergent zone over the sea surface. Thus, the tidal channels are shown as wide and bright stripes on SAR imagery. For the SAR imaging of sand ridges, all the SAR images were acquired at low tidal levels. In this case, the ocean surface waves are possibly broken up under strong winds when propagating from deep water to the shallower water, which leads to an increase of surface roughness over the sand ridges.

  18. The Generalized Gamma-DBN for High-Resolution SAR Image Classification

    Zhiqiang Zhao

    2018-06-01

    Full Text Available With the increase of resolution, effective characterization of synthetic aperture radar (SAR image becomes one of the most critical problems in many earth observation applications. Inspired by deep learning and probability mixture models, a generalized Gamma deep belief network (g Γ-DBN is proposed for SAR image statistical modeling and land-cover classification in this work. Specifically, a generalized Gamma-Bernoulli restricted Boltzmann machine (gΓB-RBM is proposed to capture high-order statistical characterizes from SAR images after introducing the generalized Gamma distribution. After stacking the g Γ B-RBM and several standard binary RBMs in a hierarchical manner, a gΓ-DBN is constructed to learn high-level representation of different SAR land-covers. Finally, a discriminative neural network is constructed by adding an additional predict layer for different land-covers over the constructed deep structure. Performance of the proposed approach is evaluated via several experiments on some high-resolution SAR image patch sets and two large-scale scenes which are captured by ALOS PALSAR-2 and COSMO-SkyMed satellites respectively.

  19. Millimeter wave radar system on a rotating platform for combined search and track functionality with SAR imaging

    Aulenbacher, Uwe; Rech, Klaus; Sedlmeier, Johannes; Pratisto, Hans; Wellig, Peter

    2014-10-01

    Ground based millimeter wave radar sensors offer the potential for a weather-independent automatic ground surveillance at day and night, e.g. for camp protection applications. The basic principle and the experimental verification of a radar system concept is described, which by means of an extreme off-axis positioning of the antenna(s) combines azimuthal mechanical beam steering with the formation of a circular-arc shaped synthetic aperture (SA). In automatic ground surveillance the function of search and detection of moving ground targets is performed by means of the conventional mechanical scan mode. The rotated antenna structure designed as a small array with two or more RX antenna elements with simultaneous receiver chains allows to instantaneous track multiple moving targets (monopulse principle). The simultaneously operated SAR mode yields areal images of the distribution of stationary scatterers. For ground surveillance application this SAR mode is best suited for identifying possible threats by means of change detection. The feasibility of this concept was tested by means of an experimental radar system comprising of a 94 GHz (W band) FM-CW module with 1 GHz bandwidth and two RX antennas with parallel receiver channels, placed off-axis at a rotating platform. SAR mode and search/track mode were tested during an outdoor measurement campaign. The scenery of two persons walking along a road and partially through forest served as test for the capability to track multiple moving targets. For SAR mode verification an image of the area composed of roads, grassland, woodland and several man-made objects was reconstructed from the measured data.

  20. Classification of agricultural fields using time series of dual polarimetry TerraSAR-X images

    S. Mirzaee

    2014-10-01

    Full Text Available Due to its special imaging characteristics, Synthetic Aperture Radar (SAR has become an important source of information for a variety of remote sensing applications dealing with environmental changes. SAR images contain information about both phase and intensity in different polarization modes, making them sensitive to geometrical structure and physical properties of the targets such as dielectric and plant water content. In this study we investigate multi temporal changes occurring to different crop types due to phenological changes using high-resolution TerraSAR-X imagers. The dataset includes 17 dual-polarimetry TSX data acquired from June 2012 to August 2013 in Lorestan province, Iran. Several features are extracted from polarized data and classified using support vector machine (SVM classifier. Training samples and different features employed in classification are also assessed in the study. Results show a satisfactory accuracy for classification which is about 0.91 in kappa coefficient.

  1. A Novel Sidelobe Reduction Algorithm Based on Two-Dimensional Sidelobe Correction Using D-SVA for Squint SAR Images

    Min Liu

    2018-03-01

    Full Text Available Sidelobe reduction is a very primary task for synthetic aperture radar (SAR images. Various methods have been proposed for broadside SAR, which can suppress the sidelobes effectively while maintaining high image resolution at the same time. Alternatively, squint SAR, especially highly squint SAR, has emerged as an important tool that provides more mobility and flexibility and has become a focus of recent research studies. One of the research challenges for squint SAR is how to resolve the severe range-azimuth coupling of echo signals. Unlike broadside SAR images, the range and azimuth sidelobes of the squint SAR images no longer locate on the principal axes with high probability. Thus the spatially variant apodization (SVA filters could hardly get all the sidelobe information, and hence the sidelobe reduction process is not optimal. In this paper, we present an improved algorithm called double spatially variant apodization (D-SVA for better sidelobe suppression. Satisfactory sidelobe reduction results are achieved with the proposed algorithm by comparing the squint SAR images to the broadside SAR images. Simulation results also demonstrate the reliability and efficiency of the proposed method.

  2. Time domain SAR raw data simulation using CST and image focusing of 3D objects

    Saeed, Adnan; Hellwich, Olaf

    2017-10-01

    This paper presents the use of a general purpose electromagnetic simulator, CST, to simulate realistic synthetic aperture radar (SAR) raw data of three-dimensional objects. Raw data is later focused in MATLAB using range-doppler algorithm. Within CST Microwave Studio a replica of TerraSAR-X chirp signal is incident upon a modeled Corner Reflector (CR) whose design and material properties are identical to that of the real one. Defining mesh and other appropriate settings reflected wave is measured at several distant points within a line parallel to the viewing direction. This is analogous to an array antenna and is synthesized to create a long aperture for SAR processing. The time domain solver in CST is based on the solution of differential form of Maxwells equations. Exported data from CST is arranged into a 2-d matrix of axis range and azimuth. Hilbert transform is applied to convert the real signal to complex data with phase information. Range compression, range cell migration correction (RCMC), and azimuth compression are applied in time domain to obtain the final SAR image. This simulation can provide valuable information to clarify which real world objects cause images suitable for high accuracy identification in the SAR images.

  3. The artificial object detection and current velocity measurement using SAR ocean surface images

    Alpatov, Boris; Strotov, Valery; Ershov, Maksim; Muraviev, Vadim; Feldman, Alexander; Smirnov, Sergey

    2017-10-01

    Due to the fact that water surface covers wide areas, remote sensing is the most appropriate way of getting information about ocean environment for vessel tracking, security purposes, ecological studies and others. Processing of synthetic aperture radar (SAR) images is extensively used for control and monitoring of the ocean surface. Image data can be acquired from Earth observation satellites, such as TerraSAR-X, ERS, and COSMO-SkyMed. Thus, SAR image processing can be used to solve many problems arising in this field of research. This paper discusses some of them including ship detection, oil pollution control and ocean currents mapping. Due to complexity of the problem several specialized algorithm are necessary to develop. The oil spill detection algorithm consists of the following main steps: image preprocessing, detection of dark areas, parameter extraction and classification. The ship detection algorithm consists of the following main steps: prescreening, land masking, image segmentation combined with parameter measurement, ship orientation estimation and object discrimination. The proposed approach to ocean currents mapping is based on Doppler's law. The results of computer modeling on real SAR images are presented. Based on these results it is concluded that the proposed approaches can be used in maritime applications.

  4. A comparative study on methods of improving SCR for ship detection in SAR image

    Lang, Haitao; Shi, Hongji; Tao, Yunhong; Ma, Li

    2017-10-01

    Knowledge about ship positions plays a critical role in a wide range of maritime applications. To improve the performance of ship detector in SAR image, an effective strategy is improving the signal-to-clutter ratio (SCR) before conducting detection. In this paper, we present a comparative study on methods of improving SCR, including power-law scaling (PLS), max-mean and max-median filter (MMF1 and MMF2), method of wavelet transform (TWT), traditional SPAN detector, reflection symmetric metric (RSM), scattering mechanism metric (SMM). The ability of SCR improvement to SAR image and ship detection performance associated with cell- averaging CFAR (CA-CFAR) of different methods are evaluated on two real SAR data.

  5. Ka-band InSAR Imaging and Analysis Based on IMU Data

    Shi Jun

    2014-02-01

    Full Text Available Compared with other bands, the millimeter wave Interferometric Synthetic Aperture Radar (InSAR has high accuracy and small size, which is a hot topic in InSAR research. On the other hand, shorter wavelength causes difficulties in 2D imaging and interferometric phase extraction. In this study, the imaging and phase performance of the streaming Back Projection (BP method combined with IMU data are analyzed and discussed on the basis of actual Ka-band InSAR data. It is found that because the wavelength of the Ka-band is short, it is more sensitive to the antenna phase-center history. To ensure the phase-preserving capacity, the IMU data must be used with accurate motion error compensation. Furthermore, during data processing, we verify the flat-earth-removing capacity of the BP algorithm that calculates and compensates the master and slave antenna phase centers individually.

  6. Improvement of the Accuracy of InSAR Image Co-Registration Based On Tie Points – A Review

    Xiaoli Ding

    2009-02-01

    Full Text Available Interferometric Synthetic Aperture Radar (InSAR is a new measurement technology, making use of the phase information contained in the Synthetic Aperture Radar (SAR images. InSAR has been recognized as a potential tool for the generation of digital elevation models (DEMs and the measurement of ground surface deformations. However, many critical factors affect the quality of InSAR data and limit its applications. One of the factors is InSAR data processing, which consists of image co-registration, interferogram generation, phase unwrapping and geocoding. The co-registration of InSAR images is the first step and dramatically influences the accuracy of InSAR products. In this paper, the principle and processing procedures of InSAR techniques are reviewed. One of important factors, tie points, to be considered in the improvement of the accuracy of InSAR image co-registration are emphatically reviewed, such as interval of tie points, extraction of feature points, window size for tie point matching and the measurement for the quality of an interferogram.

  7. Multichannel High Resolution Wide Swath SAR Imaging for Hypersonic Air Vehicle with Curved Trajectory

    Rui Zhou

    2018-01-01

    Full Text Available Synthetic aperture radar (SAR equipped on the hypersonic air vehicle in near space has many advantages over the conventional airborne SAR. However, its high-speed maneuvering characteristics with curved trajectory result in serious range migration, and exacerbate the contradiction between the high resolution and wide swath. To solve this problem, this paper establishes the imaging geometrical model matched with the flight trajectory of the hypersonic platform and the multichannel azimuth sampling model based on the displaced phase center antenna (DPCA technology. Furthermore, based on the multichannel signal reconstruction theory, a more efficient spectrum reconstruction model using discrete Fourier transform is proposed to obtain the azimuth uniform sampling data. Due to the high complexity of the slant range model, it is difficult to deduce the processing algorithm for SAR imaging. Thus, an approximate range model is derived based on the minimax criterion, and the optimal second-order approximate coefficients of cosine function are obtained using the two-population coevolutionary algorithm. On this basis, aiming at the problem that the traditional Omega-K algorithm cannot compensate the residual phase with the difficulty of Stolt mapping along the range frequency axis, this paper proposes an Exact Transfer Function (ETF algorithm for SAR imaging, and presents a method of range division to achieve wide swath imaging. Simulation results verify the effectiveness of the ETF imaging algorithm.

  8. Multichannel High Resolution Wide Swath SAR Imaging for Hypersonic Air Vehicle with Curved Trajectory.

    Zhou, Rui; Sun, Jinping; Hu, Yuxin; Qi, Yaolong

    2018-01-31

    Synthetic aperture radar (SAR) equipped on the hypersonic air vehicle in near space has many advantages over the conventional airborne SAR. However, its high-speed maneuvering characteristics with curved trajectory result in serious range migration, and exacerbate the contradiction between the high resolution and wide swath. To solve this problem, this paper establishes the imaging geometrical model matched with the flight trajectory of the hypersonic platform and the multichannel azimuth sampling model based on the displaced phase center antenna (DPCA) technology. Furthermore, based on the multichannel signal reconstruction theory, a more efficient spectrum reconstruction model using discrete Fourier transform is proposed to obtain the azimuth uniform sampling data. Due to the high complexity of the slant range model, it is difficult to deduce the processing algorithm for SAR imaging. Thus, an approximate range model is derived based on the minimax criterion, and the optimal second-order approximate coefficients of cosine function are obtained using the two-population coevolutionary algorithm. On this basis, aiming at the problem that the traditional Omega-K algorithm cannot compensate the residual phase with the difficulty of Stolt mapping along the range frequency axis, this paper proposes an Exact Transfer Function (ETF) algorithm for SAR imaging, and presents a method of range division to achieve wide swath imaging. Simulation results verify the effectiveness of the ETF imaging algorithm.

  9. Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN.

    Guo, Hao; Wu, Danni; An, Jubai

    2017-08-09

    Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features.

  10. Combining TerraSAR-X and Landsat Images for Emergency Response in Urban Environments

    Shiran Havivi

    2018-05-01

    Full Text Available Rapid damage mapping following a disaster event, especially in an urban environment, is critical to ensure that the emergency response in the affected area is rapid and efficient. This work presents a new method for mapping damage assessment in urban environments. Based on combining SAR and optical data, the method is applicable as support during initial emergency planning and rescue operations. The study focuses on the urban areas affected by the Tohoku earthquake and subsequent tsunami event in Japan that occurred on 11 March 2011. High-resolution TerraSAR-X (TSX images of before and after the event, and a Landsat 5 image before the event were acquired. The affected areas were analyzed with the SAR data using only one interferometric SAR (InSAR coherence map. To increase the damage mapping accuracy, the normalized difference vegetation index (NDVI was applied. The generated map, with a grid size of 50 m, provides a quantitative assessment of the nature and distribution of the damage. The damage mapping shows detailed information about the affected area, with high overall accuracy (89%, and high Kappa coefficient (82% and, as expected, it shows total destruction along the coastline compared to the inland region.

  11. Superresolution Imaging Using Resonant Multiples

    Guo, Bowen

    2017-12-22

    A resonant multiple is defined as a multiple reflection that revisits the same subsurface location along coincident reflection raypaths. We show that resonant first-order multiples can be migrated with either Kirchhoff or wave-equation migration methods to give images with approximately twice the spatial resolution compared to post-stack primary-reflection images. A moveout-correction stacking method is proposed to enhance the signal-to-noise ratios (SNRs) of the resonant multiples before superresolution migration. The effectiveness of this procedure is validated by synthetic and field data tests.

  12. Superresolution Imaging Using Resonant Multiples

    Guo, Bowen; Schuster, Gerard T.

    2017-01-01

    A resonant multiple is defined as a multiple reflection that revisits the same subsurface location along coincident reflection raypaths. We show that resonant first-order multiples can be migrated with either Kirchhoff or wave-equation migration methods to give images with approximately twice the spatial resolution compared to post-stack primary-reflection images. A moveout-correction stacking method is proposed to enhance the signal-to-noise ratios (SNRs) of the resonant multiples before superresolution migration. The effectiveness of this procedure is validated by synthetic and field data tests.

  13. Random Forests as a tool for estimating uncertainty at pixel-level in SAR image classification

    Loosvelt, Lien; Peters, Jan; Skriver, Henning

    2012-01-01

    , we introduce Random Forests for the probabilistic mapping of vegetation from high-dimensional remote sensing data and present a comprehensive methodology to assess and analyze classification uncertainty based on the local probabilities of class membership. We apply this method to SAR image data...

  14. SAR Image Simulation of Ship Targets Based on Multi-Path Scattering

    Guo, Y.; Wang, H.; Ma, H.; Li, K.; Xia, Z.; Hao, Y.; Guo, H.; Shi, H.; Liao, X.; Yue, H.

    2018-04-01

    Synthetic Aperture Radar (SAR) plays an important role in the classification and recognition of ship targets because of its all-weather working ability and fine resolution. In SAR images, besides the sea clutter, the influence of the sea surface on the radar echo is also known as the so-called multipath effect. These multipath effects will generate some extra "pseudo images", which may cause the distortion of the target image and affect the estimation of the characteristic parameters. In this paper,the multipath effect of rough sea surface and its influence on the estimation of ship characteristic parameters are studied. The imaging of the first and the secondary reflection of sea surface is presented . The artifacts not only overlap with the image of the target itself, but may also appear in the sea near the target area. It is difficult to distinguish them, and this artifact has an effect on the length and width of the ship.

  15. SAR and Infrared Image Fusion in Complex Contourlet Domain Based on Joint Sparse Representation

    Wu Yiquan

    2017-08-01

    Full Text Available To investigate the problems of the large grayscale difference between infrared and Synthetic Aperture Radar (SAR images and their fusion image not being fit for human visual perception, we propose a fusion method for SAR and infrared images in the complex contourlet domain based on joint sparse representation. First, we perform complex contourlet decomposition of the infrared and SAR images. Then, we employ the KSingular Value Decomposition (K-SVD method to obtain an over-complete dictionary of the low-frequency components of the two source images. Using a joint sparse representation model, we then generate a joint dictionary. We obtain the sparse representation coefficients of the low-frequency components of the source images in the joint dictionary by the Orthogonal Matching Pursuit (OMP method and select them using the selection maximization strategy. We then reconstruct these components to obtain the fused low-frequency components and fuse the high-frequency components using two criteria——the coefficient of visual sensitivity and the degree of energy matching. Finally, we obtain the fusion image by the inverse complex contourlet transform. Compared with the three classical fusion methods and recently presented fusion methods, e.g., that based on the Non-Subsampled Contourlet Transform (NSCT and another based on sparse representation, the method we propose in this paper can effectively highlight the salient features of the two source images and inherit their information to the greatest extent.

  16. Urban-area extraction from polarimetric SAR image using combination of target decomposition and orientation angle

    Zou, Bin; Lu, Da; Wu, Zhilu; Qiao, Zhijun G.

    2016-05-01

    The results of model-based target decomposition are the main features used to discriminate urban and non-urban area in polarimetric synthetic aperture radar (PolSAR) application. Traditional urban-area extraction methods based on modelbased target decomposition usually misclassified ground-trunk structure as urban-area or misclassified rotated urbanarea as forest. This paper introduces another feature named orientation angle to improve urban-area extraction scheme for the accurate mapping in urban by PolSAR image. The proposed method takes randomness of orientation angle into account for restriction of urban area first and, subsequently, implements rotation angle to improve results that oriented urban areas are recognized as double-bounce objects from volume scattering. ESAR L-band PolSAR data of the Oberpfaffenhofen Test Site Area was used to validate the proposed algorithm.

  17. Target discrimination method for SAR images based on semisupervised co-training

    Wang, Yan; Du, Lan; Dai, Hui

    2018-01-01

    Synthetic aperture radar (SAR) target discrimination is usually performed in a supervised manner. However, supervised methods for SAR target discrimination may need lots of labeled training samples, whose acquirement is costly, time consuming, and sometimes impossible. This paper proposes an SAR target discrimination method based on semisupervised co-training, which utilizes a limited number of labeled samples and an abundant number of unlabeled samples. First, Lincoln features, widely used in SAR target discrimination, are extracted from the training samples and partitioned into two sets according to their physical meanings. Second, two support vector machine classifiers are iteratively co-trained with the extracted two feature sets based on the co-training algorithm. Finally, the trained classifiers are exploited to classify the test data. The experimental results on real SAR images data not only validate the effectiveness of the proposed method compared with the traditional supervised methods, but also demonstrate the superiority of co-training over self-training, which only uses one feature set.

  18. Multiple Segmentation of Image Stacks

    Smets, Jonathan; Jaeger, Manfred

    2014-01-01

    We propose a method for the simultaneous construction of multiple image segmentations by combining a recently proposed “convolution of mixtures of Gaussians” model with a multi-layer hidden Markov random field structure. The resulting method constructs for a single image several, alternative...

  19. Discernibility of Burial Mounds in High-Resolution X-Band SAR Images for Archaeological Prospections in the Altai Mountains

    Timo Balz

    2016-09-01

    Full Text Available The Altai Mountains are a heritage-rich archaeological landscape with monuments in almost every valley. Modern nation state borders dissect the region and limit archaeological landscape analysis to intra-national areas of interest. Remote sensing can help to overcome these limitations. Due to its high precision, Synthetic Aperture Radar (SAR data can be a very useful tool for supporting archaeological prospections, but compared to optical imagery, the detectability of sites of archaeological interest is limited. We analyzed the limitations of SAR using TerraSAR-X images in different modes. Based on ground truth, the discernibility of burial mounds was analyzed in different SAR acquisition modes. We show that very-high-resolution TerraSAR-X staring spotlight images are very well suited for the task, with >75% of the larger mounds being discernible, while in images with a lower spatial resolution only a few large sites can be detected, at rates below 50%.

  20. Fast iterative censoring CFAR algorithm for ship detection from SAR images

    Gu, Dandan; Yue, Hui; Zhang, Yuan; Gao, Pengcheng

    2017-11-01

    Ship detection is one of the essential techniques for ship recognition from synthetic aperture radar (SAR) images. This paper presents a fast iterative detection procedure to eliminate the influence of target returns on the estimation of local sea clutter distributions for constant false alarm rate (CFAR) detectors. A fast block detector is first employed to extract potential target sub-images; and then, an iterative censoring CFAR algorithm is used to detect ship candidates from each target blocks adaptively and efficiently, where parallel detection is available, and statistical parameters of G0 distribution fitting local sea clutter well can be quickly estimated based on an integral image operator. Experimental results of TerraSAR-X images demonstrate the effectiveness of the proposed technique.

  1. Extraction of lead and ridge characteristics from SAR images of sea ice

    Vesecky, John F.; Smith, Martha P.; Samadani, Ramin

    1990-01-01

    Image-processing techniques for extracting the characteristics of lead and pressure ridge features in SAR images of sea ice are reported. The methods are applied to a SAR image of the Beaufort Sea collected from the Seasat satellite on October 3, 1978. Estimates of lead and ridge statistics are made, e.g., lead and ridge density (number of lead or ridge pixels per unit area of image) and the distribution of lead area and orientation as well as ridge length and orientation. The information derived is useful in both ice science and polar operations for such applications as albedo and heat and momentum transfer estimates, as well as ship routing and offshore engineering.

  2. Feature Matching for SAR and Optical Images Based on Gaussian-Gamma-shaped Edge Strength Map

    CHEN Min

    2016-03-01

    Full Text Available A matching method for SAR and optical images, robust to pixel noise and nonlinear grayscale differences, is presented. Firstly, a rough correction to eliminate rotation and scale change between images is performed. Secondly, features robust to speckle noise of SAR image are detected by improving the original phase congruency based method. Then, feature descriptors are constructed on the Gaussian-Gamma-shaped edge strength map according to the histogram of oriented gradient pattern. Finally, descriptor similarity and geometrical relationship are combined to constrain the matching processing.The experimental results demonstrate that the proposed method provides significant improvement in correct matches number and image registration accuracy compared with other traditional methods.

  3. Change detection in a time series of polarimetric SAR images

    Skriver, Henning; Nielsen, Allan Aasbjerg; Conradsen, Knut

    A test statistic for the equality of two or several variance-covariance matrices following the real (as opposed to the complex) Wishart distribution with an associated probability of finding a smaller value of the test statistic is described in the literature [1]. In 2003 we introduced a test...... statistic for the equality of two variance-covariance matrices following the complex Wishart distribution with an associated probability measure [2]. In that paper we also demonstrated the use of the test statistic to change detection over time in both fully polarimetric and azimuthal symmetric SAR data...... positives (postulating a change when there actually is none) and/or false negatives (missing an actual change). Therefore we need to test for equality for all time points simultaneously. In this paper we demonstrate a new test statistic for the equality of several variance-covariance matrices from the real...

  4. Neural network-based feature point descriptors for registration of optical and SAR images

    Abulkhanov, Dmitry; Konovalenko, Ivan; Nikolaev, Dmitry; Savchik, Alexey; Shvets, Evgeny; Sidorchuk, Dmitry

    2018-04-01

    Registration of images of different nature is an important technique used in image fusion, change detection, efficient information representation and other problems of computer vision. Solving this task using feature-based approaches is usually more complex than registration of several optical images because traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we consider the problem of registration of SAR and optical images. We train neural network to build feature point descriptors and use RANSAC algorithm to align found matches. Experimental results are presented that confirm the method's effectiveness.

  5. Probability Density Components Analysis: A New Approach to Treatment and Classification of SAR Images

    Osmar Abílio de Carvalho Júnior

    2014-04-01

    Full Text Available Speckle noise (salt and pepper is inherent to synthetic aperture radar (SAR, which causes a usual noise-like granular aspect and complicates the image classification. In SAR image analysis, the spatial information might be a particular benefit for denoising and mapping classes characterized by a statistical distribution of the pixel intensities from a complex and heterogeneous spectral response. This paper proposes the Probability Density Components Analysis (PDCA, a new alternative that combines filtering and frequency histogram to improve the classification procedure for the single-channel synthetic aperture radar (SAR images. This method was tested on L-band SAR data from the Advanced Land Observation System (ALOS Phased-Array Synthetic-Aperture Radar (PALSAR sensor. The study area is localized in the Brazilian Amazon rainforest, northern Rondônia State (municipality of Candeias do Jamari, containing forest and land use patterns. The proposed algorithm uses a moving window over the image, estimating the probability density curve in different image components. Therefore, a single input image generates an output with multi-components. Initially the multi-components should be treated by noise-reduction methods, such as maximum noise fraction (MNF or noise-adjusted principal components (NAPCs. Both methods enable reducing noise as well as the ordering of multi-component data in terms of the image quality. In this paper, the NAPC applied to multi-components provided large reductions in the noise levels, and the color composites considering the first NAPC enhance the classification of different surface features. In the spectral classification, the Spectral Correlation Mapper and Minimum Distance were used. The results obtained presented as similar to the visual interpretation of optical images from TM-Landsat and Google Maps.

  6. Exploiting Deep Matching and SAR Data for the Geo-Localization Accuracy Improvement of Optical Satellite Images

    Nina Merkle

    2017-06-01

    Full Text Available Improving the geo-localization of optical satellite images is an important pre-processing step for many remote sensing tasks like monitoring by image time series or scene analysis after sudden events. These tasks require geo-referenced and precisely co-registered multi-sensor data. Images captured by the high resolution synthetic aperture radar (SAR satellite TerraSAR-X exhibit an absolute geo-location accuracy within a few decimeters. These images represent therefore a reliable source to improve the geo-location accuracy of optical images, which is in the order of tens of meters. In this paper, a deep learning-based approach for the geo-localization accuracy improvement of optical satellite images through SAR reference data is investigated. Image registration between SAR and optical images requires few, but accurate and reliable matching points. These are derived from a Siamese neural network. The network is trained using TerraSAR-X and PRISM image pairs covering greater urban areas spread over Europe, in order to learn the two-dimensional spatial shifts between optical and SAR image patches. Results confirm that accurate and reliable matching points can be generated with higher matching accuracy and precision with respect to state-of-the-art approaches.

  7. A neural network detection model of spilled oil based on the texture analysis of SAR image

    An, Jubai; Zhu, Lisong

    2006-01-01

    A Radial Basis Function Neural Network (RBFNN) Model is investigated for the detection of spilled oil based on the texture analysis of SAR imagery. In this paper, to take the advantage of the abundant texture information of SAR imagery, the texture features are extracted by both wavelet transform and the Gray Level Co-occurrence matrix. The RBFNN Model is fed with a vector of these texture features. The RBFNN Model is trained and tested by the sample data set of the feature vectors. Finally, a SAR image is classified by this model. The classification results of a spilled oil SAR image show that the classification accuracy for oil spill is 86.2 by the RBFNN Model using both wavelet texture and gray texture, while the classification accuracy for oil spill is 78.0 by same RBFNN Model using only wavelet texture as the input of this RBFNN model. The model using both wavelet transform and the Gray Level Co-occurrence matrix is more effective than that only using wavelet texture. Furthermore, it keeps the complicated proximity and has a good performance of classification.

  8. Synthetic aperture integration (SAI) algorithm for SAR imaging

    Chambers, David H; Mast, Jeffrey E; Paglieroni, David W; Beer, N. Reginald

    2013-07-09

    A method and system for detecting the presence of subsurface objects within a medium is provided. In some embodiments, the imaging and detection system operates in a multistatic mode to collect radar return signals generated by an array of transceiver antenna pairs that is positioned across the surface and that travels down the surface. The imaging and detection system pre-processes the return signal to suppress certain undesirable effects. The imaging and detection system then generates synthetic aperture radar images from real aperture radar images generated from the pre-processed return signal. The imaging and detection system then post-processes the synthetic aperture radar images to improve detection of subsurface objects. The imaging and detection system identifies peaks in the energy levels of the post-processed image frame, which indicates the presence of a subsurface object.

  9. MREG V1.1 : a multi-scale image registration algorithm for SAR applications.

    Eichel, Paul H.

    2013-08-01

    MREG V1.1 is the sixth generation SAR image registration algorithm developed by the Signal Processing&Technology Department for Synthetic Aperture Radar applications. Like its predecessor algorithm REGI, it employs a powerful iterative multi-scale paradigm to achieve the competing goals of sub-pixel registration accuracy and the ability to handle large initial offsets. Since it is not model based, it allows for high fidelity tracking of spatially varying terrain-induced misregistration. Since it does not rely on image domain phase, it is equally adept at coherent and noncoherent image registration. This document provides a brief history of the registration processors developed by Dept. 5962 leading up to MREG V1.1, a full description of the signal processing steps involved in the algorithm, and a user's manual with application specific recommendations for CCD, TwoColor MultiView, and SAR stereoscopy.

  10. Change detection in polarimetric SAR images using complex Wishart distributed matrices

    Conradsen, Knut; Nielsen, Allan Aasbjerg; Skriver, Henning

    In surveillance it is important to be able to detect natural or man-made changes e.g. based on sequences of satellite or air borne images of the same area taken at different times. The mapping capability of synthetic aperture radar (SAR) is independent of e.g. cloud cover, and thus this technology...... scattering matrix, and after suitable preprocessing the outcome at each picture element (pixel) may be represented as a 3 by 3 Hermitian matrix following a complex Wishart distribution. One approach to solving the change detection problem based on SAR images is therefore to apply suitable statistical tests...... in the complex Wishart distribution. We propose a set-up for a systematic solution to the (practical) problems using the likelihood ratio test statistics. We show some examples based on a time series of images with 1024 by 1024 pixels....

  11. Potential of TCPInSAR in Monitoring Linear Infrastructure with a Small Dataset of SAR Images: Application of the Donghai Bridge, China

    Lei Zhang

    2018-03-01

    Full Text Available Reliably monitoring deformation associated with linear infrastructures, such as long-span bridges, is vitally important to assess their structural health. In this paper, we attempt to employ satellite interferometric synthetic aperture radar (InSAR to map the deformation of Donghai Bridge over a half of an annual cycle. The bridge, as the fourth longest cross-sea bridge in the world, located in the north of Hangzhou Bay, East China Sea where the featureless sea surface largely occupied the radar image raises challenges to accurately co-register the coherent points along the bridge. To tackle the issues due to co-registration and the limited number of synthetic aperture radar (SAR images, we adopt the termed temporarily-coherent point (TCP InSAR (TCPInSAR technique to process the radar images. TCPs that are not necessarily coherent during the whole observation period can be identified within every two SAR acquisitions during the co-registration procedure based on the statistics of azimuth and range offsets. In the process, co-registration is performed only using the offsets of these TCPs, leading to improved interferometric phases and the local Delaunay triangulation is used to construct point pairs to reduce the atmospheric artifacts along the bridge. With the TCPInSAR method the deformation rate along the bridge is estimated with no need of phase unwrapping. The achieved result reveals that the Donghai Bridge suffered a line-of-sight (LOS deformation rate up to −2.3 cm/year from January 2009 to July 2009 at the cable-stayed part, which is likely due to the thermal expansion of cables.

  12. Multi-linear sparse reconstruction for SAR imaging based on higher-order SVD

    Gao, Yu-Fei; Gui, Guan; Cong, Xun-Chao; Yang, Yue; Zou, Yan-Bin; Wan, Qun

    2017-12-01

    This paper focuses on the spotlight synthetic aperture radar (SAR) imaging for point scattering targets based on tensor modeling. In a real-world scenario, scatterers usually distribute in the block sparse pattern. Such a distribution feature has been scarcely utilized by the previous studies of SAR imaging. Our work takes advantage of this structure property of the target scene, constructing a multi-linear sparse reconstruction algorithm for SAR imaging. The multi-linear block sparsity is introduced into higher-order singular value decomposition (SVD) with a dictionary constructing procedure by this research. The simulation experiments for ideal point targets show the robustness of the proposed algorithm to the noise and sidelobe disturbance which always influence the imaging quality of the conventional methods. The computational resources requirement is further investigated in this paper. As a consequence of the algorithm complexity analysis, the present method possesses the superiority on resource consumption compared with the classic matching pursuit method. The imaging implementations for practical measured data also demonstrate the effectiveness of the algorithm developed in this paper.

  13. Doppler Spectrum-Based NRCS Estimation Method for Low-Scattering Areas in Ocean SAR Images

    Hui Meng

    2017-02-01

    Full Text Available The image intensities of low-backscattering areas in synthetic aperture radar (SAR images are often seriously contaminated by the system noise floor and azimuthal ambiguity signal from adjacent high-backscattering areas. Hence, the image intensity of low-backscattering areas does not correctly reflect the backscattering intensity, which causes confusion in subsequent image processing or interpretation. In this paper, a method is proposed to estimate the normalized radar cross-section (NRCS of low-backscattering area by utilizing the differences between noise, azimuthal ambiguity, and signal in the Doppler frequency domain of single-look SAR images; the aim is to eliminate the effect of system noise and azimuthal ambiguity. Analysis shows that, for a spaceborne SAR with a noise equivalent sigma zero (NESZ of −25 dB and a single-look pixel of 8 m × 5 m, the NRCS-estimation precision of this method can reach −38 dB at a resolution of 96 m × 100 m. Three examples are given to validate the advantages of this method in estimating the low NRCS and the filtering of the azimuthal ambiguity.

  14. Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model

    Li, X. L.; Zhao, Q. H.; Li, Y.

    2017-09-01

    Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.

  15. RESEARCH ON COORDINATE TRANSFORMATION METHOD OF GB-SAR IMAGE SUPPORTED BY 3D LASER SCANNING TECHNOLOGY

    P. Wang

    2018-04-01

    Full Text Available In the image plane of GB-SAR, identification of deformation distribution is usually carried out by artificial interpretation. This method requires analysts to have adequate experience of radar imaging and target recognition, otherwise it can easily cause false recognition of deformation target or region. Therefore, it is very meaningful to connect two-dimensional (2D plane coordinate system with the common three-dimensional (3D terrain coordinate system. To improve the global accuracy and reliability of the transformation from 2D coordinates of GB-SAR images to local 3D coordinates, and overcome the limitation of traditional similarity transformation parameter estimation method, 3D laser scanning data is used to assist the transformation of GB-SAR image coordinates. A straight line fitting method for calculating horizontal angle was proposed in this paper. After projection into a consistent imaging plane, we can calculate horizontal rotation angle by using the linear characteristics of the structure in radar image and the 3D coordinate system. Aided by external elevation information by 3D laser scanning technology, we completed the matching of point clouds and pixels on the projection plane according to the geometric projection principle of GB-SAR imaging realizing the transformation calculation of GB-SAR image coordinates to local 3D coordinates. Finally, the effectiveness of the method is verified by the GB-SAR deformation monitoring experiment on the high slope of Geheyan dam.

  16. Research on Coordinate Transformation Method of Gb-Sar Image Supported by 3d Laser Scanning Technology

    Wang, P.; Xing, C.

    2018-04-01

    In the image plane of GB-SAR, identification of deformation distribution is usually carried out by artificial interpretation. This method requires analysts to have adequate experience of radar imaging and target recognition, otherwise it can easily cause false recognition of deformation target or region. Therefore, it is very meaningful to connect two-dimensional (2D) plane coordinate system with the common three-dimensional (3D) terrain coordinate system. To improve the global accuracy and reliability of the transformation from 2D coordinates of GB-SAR images to local 3D coordinates, and overcome the limitation of traditional similarity transformation parameter estimation method, 3D laser scanning data is used to assist the transformation of GB-SAR image coordinates. A straight line fitting method for calculating horizontal angle was proposed in this paper. After projection into a consistent imaging plane, we can calculate horizontal rotation angle by using the linear characteristics of the structure in radar image and the 3D coordinate system. Aided by external elevation information by 3D laser scanning technology, we completed the matching of point clouds and pixels on the projection plane according to the geometric projection principle of GB-SAR imaging realizing the transformation calculation of GB-SAR image coordinates to local 3D coordinates. Finally, the effectiveness of the method is verified by the GB-SAR deformation monitoring experiment on the high slope of Geheyan dam.

  17. Modulation of Tidal Channel Signatures on SAR Images Over Gyeonggi Bay in Relation to Environmental Factors

    Tae-Sung Kim

    2018-04-01

    Full Text Available In this study, variations of radar backscatter features of the tidal channel in Gyeonggi Bay in the Eastern Yellow Sea were investigated using spaceborne synthetic aperture radar (SAR images. Consistent quasi-linear bright features appeared on the SAR images. Examining the detailed local bathymetry chart, we found that the features were co-located with the major axis of the tidal channel in the region. It was also shown that modulation of the radar backscatter features changed according to the environmental conditions at the time of imaging. For the statistical analysis, the bathymetric features over the tidal channel were extracted by an objective method. In terms of shape, the extracted features had higher variability in width than in length. The analysis of the variation in intensity with the coinciding bathymetric distribution confirmed that the quasi-linear bright features on the SAR images are fundamentally imprinted due to the surface current convergence and divergence caused by the bathymetry-induced tidal current variation. Furthermore, the contribution of environmental factors to the intensity modulation was quantitatively analyzed. A comparison of the variation in normalized radar cross section (NRCS with tidal current showed a positive correlation only with the perpendicular component of tidal current (r= 0.47. This implies that the modulation in intensity of the tidal channel signatures is mainly affected by the interaction with cross-current flow. On the other hand, the modulation of the NRCS over the tidal channel tended to be degraded as wind speed increased (r= −0.65. Considering the environmental circumstances in the study area, it can be inferred that the imaging capability of SAR for the detection of tidal channel signatures mainly relies on wind speed.

  18. Integrated Shoreline Extraction Approach with Use of Rasat MS and SENTINEL-1A SAR Images

    Demir, N.; Oy, S.; Erdem, F.; Şeker, D. Z.; Bayram, B.

    2017-09-01

    Shorelines are complex ecosystems and highly important socio-economic environments. They may change rapidly due to both natural and human-induced effects. Determination of movements along the shoreline and monitoring of the changes are essential for coastline management, modeling of sediment transportation and decision support systems. Remote sensing provides an opportunity to obtain rapid, up-to-date and reliable information for monitoring of shoreline. In this study, approximately 120 km of Antalya-Kemer shoreline which is under the threat of erosion, deposition, increasing of inhabitants and urbanization and touristic hotels, has been selected as the study area. In the study, RASAT pansharpened and SENTINEL-1A SAR images have been used to implement proposed shoreline extraction methods. The main motivation of this study is to combine the land/water body segmentation results of both RASAT MS and SENTINEL-1A SAR images to improve the quality of the results. The initial land/water body segmentation has been obtained using RASAT image by means of Random Forest classification method. This result has been used as training data set to define fuzzy parameters for shoreline extraction from SENTINEL-1A SAR image. Obtained results have been compared with the manually digitized shoreline. The accuracy assessment has been performed by calculating perpendicular distances between reference data and extracted shoreline by proposed method. As a result, the mean difference has been calculated around 1 pixel.

  19. Two-dimensional Fast ESPRIT Algorithm for Linear Array SAR Imaging

    Zhao Yi-chao

    2015-10-01

    Full Text Available The linear array Synthetic Aperture Radar (SAR system is a popular research tool, because it can realize three-dimensional imaging. However, owning to limitations of the aircraft platform and actual conditions, resolution improvement is difficult in cross-track and along-track directions. In this study, a twodimensional fast Estimation of Signal Parameters by Rotational Invariance Technique (ESPRIT algorithm for linear array SAR imaging is proposed to overcome these limitations. This approach combines the Gerschgorin disks method and the ESPRIT algorithm to estimate the positions of scatterers in cross and along-rack directions. Moreover, the reflectivity of scatterers is obtained by a modified pairing method based on “region growing”, replacing the least-squares method. The simulation results demonstrate the applicability of the algorithm with high resolution, quick calculation, and good real-time response.

  20. SAR Imaging of Ground Moving Targets with Non-ideal Motion Error Compensation(in English

    Zhou Hui

    2015-06-01

    Full Text Available Conventional ground moving target imaging algorithms mainly focus on the range cell migration correction and the motion parameter estimation of the moving target. However, in real Synthetic Aperture Radar (SAR data processing, non-ideal motion error compensation is also a critical process, which focuses and has serious impacts on the imaging quality of moving targets. Non-ideal motion error can not be compensated by either the stationary SAR motion error compensation algorithms or the autofocus techniques. In this paper, two sorts of non-ideal motion errors that affect the Doppler centroid of the moving target is analyzed, and a novel non-ideal motion error compensation algorithm is proposed based on the Inertial Navigation System (INS data and the range walk trajectory. Simulated and real data processing results are provided to demonstrate the effectiveness of the proposed algorithm.

  1. Discrimination of Different Water Layers with TerraSAR X Images in "La Albufera de Valencia"

    García Fernández, M. A.; Miguelsanz Muñoz, P.

    2009-04-01

    To analyze the capabilities of TerraSAR X Strip Map images in order to discriminate different water layers in the "Parque de la Albufera de Valencia", Spain, a test project was carried out. This place is a rice crop area under European and National Agro environmental regulation which obliges to preserve the habitat and to keep the rice plots flooded out of crop season, from October to January

  2. Mapping Winter Wheat with Multi-Temporal SAR and Optical Images in an Urban Agricultural Region.

    Zhou, Tao; Pan, Jianjun; Zhang, Peiyu; Wei, Shanbao; Han, Tao

    2017-05-25

    Winter wheat is the second largest food crop in China. It is important to obtain reliable winter wheat acreage to guarantee the food security for the most populous country in the world. This paper focuses on assessing the feasibility of in-season winter wheat mapping and investigating potential classification improvement by using SAR (Synthetic Aperture Radar) images, optical images, and the integration of both types of data in urban agricultural regions with complex planting structures in Southern China. Both SAR (Sentinel-1A) and optical (Landsat-8) data were acquired, and classification using different combinations of Sentinel-1A-derived information and optical images was performed using a support vector machine (SVM) and a random forest (RF) method. The interference coherence and texture images were obtained and used to assess the effect of adding them to the backscatter intensity images on the classification accuracy. The results showed that the use of four Sentinel-1A images acquired before the jointing period of winter wheat can provide satisfactory winter wheat classification accuracy, with an F1 measure of 87.89%. The combination of SAR and optical images for winter wheat mapping achieved the best F1 measure-up to 98.06%. The SVM was superior to RF in terms of the overall accuracy and the kappa coefficient, and was faster than RF, while the RF classifier was slightly better than SVM in terms of the F1 measure. In addition, the classification accuracy can be effectively improved by adding the texture and coherence images to the backscatter intensity data.

  3. Saharasar: An Interactive SAR Image Database for Desert Mapping

    Lopez, S.; Paillou, Ph.

    2017-06-01

    We present a dedicated tool for accessing radar images acquired by the ALOS/PALSAR mission over Sahara and Arabia. We developed a dedicated web site, using the Mapserver web mapping server and the Cesium javascript library.

  4. Flood extent and water level estimation from SAR using data-model integration

    Ajadi, O. A.; Meyer, F. J.

    2017-12-01

    Synthetic Aperture Radar (SAR) images have long been recognized as a valuable data source for flood mapping. Compared to other sources, SAR's weather and illumination independence and large area coverage at high spatial resolution supports reliable, frequent, and detailed observations of developing flood events. Accordingly, SAR has the potential to greatly aid in the near real-time monitoring of natural hazards, such as flood detection, if combined with automated image processing. This research works towards increasing the reliability and temporal sampling of SAR-derived flood hazard information by integrating information from multiple SAR sensors and SAR modalities (images and Interferometric SAR (InSAR) coherence) and by combining SAR-derived change detection information with hydrologic and hydraulic flood forecast models. First, the combination of multi-temporal SAR intensity images and coherence information for generating flood extent maps is introduced. The application of least-squares estimation integrates flood information from multiple SAR sensors, thus increasing the temporal sampling. SAR-based flood extent information will be combined with a Digital Elevation Model (DEM) to reduce false alarms and to estimate water depth and flood volume. The SAR-based flood extent map is assimilated into the Hydrologic Engineering Center River Analysis System (Hec-RAS) model to aid in hydraulic model calibration. The developed technology is improving the accuracy of flood information by exploiting information from data and models. It also provides enhanced flood information to decision-makers supporting the response to flood extent and improving emergency relief efforts.

  5. LARGE OIL SPILL CLASSIFICATION USING SAR IMAGES BASED ON SPATIAL HISTOGRAM

    I. Schvartzman

    2016-06-01

    Full Text Available Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010. The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA data.

  6. Large Oil Spill Classification Using SAR Images Based on Spatial Histogram

    Schvartzman, I.; Havivi, S.; Maman, S.; Rotman, S. R.; Blumberg, D. G.

    2016-06-01

    Among the different types of marine pollution, oil spill is a major threat to the sea ecosystems. Remote sensing is used in oil spill response. Synthetic Aperture Radar (SAR) is an active microwave sensor that operates under all weather conditions and provides information about the surface roughness and covers large areas at a high spatial resolution. SAR is widely used to identify and track pollutants in the sea, which may be due to a secondary effect of a large natural disaster or by a man-made one . The detection of oil spill in SAR imagery relies on the decrease of the backscattering from the sea surface, due to the increased viscosity, resulting in a dark formation that contrasts with the brightness of the surrounding area. Most of the use of SAR images for oil spill detection is done by visual interpretation. Trained interpreters scan the image, and mark areas of low backscatter and where shape is a-symmetrical. It is very difficult to apply this method for a wide area. In contrast to visual interpretation, automatic detection algorithms were suggested and are mainly based on scanning dark formations, extracting features, and applying big data analysis. We propose a new algorithm that applies a nonlinear spatial filter that detects dark formations and is not susceptible to noises, such as internal or speckle. The advantages of this algorithm are both in run time and the results retrieved. The algorithm was tested in genesimulations as well as on COSMO-SkyMed images, detecting the Deep Horizon oil spill in the Gulf of Mexico (occurred on 20/4/2010). The simulation results show that even in a noisy environment, oil spill is detected. Applying the algorithm to the Deep Horizon oil spill, the algorithm classified the oil spill better than focusing on dark formation algorithm. Furthermore, the results were validated by the National Oceanic and Atmospheric Administration (NOAA) data.

  7. Investigation of Joint Visibility Between SAR and Optical Images of Urban Environments

    Hughes, L. H.; Auer, S.; Schmitt, M.

    2018-05-01

    In this paper, we present a work-flow to investigate the joint visibility between very-high-resolution SAR and optical images of urban scenes. For this task, we extend the simulation framework SimGeoI to enable a simulation of individual pixels rather than complete images. Using the extended SimGeoI simulator, we carry out a case study using a TerraSAR-X staring spotlight image and a Worldview-2 panchromatic image acquired over the city of Munich, Germany. The results of this study indicate that about 55 % of the scene are visible in both images and are thus suitable for matching and data fusion endeavours, while about 25 % of the scene are affected by either radar shadow or optical occlusion. Taking the image acquisition parameters into account, our findings can provide support regarding the definition of upper bounds for image fusion tasks, as well as help to improve acquisition planning with respect to different application goals.

  8. Aircraft Segmentation in SAR Images Based on Improved Active Shape Model

    Zhang, X.; Xiong, B.; Kuang, G.

    2018-04-01

    In SAR image interpretation, aircrafts are the important targets arousing much attention. However, it is far from easy to segment an aircraft from the background completely and precisely in SAR images. Because of the complex structure, different kinds of electromagnetic scattering take place on the aircraft surfaces. As a result, aircraft targets usually appear to be inhomogeneous and disconnected. It is a good idea to extract an aircraft target by the active shape model (ASM), since combination of the geometric information controls variations of the shape during the contour evolution. However, linear dimensionality reduction, used in classic ACM, makes the model rigid. It brings much trouble to segment different types of aircrafts. Aiming at this problem, an improved ACM based on ISOMAP is proposed in this paper. ISOMAP algorithm is used to extract the shape information of the training set and make the model flexible enough to deal with different aircrafts. The experiments based on real SAR data shows that the proposed method achieves obvious improvement in accuracy.

  9. Advanced Interferometric Synthetic Aperture Imaging Radar (InSAR) for Dune Mapping

    Havivi, Shiran; Amir, Doron; Schvartzman, Ilan; August, Yitzhak; Mamman, Shimrit; Rotman, Stanely R.; Blumberg, Dan G.

    2016-04-01

    Aeolian morphologies are formed in the presence of sufficient wind energy and available lose particles. These processes occur naturally or are further enhanced or reduced by human intervention. The dimensions of change are dependent primarily on the wind energy and surface properties. Since the 1970s, remote sensing imagery, both optical and radar, have been used for documentation and interpretation of the geomorphologic changes of sand dunes. Remote sensing studies of aeolian morphologies is mostly useful to document major changes, yet, subtle changes, occurring in a period of days or months in scales of centimeters, are very difficult to detect in imagery. Interferometric Synthetic Aperture Radar (InSAR) is an imaging technique for measuring Earth's surface topography and deformation. InSAR images are produced by measuring the radar phase difference between two separated antennas that view the same surface area. Classical InSAR is based on high coherence between two or more images. The output (interferogram) can show subtle changes with an accuracy of several millimeters to centimeters. Very little work has been done on measuring or identifying the changes in dunes using InSAR methods. The reason is that dunes tend to be less coherent than firm, stable, surfaces. This work aims to demonstrate how interferometric decorrelation can be used for identifying dune instability. We hypothesize and demonstrate that the loss of radar coherence over time on dunes can be used as an indication of the dune's instability. When SAR images are acquired at sufficiently close intervals one can measure the time it takes to lose coherence and associate this time with geomorphic stability. To achieve our goals, the coherence change detection method was used, in order to identify dune stability or instability and the dune activity level. The Nitzanim-Ashdod coastal dunes along the Mediterranean, 40 km south of Tel-Aviv, Israel, were chosen as a case study. The dunes in this area are of

  10. Performance Analysis of Ship Wake Detection on Sentinel-1 SAR Images

    Maria Daniela Graziano

    2017-10-01

    Full Text Available A novel technique for ship wake detection has been recently proposed and applied on X-band Synthetic Aperture Radar images provided by COSMO/SkyMed and TerraSAR-X. The approach shows that the vast majority of wake features are correctly detected and validated in critical situations. In this paper, the algorithm was applied to 28 wakes imaged by Sentinel-1 mission with different polarizations and incidence angles with the aim of testing the method’s robustness with reference to radar frequency and resolution. The detection process is properly modified. The results show that the features were correctly classified in 78.5% of cases, whereas false confirmations occur mainly on Kelvin cusps. Finally, the results were compared with the algorithm performance on X-band images, showing that no significant difference arises. In fact, the total false confirmations rate was 15.8% on X-band images and 18.5% on C-band images. Moreover, since the main criticality concerns again the false confirmation of Kelvin cusps, the same empirical criterion suggested for the X-band SAR images yielded a negligible 1.5% of false detection rate.

  11. AN AUTOMATIC OPTICAL AND SAR IMAGE REGISTRATION METHOD USING ITERATIVE MULTI-LEVEL AND REFINEMENT MODEL

    C. Xu

    2016-06-01

    Full Text Available Automatic image registration is a vital yet challenging task, particularly for multi-sensor remote sensing images. Given the diversity of the data, it is unlikely that a single registration algorithm or a single image feature will work satisfactorily for all applications. Focusing on this issue, the mainly contribution of this paper is to propose an automatic optical-to-SAR image registration method using –level and refinement model: Firstly, a multi-level strategy of coarse-to-fine registration is presented, the visual saliency features is used to acquire coarse registration, and then specific area and line features are used to refine the registration result, after that, sub-pixel matching is applied using KNN Graph. Secondly, an iterative strategy that involves adaptive parameter adjustment for re-extracting and re-matching features is presented. Considering the fact that almost all feature-based registration methods rely on feature extraction results, the iterative strategy improve the robustness of feature matching. And all parameters can be automatically and adaptively adjusted in the iterative procedure. Thirdly, a uniform level set segmentation model for optical and SAR images is presented to segment conjugate features, and Voronoi diagram is introduced into Spectral Point Matching (VSPM to further enhance the matching accuracy between two sets of matching points. Experimental results show that the proposed method can effectively and robustly generate sufficient, reliable point pairs and provide accurate registration.

  12. The Research on Denoising of SAR Image Based on Improved K-SVD Algorithm

    Tan, Linglong; Li, Changkai; Wang, Yueqin

    2018-04-01

    SAR images often receive noise interference in the process of acquisition and transmission, which can greatly reduce the quality of images and cause great difficulties for image processing. The existing complete DCT dictionary algorithm is fast in processing speed, but its denoising effect is poor. In this paper, the problem of poor denoising, proposed K-SVD (K-means and singular value decomposition) algorithm is applied to the image noise suppression. Firstly, the sparse dictionary structure is introduced in detail. The dictionary has a compact representation and can effectively train the image signal. Then, the sparse dictionary is trained by K-SVD algorithm according to the sparse representation of the dictionary. The algorithm has more advantages in high dimensional data processing. Experimental results show that the proposed algorithm can remove the speckle noise more effectively than the complete DCT dictionary and retain the edge details better.

  13. Decomposition of Polarimetric SAR Images Based on Second- and Third-order Statics Analysis

    Kojima, S.; Hensley, S.

    2012-12-01

    There are many papers concerning the research of the decomposition of polerimetric SAR imagery. Most of them are based on second-order statics analysis that Freeman and Durden [1] suggested for the reflection symmetry condition that implies that the co-polarization and cross-polarization correlations are close to zero. Since then a number of improvements and enhancements have been proposed to better understand the underlying backscattering mechanisms present in polarimetric SAR images. For example, Yamaguchi et al. [2] added the helix component into Freeman's model and developed a 4 component scattering model for the non-reflection symmetry condition. In addition, Arii et al. [3] developed an adaptive model-based decomposition method that could estimate both the mean orientation angle and a degree of randomness for the canopy scattering for each pixel in a SAR image without the reflection symmetry condition. This purpose of this research is to develop a new decomposition method based on second- and third-order statics analysis to estimate the surface, dihedral, volume and helix scattering components from polarimetric SAR images without the specific assumptions concerning the model for the volume scattering. In addition, we evaluate this method by using both simulation and real UAVSAR data and compare this method with other methods. We express the volume scattering component using the wire formula and formulate the relationship equation between backscattering echo and each component such as the surface, dihedral, volume and helix via linearization based on second- and third-order statics. In third-order statics, we calculate the correlation of the correlation coefficients for each polerimetric data and get one new relationship equation to estimate each polarization component such as HH, VV and VH for the volume. As a result, the equation for the helix component in this method is the same formula as one in Yamaguchi's method. However, the equation for the volume

  14. A combined use of multispectral and SAR images for ship detection and characterization through object based image analysis

    Aiello, Martina; Gianinetto, Marco

    2017-10-01

    Marine routes represent a huge portion of commercial and human trades, therefore surveillance, security and environmental protection themes are gaining increasing importance. Being able to overcome the limits imposed by terrestrial means of monitoring, ship detection from satellite has recently prompted a renewed interest for a continuous monitoring of illegal activities. This paper describes an automatic Object Based Image Analysis (OBIA) approach to detect vessels made of different materials in various sea environments. The combined use of multispectral and SAR images allows for a regular observation unrestricted by lighting and atmospheric conditions and complementarity in terms of geographic coverage and geometric detail. The method developed adopts a region growing algorithm to segment the image in homogeneous objects, which are then classified through a decision tree algorithm based on spectral and geometrical properties. Then, a spatial analysis retrieves the vessels' position, length and heading parameters and a speed range is associated. Optimization of the image processing chain is performed by selecting image tiles through a statistical index. Vessel candidates are detected over amplitude SAR images using an adaptive threshold Constant False Alarm Rate (CFAR) algorithm prior the object based analysis. Validation is carried out by comparing the retrieved parameters with the information provided by the Automatic Identification System (AIS), when available, or with manual measurement when AIS data are not available. The estimation of length shows R2=0.85 and estimation of heading R2=0.92, computed as the average of R2 values obtained for both optical and radar images.

  15. AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY

    P. Fischer

    2018-04-01

    Full Text Available This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.

  16. A High-precision Motion Compensation Method for SAR Based on Image Intensity Optimization

    Hu Ke-bin

    2015-02-01

    Full Text Available Owing to the platform instability and precision limitations of motion sensors, motion errors negatively affect the quality of synthetic aperture radar (SAR images. The autofocus Back Projection (BP algorithm based on the optimization of image sharpness compensates for motion errors through phase error estimation. This method can attain relatively good performance, while assuming the same phase error for all pixels, i.e., it ignores the spatial variance of motion errors. To overcome this drawback, a high-precision motion error compensation method is presented in this study. In the proposed method, the Antenna Phase Centers (APC are estimated via optimization using the criterion of maximum image intensity. Then, the estimated APCs are applied for BP imaging. Because the APC estimation equals the range history estimation for each pixel, high-precision phase compensation for every pixel can be achieved. Point-target simulations and processing of experimental data validate the effectiveness of the proposed method.

  17. Monitoring of Building Construction by 4D Change Detection Using Multi-temporal SAR Images

    Yang, C. H.; Pang, Y.; Soergel, U.

    2017-05-01

    Monitoring urban changes is important for city management, urban planning, updating of cadastral map, etc. In contrast to conventional field surveys, which are usually expensive and slow, remote sensing techniques are fast and cost-effective alternatives. Spaceborne synthetic aperture radar (SAR) sensors provide radar images captured rapidly over vast areas at fine spatiotemporal resolution. In addition, the active microwave sensors are capable of day-and-night vision and independent of weather conditions. These advantages make multi-temporal SAR images suitable for scene monitoring. Persistent scatterer interferometry (PSI) detects and analyses PS points, which are characterized by strong, stable, and coherent radar signals throughout a SAR image sequence and can be regarded as substructures of buildings in built-up cities. Attributes of PS points, for example, deformation velocities, are derived and used for further analysis. Based on PSI, a 4D change detection technique has been developed to detect disappearance and emergence of PS points (3D) at specific times (1D). In this paper, we apply this 4D technique to the centre of Berlin, Germany, to investigate its feasibility and application for construction monitoring. The aims of the three case studies are to monitor construction progress, business districts, and single buildings, respectively. The disappearing and emerging substructures of the buildings are successfully recognized along with their occurrence times. The changed substructures are then clustered into single construction segments based on DBSCAN clustering and α-shape outlining for object-based analysis. Compared with the ground truth, these spatiotemporal results have proven able to provide more detailed information for construction monitoring.

  18. GOTCHA experience report: three-dimensional SAR imaging with complete circular apertures

    Ertin, Emre; Austin, Christian D.; Sharma, Samir; Moses, Randolph L.; Potter, Lee C.

    2007-04-01

    We study circular synthetic aperture radar (CSAR) systems collecting radar backscatter measurements over a complete circular aperture of 360 degrees. This study is motivated by the GOTCHA CSAR data collection experiment conducted by the Air Force Research Laboratory (AFRL). Circular SAR provides wide-angle information about the anisotropic reflectivity of the scattering centers in the scene, and also provides three dimensional information about the location of the scattering centers due to a non planar collection geometry. Three dimensional imaging results with single pass circular SAR data reveals that the 3D resolution of the system is poor due to the limited persistence of the reflectors in the scene. We present results on polarimetric processing of CSAR data and illustrate reasoning of three dimensional shape from multi-view layover using prior information about target scattering mechanisms. Next, we discuss processing of multipass (CSAR) data and present volumetric imaging results with IFSAR and three dimensional backprojection techniques on the GOTCHA data set. We observe that the volumetric imaging with GOTCHA data is degraded by aliasing and high sidelobes due to nonlinear flightpaths and sparse and unequal sampling in elevation. We conclude with a model based technique that resolves target features and enhances the volumetric imagery by extrapolating the phase history data using the estimated model.

  19. Research on a dem Coregistration Method Based on the SAR Imaging Geometry

    Niu, Y.; Zhao, C.; Zhang, J.; Wang, L.; Li, B.; Fan, L.

    2018-04-01

    Due to the systematic error, especially the horizontal deviation that exists in the multi-source, multi-temporal DEMs (Digital Elevation Models), a method for high precision coregistration is needed. This paper presents a new fast DEM coregistration method based on a given SAR (Synthetic Aperture Radar) imaging geometry to overcome the divergence and time-consuming problem of the conventional DEM coregistration method. First, intensity images are simulated for two DEMs under the given SAR imaging geometry. 2D (Two-dimensional) offsets are estimated in the frequency domain using the intensity cross-correlation operation in the FFT (Fast Fourier Transform) tool, which can greatly accelerate the calculation process. Next, the transformation function between two DEMs is achieved via the robust least-square fitting of 2D polynomial operation. Accordingly, two DEMs can be precisely coregistered. Last, two DEMs, i.e., one high-resolution LiDAR (Light Detection and Ranging) DEM and one low-resolution SRTM (Shutter Radar Topography Mission) DEM, covering the Yangjiao landslide region of Chongqing are taken as an example to test the new method. The results indicate that, in most cases, this new method can achieve not only a result as much as 80 times faster than the minimum elevation difference (Least Z-difference, LZD) DEM registration method, but also more accurate and more reliable results.

  20. Observation of pressure ridges in SAR images of sea ice: Scattering theory and comparison with observations

    Vesecky, J. F.; Daida, J. M.; Shuchman, R. A.; Onstott, R. H.; Camiso, J. C.

    1993-01-01

    Ridges and keels (hummocks and bummocks) in sea ice flows are important in sea ice research for both scientific and practical reasons. Sea ice movement and deformation is driven by internal and external stresses on the ice. Ridges and keels play important roles in both cases because they determine the external wind and current stresses via drag coefficients. For example, the drag coefficient over sea ice can vary by a factor of several depending on the fluid mechanical roughness length of the surface. This roughness length is thought to be strongly dependent on the ridge structures present. Thus, variations in ridge and keel structure can cause gradients in external stresses which must be balanced by internal stresses and possibly fracture of the ice. Ridging in sea ice is also a sign of fracture. In a practical sense, large ridges form the biggest impediment to surface travel over the ice or penetration through sea ice by ice-strengthened ships. Ridges also play an important role in the damage caused by sea ice to off-shore structures. Hence, observation and measurement of sea ice ridges is an important component of sea ice remote sensing. The research reported here builds on previous work, estimating the characteristics of ridges and leads in sea ice from SAR images. Our objective is to develop methods for quantitative measurement of sea ice ridges from SAR images. To make further progress, in particular, to estimate ridge height, a scattering model for ridges is needed. Our research approach for a ridge scattering model begins with a survey of the geometrical properties of ridges and a comparison with the characteristics of the surrounding ice. For this purpose we have used airborne optical laser (AOL) data collected during the 1987 Greenland Sea Experiment. These data were used to generate a spatial wavenumber spectrum for height variance for a typical ridge - the typical ridge is the average over 10 large ridges. Our first-order model radar scattering includes

  1. The Intercomparison of X-Band SAR Images from COSMO‑SkyMed and TerraSAR-X Satellites: Case Studies

    Simone Pettinato

    2013-06-01

    Full Text Available The analysis of experimental data collected by X-band SAR of COSMO-SkyMed (CSK® and TerraSAR-X (TSX images on the same surface types has shown significant differences in the signal level of the two sensors. In order to investigate the possibility of combining data from the two instruments, a study was carried out by comparing images collected with similar orbital and sensor parameters (e.g., incidence angle, polarization, look angle at approximately the same date on two Italian agricultural test sites. Several homogenous agricultural fields within the observed area common to the two sensors were selected. Some forest plots have also been considered and used as a reference target. Direct comparisons were then performed between CSK and TSX images in different acquisition modes. The analysis carried out on the agricultural fields showed that, in general, the backscattering coefficient is higher in TSX Stripmap images with respect to CSK-Himage (about 3 dB, while CSK-Ping Pong data showed values lower than TSX of about 4.8 dB. Finally, a difference in backscattering of about 2.5 dB was pointed out between CSK-Himage and Ping-Pong images on agricultural fields. These results, achieved on bare soils, have also been compared with simulations performed by using the Advanced Integral Equation Model (AIEM.

  2. Skipping the real world: Classification of PolSAR images without explicit feature extraction

    Hänsch, Ronny; Hellwich, Olaf

    2018-06-01

    The typical processing chain for pixel-wise classification from PolSAR images starts with an optional preprocessing step (e.g. speckle reduction), continues with extracting features projecting the complex-valued data into the real domain (e.g. by polarimetric decompositions) which are then used as input for a machine-learning based classifier, and ends in an optional postprocessing (e.g. label smoothing). The extracted features are usually hand-crafted as well as preselected and represent (a somewhat arbitrary) projection from the complex to the real domain in order to fit the requirements of standard machine-learning approaches such as Support Vector Machines or Artificial Neural Networks. This paper proposes to adapt the internal node tests of Random Forests to work directly on the complex-valued PolSAR data, which makes any explicit feature extraction obsolete. This approach leads to a classification framework with a significantly decreased computation time and memory footprint since no image features have to be computed and stored beforehand. The experimental results on one fully-polarimetric and one dual-polarimetric dataset show that, despite the simpler approach, accuracy can be maintained (decreased by only less than 2 % for the fully-polarimetric dataset) or even improved (increased by roughly 9 % for the dual-polarimetric dataset).

  3. Two-Step Single Slope/SAR ADC with Error Correction for CMOS Image Sensor

    Fang Tang

    2014-01-01

    Full Text Available Conventional two-step ADC for CMOS image sensor requires full resolution noise performance in the first stage single slope ADC, leading to high power consumption and large chip area. This paper presents an 11-bit two-step single slope/successive approximation register (SAR ADC scheme for CMOS image sensor applications. The first stage single slope ADC generates a 3-bit data and 1 redundant bit. The redundant bit is combined with the following 8-bit SAR ADC output code using a proposed error correction algorithm. Instead of requiring full resolution noise performance, the first stage single slope circuit of the proposed ADC can tolerate up to 3.125% quantization noise. With the proposed error correction mechanism, the power consumption and chip area of the single slope ADC are significantly reduced. The prototype ADC is fabricated using 0.18 μm CMOS technology. The chip area of the proposed ADC is 7 μm × 500 μm. The measurement results show that the energy efficiency figure-of-merit (FOM of the proposed ADC core is only 125 pJ/sample under 1.4 V power supply and the chip area efficiency is 84 k μm2·cycles/sample.

  4. Two-step single slope/SAR ADC with error correction for CMOS image sensor.

    Tang, Fang; Bermak, Amine; Amira, Abbes; Amor Benammar, Mohieddine; He, Debiao; Zhao, Xiaojin

    2014-01-01

    Conventional two-step ADC for CMOS image sensor requires full resolution noise performance in the first stage single slope ADC, leading to high power consumption and large chip area. This paper presents an 11-bit two-step single slope/successive approximation register (SAR) ADC scheme for CMOS image sensor applications. The first stage single slope ADC generates a 3-bit data and 1 redundant bit. The redundant bit is combined with the following 8-bit SAR ADC output code using a proposed error correction algorithm. Instead of requiring full resolution noise performance, the first stage single slope circuit of the proposed ADC can tolerate up to 3.125% quantization noise. With the proposed error correction mechanism, the power consumption and chip area of the single slope ADC are significantly reduced. The prototype ADC is fabricated using 0.18 μ m CMOS technology. The chip area of the proposed ADC is 7 μ m × 500 μ m. The measurement results show that the energy efficiency figure-of-merit (FOM) of the proposed ADC core is only 125 pJ/sample under 1.4 V power supply and the chip area efficiency is 84 k  μ m(2) · cycles/sample.

  5. On the classification of mixed floating pollutants on the Yellow Sea of China by using a quad-polarized SAR image

    Wang, Xiaochen; Shao, Yun; Tian, Wei; Li, Kun

    2018-06-01

    This study explored different methodologies using a C-band RADARSAT-2 quad-polarized Synthetic Aperture Radar (SAR) image located over China's Yellow Sea to investigate polarization decomposition parameters for identifying mixed floating pollutants from a complex ocean background. It was found that solitary polarization decomposition did not meet the demand for detecting and classifying multiple floating pollutants, even after applying a polarized SAR image. Furthermore, considering that Yamaguchi decomposition is sensitive to vegetation and the algal variety Enteromorpha prolifera, while H/A/alpha decomposition is sensitive to oil spills, a combination of parameters which was deduced from these two decompositions was proposed for marine environmental monitoring of mixed floating sea surface pollutants. A combination of volume scattering, surface scattering, and scattering entropy was the best indicator for classifying mixed floating pollutants from a complex ocean background. The Kappa coefficients for Enteromorpha prolifera and oil spills were 0.7514 and 0.8470, respectively, evidence that the composite polarized parameters based on quad-polarized SAR imagery proposed in this research is an effective monitoring method for complex marine pollution.

  6. Removal of Optically Thick Clouds from Multi-Spectral Satellite Images Using Multi-Frequency SAR Data

    Robert Eckardt

    2013-06-01

    Full Text Available This study presents a method for the reconstruction of pixels contaminated by optical thick clouds in multi-spectral Landsat images using multi-frequency SAR data. A number of reconstruction techniques have already been proposed in the scientific literature. However, all of the existing techniques have certain limitations. In order to overcome these limitations, we expose the Closest Spectral Fit (CSF method proposed by Meng et al. to a new, synergistic approach using optical and SAR data. Therefore, the term Closest Feature Vector (CFV is introduced. The technique facilitates an elegant way to avoid radiometric distortions in the course of image reconstruction. Furthermore the cloud cover removal is independent from underlying land cover types and assumptions on seasonality, etc. The methodology is applied to mono-temporal, multi-frequency SAR data from TerraSAR-X (X-Band, ERS (C-Band and ALOS Palsar (L-Band. This represents a way of thinking about Radar data not as foreign, but as additional data source in multi-spectral remote sensing. For the assessment of the image restoration performance, an experimental framework is established and a statistical evaluation protocol is designed. The results show the potential of a synergistic usage of multi-spectral and SAR data to overcome the loss of data due to cloud cover.

  7. Phi-s correlation and dynamic time warping - Two methods for tracking ice floes in SAR images

    Mcconnell, Ross; Kober, Wolfgang; Kwok, Ronald; Curlander, John C.; Pang, Shirley S.

    1991-01-01

    The authors present two algorithms for performing shape matching on ice floe boundaries in SAR (synthetic aperture radar) images. These algorithms quickly produce a set of ice motion and rotation vectors that can be used to guide a pixel value correlator. The algorithms match a shape descriptor known as the Phi-s curve. The first algorithm uses normalized correlation to match the Phi-s curves, while the second uses dynamic programming to compute an elastic match that better accommodates ice floe deformation. Some empirical data on the performance of the algorithms on Seasat SAR images are presented.

  8. An Integrated Processing Strategy for Mountain Glacier Motion Monitoring Based on SAR Images

    Ruan, Z.; Yan, S.; Liu, G.; LV, M.

    2017-12-01

    Mountain glacier dynamic variables are important parameters in studies of environment and climate change in High Mountain Asia. Due to the increasing events of abnormal glacier-related hazards, research of monitoring glacier movements has attracted more interest during these years. Glacier velocities are sensitive and changing fast under complex conditions of high mountain regions, which implies that analysis of glacier dynamic changes requires comprehensive and frequent observations with relatively high accuracy. Synthetic aperture radar (SAR) has been successfully exploited to detect glacier motion in a number of previous studies, usually with pixel-tracking and interferometry methods. However, the traditional algorithms applied to mountain glacier regions are constrained by the complex terrain and diverse glacial motion types. Interferometry techniques are prone to fail in mountain glaciers because of their narrow size and the steep terrain, while pixel-tracking algorithm, which is more robust in high mountain areas, is subject to accuracy loss. In order to derive glacier velocities continually and efficiently, we propose a modified strategy to exploit SAR data information for mountain glaciers. In our approach, we integrate a set of algorithms for compensating non-glacial-motion-related signals which exist in the offset values retrieved by sub-pixel cross-correlation of SAR image pairs. We exploit modified elastic deformation model to remove the offsets associated with orbit and sensor attitude, and for the topographic residual offset we utilize a set of operations including DEM-assisted compensation algorithm and wavelet-based algorithm. At the last step of the flow, an integrated algorithm combining phase and intensity information of SAR images will be used to improve regional motion results failed in cross-correlation related processing. The proposed strategy is applied to the West Kunlun Mountain and Muztagh Ata region in western China using ALOS

  9. Data Based Parameter Estimation Method for Circular-scanning SAR Imaging

    Chen Gong-bo

    2013-06-01

    Full Text Available The circular-scanning Synthetic Aperture Radar (SAR is a novel working mode and its image quality is closely related to the accuracy of the imaging parameters, especially considering the inaccuracy of the real speed of the motion. According to the characteristics of the circular-scanning mode, a new data based method for estimating the velocities of the radar platform and the scanning-angle of the radar antenna is proposed in this paper. By referring to the basic conception of the Doppler navigation technique, the mathematic model and formulations for the parameter estimation are firstly improved. The optimal parameter approximation based on the least square criterion is then realized in solving those equations derived from the data processing. The simulation results verified the validity of the proposed scheme.

  10. AN UNSUPERVISED CHANGE DETECTION BASED ON TEST STATISTIC AND KI FROM MULTI-TEMPORAL AND FULL POLARIMETRIC SAR IMAGES

    J. Q. Zhao

    2016-06-01

    Full Text Available Accurate and timely change detection of Earth’s surface features is extremely important for understanding relationships and interactions between people and natural phenomena. Many traditional methods of change detection only use a part of polarization information and the supervised threshold selection. Those methods are insufficiency and time-costing. In this paper, we present a novel unsupervised change-detection method based on quad-polarimetric SAR data and automatic threshold selection to solve the problem of change detection. First, speckle noise is removed for the two registered SAR images. Second, the similarity measure is calculated by the test statistic, and automatic threshold selection of KI is introduced to obtain the change map. The efficiency of the proposed method is demonstrated by the quad-pol SAR images acquired by Radarsat-2 over Wuhan of China.

  11. Visual analytics for semantic queries of TerraSAR-X image content

    Espinoza-Molina, Daniela; Alonso, Kevin; Datcu, Mihai

    2015-10-01

    With the continuous image product acquisition of satellite missions, the size of the image archives is considerably increasing every day as well as the variety and complexity of their content, surpassing the end-user capacity to analyse and exploit them. Advances in the image retrieval field have contributed to the development of tools for interactive exploration and extraction of the images from huge archives using different parameters like metadata, key-words, and basic image descriptors. Even though we count on more powerful tools for automated image retrieval and data analysis, we still face the problem of understanding and analyzing the results. Thus, a systematic computational analysis of these results is required in order to provide to the end-user a summary of the archive content in comprehensible terms. In this context, visual analytics combines automated analysis with interactive visualizations analysis techniques for an effective understanding, reasoning and decision making on the basis of very large and complex datasets. Moreover, currently several researches are focused on associating the content of the images with semantic definitions for describing the data in a format to be easily understood by the end-user. In this paper, we present our approach for computing visual analytics and semantically querying the TerraSAR-X archive. Our approach is mainly composed of four steps: 1) the generation of a data model that explains the information contained in a TerraSAR-X product. The model is formed by primitive descriptors and metadata entries, 2) the storage of this model in a database system, 3) the semantic definition of the image content based on machine learning algorithms and relevance feedback, and 4) querying the image archive using semantic descriptors as query parameters and computing the statistical analysis of the query results. The experimental results shows that with the help of visual analytics and semantic definitions we are able to explain

  12. An Adaptive Ship Detection Algorithm for Hrws SAR Images Under Complex Background: Application to SENTINEL1A Data

    He, G.; Xia, Z.; Chen, H.; Li, K.; Zhao, Z.; Guo, Y.; Feng, P.

    2018-04-01

    Real-time ship detection using synthetic aperture radar (SAR) plays a vital role in disaster emergency and marine security. Especially the high resolution and wide swath (HRWS) SAR images, provides the advantages of high resolution and wide swath synchronously, significantly promotes the wide area ocean surveillance performance. In this study, a novel method is developed for ship target detection by using the HRWS SAR images. Firstly, an adaptive sliding window is developed to propose the suspected ship target areas, based upon the analysis of SAR backscattering intensity images. Then, backscattering intensity and texture features extracted from the training samples of manually selected ship and non-ship slice images, are used to train a support vector machine (SVM) to classify the proposed ship slice images. The approach is verified by using the Sentinl1A data working in interferometric wide swath mode. The results demonstrate the improvement performance of the proposed method over the constant false alarm rate (CFAR) method, where the classification accuracy improved from 88.5 % to 96.4 % and the false alarm rate mitigated from 11.5 % to 3.6 % compared with CFAR respectively.

  13. STUDY ON LANDSLIDE DISASTER EXTRACTION METHOD BASED ON SPACEBORNE SAR REMOTE SENSING IMAGES – TAKE ALOS PALSAR FOR AN EXAMPLE

    D. Xue

    2018-04-01

    Full Text Available In this paper, sequence ALOS PALSAR data and airborne SAR data of L-band from June 5, 2008 to September 8, 2015 are used. Based on the research of SAR data preprocessing and core algorithms, such as geocode, registration, filtering, unwrapping and baseline estimation, the improved Goldstein filtering algorithm and the branch-cut path tracking algorithm are used to unwrap the phase. The DEM and surface deformation information of the experimental area were extracted. Combining SAR-specific geometry and differential interferometry, on the basis of composite analysis of multi-source images, a method of detecting landslide disaster combining coherence of SAR image is developed, which makes up for the deficiency of single SAR and optical remote sensing acquisition ability. Especially in bad weather and abnormal climate areas, the speed of disaster emergency and the accuracy of extraction are improved. It is found that the deformation in this area is greatly affected by faults, and there is a tendency of uplift in the southeast plain and western mountainous area, while in the southwest part of the mountain area there is a tendency to sink. This research result provides a basis for decision-making for local disaster prevention and control.

  14. Geocoding of SAR Image Using the Orbit and Attitude Determination of RADARSAT

    Jin Wook So

    1998-06-01

    Full Text Available The Synthetic Aperture Radar (SAR image and the Digital Elevation Model (DEM of an target area are put into use to generate three dimensional image map. An method of image map generation is explained. The orbit and attitude determination of satellite makes it possible to model signal acquisition configuration precisely, which is a key to mapping image coordinates to geographic coordinates of concerned area. An application is made to RADARSAT in the purpose of testing its validity. To determine the orbit, zero Doppler range is used. And to determine the attitude, Doppler centroid frequency, which is the frequency observed when target is in the center of antenna's view, is used. Conventional geocoding has been performed on the basis of direct method(mapping image coordinates to geographic coordinates, but in this research the inverse method (mapping from geographic coordinates to image coordinates is taken. This paper shows that precise signal acquisition modeling based on the orbit and attitude determination of satellite as a platform leads to a satellite-centered accurate geocoding process. It also shows how to model relative motion between spaceborne radar and target. And the relative motion is described in ECIC (earth-centered initial coordinates using Doppler equation and signal acquisition geometry.

  15. Expressway deformation mapping using high-resolution TerraSAR-X images

    Shi, Xuguo

    2014-01-27

    Monitoring deformation of linear infrastructures such as expressway and railway caused by natural processes or anthropogenic activities is a vital task to ensure the safety of human lives and properties. Interferometric Synthetic Aperture Radar (InSAR) has been widely recognized as an effective technology to carry out large-area surface deformation mapping. However, its application in linear infrastructure deformation monitoring has not been intensively studied till now. In this article, a modified Small BAseline Subset (SBAS) method is proposed to retrieve the deformation patterns of the expressway. In our method, only the point-like targets identified on the expressway were kept in our analysis, and two complementary subsets of interferograms were formed to better separate the signals of height error and deformation from inteferometric phase observations. We successfully applied this method with multitemporal high-resolution TerraSAR-X images to retrieve the spatialoral pattern of surface deformation along the Beian-Heihe expressway that is located in island-permafrost areas and threatened by geohazards. © 2014 Taylor & Francis.

  16. MAXIMUM LIKELIHOOD CLASSIFICATION OF HIGH-RESOLUTION SAR IMAGES IN URBAN AREA

    M. Soheili Majd

    2012-09-01

    Full Text Available In this work, we propose a state-of-the-art on statistical analysis of polarimetric synthetic aperture radar (SAR data, through the modeling of several indices. We concentrate on eight ground classes which have been carried out from amplitudes, co-polarisation ratio, depolarization ratios, and other polarimetric descriptors. To study their different statistical behaviours, we consider Gauss, log- normal, Beta I, Weibull, Gamma, and Fisher statistical models and estimate their parameters using three methods: method of moments (MoM, maximum-likelihood (ML methodology, and log-cumulants method (MoML. Then, we study the opportunity of introducing this information in an adapted supervised classification scheme based on Maximum–Likelihood and Fisher pdf. Our work relies on an image of a suburban area, acquired by the airborne RAMSES SAR sensor of ONERA. The results prove the potential of such data to discriminate urban surfaces and show the usefulness of adapting any classical classification algorithm however classification maps present a persistant class confusion between flat gravelled or concrete roofs and trees.

  17. Expressway deformation mapping using high-resolution TerraSAR-X images

    Shi, Xuguo; Liao, Mingsheng; Wang, Teng; Zhang, Lu; Shan, Wei; Wang, Chunjiao

    2014-01-01

    Monitoring deformation of linear infrastructures such as expressway and railway caused by natural processes or anthropogenic activities is a vital task to ensure the safety of human lives and properties. Interferometric Synthetic Aperture Radar (InSAR) has been widely recognized as an effective technology to carry out large-area surface deformation mapping. However, its application in linear infrastructure deformation monitoring has not been intensively studied till now. In this article, a modified Small BAseline Subset (SBAS) method is proposed to retrieve the deformation patterns of the expressway. In our method, only the point-like targets identified on the expressway were kept in our analysis, and two complementary subsets of interferograms were formed to better separate the signals of height error and deformation from inteferometric phase observations. We successfully applied this method with multitemporal high-resolution TerraSAR-X images to retrieve the spatialoral pattern of surface deformation along the Beian-Heihe expressway that is located in island-permafrost areas and threatened by geohazards. © 2014 Taylor & Francis.

  18. A New Method Based on Two-Stage Detection Mechanism for Detecting Ships in High-Resolution SAR Images

    Xu Yongli

    2017-01-01

    Full Text Available Ship detection in synthetic aperture radar (SAR remote sensing images, being a fundamental but challenging problem in the field of satellite image analysis, plays an important role for a wide range of applications and is receiving significant attention in recent years. Aiming at the requirements of ship detection in high-resolution SAR images, the accuracy, the intelligent level, a better real-time operation and processing efficiency, The characteristics of ocean background and ship target in high-resolution SAR images were analyzed, we put forward a ship detection algorithm in high-resolution SAR images. The algorithm consists of two detection stages: The first step designs a pre-training classifier based on improved spectral residual visual model to obtain the visual salient regions containing ship targets quickly, then achieve the purpose of probably detection of ships. In the second stage, considering the Bayesian theory of binary hypothesis detection, a local maximum posterior probability (MAP classifier is designed for the classification of pixels. After the parameter estimation and judgment criterion, the classification of pixels are carried out in the target areas to achieve the classification of two types of pixels in the salient regions. In the paper, several types of satellite image data, such as TerraSAR-X (TS-X, Radarsat-2, are used to evaluate the performance of detection methods. Comparing with classical CFAR detection algorithms, experimental results show that the algorithm can achieve a better effect of suppressing false alarms, which caused by the speckle noise and ocean clutter background inhomogeneity. At the same time, the detection speed is increased by 25% to 45%.

  19. Automated Registration Of Images From Multiple Sensors

    Rignot, Eric J. M.; Kwok, Ronald; Curlander, John C.; Pang, Shirley S. N.

    1994-01-01

    Images of terrain scanned in common by multiple Earth-orbiting remote sensors registered automatically with each other and, where possible, on geographic coordinate grid. Simulated image of terrain viewed by sensor computed from ancillary data, viewing geometry, and mathematical model of physics of imaging. In proposed registration algorithm, simulated and actual sensor images matched by area-correlation technique.

  20. Measurement of pressure ridges in SAR images of sea ice - Preliminary results on scattering theory

    Vesecky, J. F.; Smith, M. P.; Daida, J. M.; Samadani, R.; Camiso, J. C.

    1992-01-01

    Sea ice ridges and keels (hummocks and bummocks) are important in sea ice research for both scientific and practical reasons. A long-term objective is to make quantitative measurements of sea ice ridges using synthetic aperture radar (SAR) images. The preliminary results of a scattering model for sea ice ridge are reported. The approach is through the ridge height variance spectrum Psi(K), where K is the spatial wavenumber, and the two-scale scattering model. The height spectrum model is constructed to mimic height statistics observed with an airborne optical laser. The spectrum model is used to drive a two-scale scattering model. Model results for ridges observed at C- and X-band yield normalized radar cross sections that are 10 to 15 dB larger than the observed cross sections of multiyear ice over the range of angles of incidence from 10 to 70 deg.

  1. A Novel Fusion-Based Ship Detection Method from Pol-SAR Images

    Wenguang Wang

    2015-09-01

    Full Text Available A novel fusion-based ship detection method from polarimetric Synthetic Aperture Radar (Pol-SAR images is proposed in this paper. After feature extraction and constant false alarm rate (CFAR detection, the detection results of HH channel, diplane scattering by Pauli decomposition and helical factor by Barnes decomposition are fused together. The confirmed targets and potential target pixels can be obtained after the fusion process. Using the difference degree of the target, potential target pixels can be classified. The fusion-based ship detection method works accurately by utilizing three different features comprehensively. The result of applying the technique to measured Airborne Synthetic Radar (AIRSAR data shows that the novel detection method can achieve better performance in both ship’s detection and ship’s shape preservation compared to the result of K-means clustering method and the Notch Filter method.

  2. Classification of PolSAR Images Using Multilayer Autoencoders and a Self-Paced Learning Approach

    Wenshuai Chen

    2018-01-01

    Full Text Available In this paper, a novel polarimetric synthetic aperture radar (PolSAR image classification method based on multilayer autoencoders and self-paced learning (SPL is proposed. The multilayer autoencoders network is used to learn the features, which convert raw data into more abstract expressions. Then, softmax regression is applied to produce the predicted probability distributions over all the classes of each pixel. When we optimize the multilayer autoencoders network, self-paced learning is used to accelerate the learning convergence and achieve a stronger generalization capability. Under this learning paradigm, the network learns the easier samples first and gradually involves more difficult samples in the training process. The proposed method achieves the overall classification accuracies of 94.73%, 94.82% and 78.12% on the Flevoland dataset from AIRSAR, Flevoland dataset from RADARSAT-2 and Yellow River delta dataset, respectively. Such results are comparable with other state-of-the-art methods.

  3. Near Surface Soil Moisture Estimation Using SAR Images: A Case Study in the Mediterranean Area of Catalonia

    Reppucci, Antonio; Moreno, Laura

    2010-12-01

    Information on Soil moisture spatial and temporal evolution is of great importance for managing the utilization of soils and vegetation, in particular in environments where the water resources are scarce. In-situ measurement of soil moisture are costly and not able to sample the spatial behaviour of a whole region. Thanks to their all weather capability and wide coverage, Synthetic Aperture Radar (SAR) images offer the opportunity to monitor large area with high resolution. This study presents the results of a project, partially founded by the Catalan government, to improve the monitoring of soil moisture using Earth Observation data. In particular the project is focused on the calibration of existing semi-empirical algorithm in the area of study. This will be done using co-located SAR and in-situ measurements acquired during several field campaigns. Observed deviations between SAR measurements and in-situ measurement are discussed.

  4. Investigation of Slow-Moving Landslides from ALOS/PALSAR Images with TCPInSAR: A Case Study of Oso, USA

    Qian Sun

    2014-12-01

    Full Text Available Monitoring slope instability is of great significance for understanding landslide kinematics and, therefore, reducing the related geological hazards. In recent years, interferometric synthetic aperture radar (InSAR has been widely applied to this end, especially thanks to the prompt evolution of multi-temporal InSAR (MTInSAR algorithms. In this paper, temporarily-coherent point InSAR (TCPInSAR, a recently-developed MTInSAR technique, is employed to investigate the slow-moving landslides in Oso, U.S., with 13 ALOS/PALSAR images. Compared to other MTInSAR techniques, TCPInSAR can work well with a small amount of data and is immune to unwrapping errors. Furthermore, the severe orbital ramps emanated from the inaccurate determination of the ALOS satellite’s state vector can be jointly estimated by TCPInSAR, resulting in an exhaustive separation between the orbital errors and displacement signals. The TCPInSAR-derived deformation map indicates that the riverside slopes adjacent to the North Fork of the Stillaguamish River, where the 2014 mudslide occurred, were active during 2007 and 2011. Besides, Coal Mountain has been found to be experiencing slow-moving landslides with clear boundaries and considerable magnitudes. The Deer Creek River is also threatened by a potential landslide dam due to the creeps detected in a nearby slope. The slope instability information revealed in this study is helpful to deal with the landslide hazards in Oso.

  5. Ship Detection in Gaofen-3 SAR Images Based on Sea Clutter Distribution Analysis and Deep Convolutional Neural Network.

    An, Quanzhi; Pan, Zongxu; You, Hongjian

    2018-01-24

    Target detection is one of the important applications in the field of remote sensing. The Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) satellite launched by China is a powerful tool for maritime monitoring. This work aims at detecting ships in GF-3 SAR images using a new land masking strategy, the appropriate model for sea clutter and a neural network as the discrimination scheme. Firstly, the fully convolutional network (FCN) is applied to separate the sea from the land. Then, by analyzing the sea clutter distribution in GF-3 SAR images, we choose the probability distribution model of Constant False Alarm Rate (CFAR) detector from K-distribution, Gamma distribution and Rayleigh distribution based on a tradeoff between the sea clutter modeling accuracy and the computational complexity. Furthermore, in order to better implement CFAR detection, we also use truncated statistic (TS) as a preprocessing scheme and iterative censoring scheme (ICS) for boosting the performance of detector. Finally, we employ a neural network to re-examine the results as the discrimination stage. Experiment results on three GF-3 SAR images verify the effectiveness and efficiency of this approach.

  6. A novel ship CFAR detection algorithm based on adaptive parameter enhancement and wake-aided detection in SAR images

    Meng, Siqi; Ren, Kan; Lu, Dongming; Gu, Guohua; Chen, Qian; Lu, Guojun

    2018-03-01

    Synthetic aperture radar (SAR) is an indispensable and useful method for marine monitoring. With the increase of SAR sensors, high resolution images can be acquired and contain more target structure information, such as more spatial details etc. This paper presents a novel adaptive parameter transform (APT) domain constant false alarm rate (CFAR) to highlight targets. The whole method is based on the APT domain value. Firstly, the image is mapped to the new transform domain by the algorithm. Secondly, the false candidate target pixels are screened out by the CFAR detector to highlight the target ships. Thirdly, the ship pixels are replaced by the homogeneous sea pixels. And then, the enhanced image is processed by Niblack algorithm to obtain the wake binary image. Finally, normalized Hough transform (NHT) is used to detect wakes in the binary image, as a verification of the presence of the ships. Experiments on real SAR images validate that the proposed transform does enhance the target structure and improve the contrast of the image. The algorithm has a good performance in the ship and ship wake detection.

  7. Experimental validation of hyperthermia SAR treatment planning using MR B1+ imaging

    Berg, Cornelis A T van den; Bartels, Lambertus W; Leeuw, Astrid A C De; Lagendijk, Jan J W; Kamer, Jeroen B Van de

    2004-01-01

    In this paper the concept of using B 1+ imaging as a means to validate SAR models for radiofrequency hyperthermia is presented. As in radiofrequency hyperthermia, in common clinical MR imaging which applies RF frequencies between 64 and 128 MHz, the RF field distribution inside a patient is largely determined by the dielectric distribution of the anatomy. Modern MR imaging techniques allow measurement of the RF magnetic field component B 1+ making it possible to measure at high resolution the dielectric interaction of the RF field with the patient. Given these considerations, we propose to use MR imaging to verify the validity of our dielectric patient model used for SAR models of radiofrequency hyperthermia. The aim of this study was to investigate the feasibility of this concept by performing B 1+ measurements and simulations on cylindrical split phantoms consisting of materials with dielectric properties similar to human tissue types. Important topics of investigation were the accuracy and sensitivity of B 1+ measurements and the validity of the electric model of the MR body coil. The measurements were performed on a clinical 1.5 T MR scanner with its quadrature body coil operating at 64 MHz. It was shown that even small B 1+ variations of 2 to 5% could be measured reliably in the phantom experiments. An electrical model of the transmit coil was implemented on our FDTD-based hyperthermia treatment planning platform and the RF field distributions were calculated assuming an idealized quadrature current distribution in the coil. A quantitatively good correlation between measurements and simulations was found for phantoms consisting of water and oil, while highly conductive phantoms show considerable deviations. However, assuming linear excitation for these conductive phantoms resulted in good correspondence. As an explanation it is suggested that the coil is being detuned due to the inductive nature of the conductive phantoms, breaking up the phase difference of

  8. Selective interferometric imaging of internal multiples

    Zuberi, M. A H

    2013-01-01

    Internal multiples deteriorate the image when the imaging procedure assumes only single scattering, especially if the velocity model does not reproduce such scattering in the Green’s function. If properly imaged, internal multiples (and internally-scattered energy) can enhance the seismic image and illuminate areas otherwise neglected or poorly imaged by conventional single-scattering approaches. Conventionally, in order to image internal multiples, accurate, sharp contrasts in the velocity model are required to construct a Green’s function with all the scattered energy. As an alternative, we develop a three-step procedure, which images the first-order internal scattering using the background Green’s function (from the surface to each image point), constructed from a smooth velocity model: We first back-propagate the recorded surface data using the background Green’s function, then cross-correlate the back-propagated data with the recorded data and finally cross-correlate the result with the original background Green’s function. This procedure images the contribution of the recorded first-order internal multiples and is almost free of the single-scattering recorded energy. This image can be added to the conventional single-scattering image, obtained e.g. from Kirchhoff migration, to enhance the image. Application to synthetic data with reflectors illuminated by multiple scattering only demonstrates the effectiveness of the approach.

  9. Bistatic sAR data processing algorithms

    Qiu, Xiaolan; Hu, Donghui

    2013-01-01

    Synthetic Aperture Radar (SAR) is critical for remote sensing. It works day and night, in good weather or bad. Bistatic SAR is a new kind of SAR system, where the transmitter and receiver are placed on two separate platforms. Bistatic SAR is one of the most important trends in SAR development, as the technology renders SAR more flexible and safer when used in military environments. Imaging is one of the most difficult and important aspects of bistatic SAR data processing. Although traditional SAR signal processing is fully developed, bistatic SAR has a more complex system structure, so sign

  10. Wake-based ship route estimation in high-resolution SAR images

    Graziano, M. Daniela; Rufino, Giancarlo; D'Errico, Marco

    2014-10-01

    This paper presents a novel algorithm for wake detection in Synthetic Aperture Radar images of the sea. The algorithm has been conceived as part of a ship traffic monitoring system, in charge of ship detection validation and to estimate ship route features, such as heading and ground speed. In addition, it has been intended to be adequate for inclusion in an automatic procedure without human operator supervision. The algorithm exploits the Radon transform to identify the images ship wake on the basis of the well known theoretical characteristics of the wakes' geometry and components, that are the turbulent wake, the narrow-V wakes, and the Kelvin arms, as well as the typical appearance of such components in Synthetic Aperture Radar images of the sea as bright or dark linear feature. Examples of application to high-resolution X-band Synthetic Aperture Radar products (COSMOSkymed and TerraSAR-X) are reported, both for wake detection and ship route estimation, showing the achieved quality and reliability of wake detection, adequacy to automatic procedures, as well as speed measure accuracy.

  11. Multiple-image oscilloscope camera

    Yasillo, N.J.

    1978-01-01

    An optical device for placing automatically a plurality of images at selected locations on one film comprises a stepping motor coupled to a rotating mirror and lens. A mechanical connection from the mirror controls an electronic logical system to allow rotation of the mirror to place a focused image at tge desired preselected location. The device is of especial utility when used to place four images on a single film to record oscilloscope views obtained in gamma radiography

  12. Simultaneous Genomic Detection of Multiple Enteric Bacterial and Viral Pathogens, Including Sars-CoV and RVFV

    Payne, S; Peters, C. J. (Clarence James), 1940; Makino, S; Oliver, K; Weiss, C; Kornguth, S; Carruthers, L; Chin, R

    2004-01-01

    ...) associated with the SARS-associated coronavirus (SARS-CoV) and Rift Valley Fever Virus (RVFV) has been developed. This system is based upon the Luminex xMAP" System, a multiplexed assay platform that combines high sample throughput...

  13. The 2008 Wells, Nevada earthquake sequence: Source constraints using calibrated multiple event relocation and InSAR

    Nealy, Jennifer; Benz, Harley M.; Hayes, Gavin; Berman, Eric; Barnhart, William

    2017-01-01

    The 2008 Wells, NV earthquake represents the largest domestic event in the conterminous U.S. outside of California since the October 1983 Borah Peak earthquake in southern Idaho. We present an improved catalog, magnitude complete to 1.6, of the foreshock-aftershock sequence, supplementing the current U.S. Geological Survey (USGS) Preliminary Determination of Epicenters (PDE) catalog with 1,928 well-located events. In order to create this catalog, both subspace and kurtosis detectors are used to obtain an initial set of earthquakes and associated locations. The latter are then calibrated through the implementation of the hypocentroidal decomposition method and relocated using the BayesLoc relocation technique. We additionally perform a finite fault slip analysis of the mainshock using InSAR observations. By combining the relocated sequence with the finite fault analysis, we show that the aftershocks occur primarily updip and along the southwestern edge of the zone of maximum slip. The aftershock locations illuminate areas of post-mainshock strain increase; aftershock depths, ranging from 5 to 16 km, are consistent with InSAR imaging, which shows that the Wells earthquake was a buried source with no observable near-surface offset.

  14. Automated Waterline Detection in the Wadden Sea Using High-Resolution TerraSAR-X Images

    Stefan Wiehle

    2015-01-01

    Full Text Available We present an algorithm for automatic detection of the land-water-line from TerraSAR-X images acquired over the Wadden Sea. In this coastal region of the southeastern North Sea, a strip of up to 20 km of seabed falls dry during low tide, revealing mudflats and tidal creeks. The tidal currents transport sediments and can change the coastal shape with erosion rates of several meters per month. This rate can be strongly increased by storm surges which also cause flooding of usually dry areas. Due to the high number of ships traveling through the Wadden Sea to the largest ports of Germany, frequent monitoring of the bathymetry is also an important task for maritime security. For such an extended area and the required short intervals of a few months, only remote sensing methods can perform this task efficiently. Automating the waterline detection in weather-independent radar images provides a fast and reliable way to spot changes in the coastal topography. The presented algorithm first performs smoothing, brightness thresholding, and edge detection. In the second step, edge drawing and flood filling are iteratively performed to determine optimal thresholds for the edge drawing. In the last step, small misdetections are removed.

  15. Simulation-Based Evaluation of Light Posts and Street Signs as 3-D Geolocation Targets in SAR Images

    Auer, S.; Balss, U.

    2017-05-01

    The assignment of phase center positions (in 2D or 3D) derived from SAR data to physical object is challenging for many man-made structures such as buildings or bridges. In contrast, light poles and traffic signs are promising targets for tasks based on 3-D geolocation as they often show a prominent and spatially isolated appearance. For a detailed understanding of the nature of both targets, this paper presents results of a dedicated simulation case study, which is based on ray tracing methods (simulator RaySAR). For the first time, the appearance of the targets is analyzed in 2D (image plane) and 3D space (world coordinates of scene model) and reflecting surfaces are identified for related dominant image pixels. The case studies confirms the crucial impact of spatial resolution in the context of light poles and traffic signs and the appropriateness of light poles as target for 3-D geolocation in case of horizontal ground surfaces beneath.

  16. PET imaging in multiple sclerosis

    Faria, Daniele de Paula; Copray, Sjef; Buchpiguel, Carlos; Dierckx, Rudi; de Vries, Erik

    Positron emission tomography (PET) is a non-invasive technique for quantitative imaging of biochemical and physiological processes in animals and humans. PET uses probes labeled with a radioactive isotope, called PET tracers, which can bind to or be converted by a specific biological target and thus

  17. Multimodality imaging features of hereditary multiple exostoses

    Kok, H K; Fitzgerald, L; Campbell, N; Lyburn, I D; Munk, P L; Buckley, O; Torreggiani, W C

    2013-01-01

    Hereditary multiple exostoses (HME) or diaphyseal aclasis is an inherited disorder characterised by the formation of multiple osteochondromas, which are cartilage-capped osseous outgrowths, and the development of associated osseous deformities. Individuals with HME may be asymptomatic or develop clinical symptoms, which prompt imaging studies. Different modalities ranging from plain radiographs to cross-sectional and nuclear medicine imaging studies can be helpful in the diagnosis and detecti...

  18. Multiple Image Radiography With Diffraction Enhanced Imaging For Breast Specimen

    Oltulu, Oral; Zhong Zhong; Hasnah, Moumen; Chapman, Dean

    2007-01-01

    Biological samples are of great interest for many imaging techniques. The samples usually contain small structures and weak absorption properties. The combinations of weak signals with overlying structures make feature recognition difficult in many cases. In the x-ray regime, a relatively new imaging technique Diffraction Enhanced Imaging (DEI) has superior tissue contrast over conventional radiography and is proven to be very sensitive method. Multiple images taken by DEI are called Multiple Image Radiography (MIR). The purpose of this study is to validate the potential application of the method and to show that MIR-DEI method may give more information about the sample

  19. Multiplicative calculus in biomedical image analysis

    Florack, L.M.J.; Assen, van H.C.

    2011-01-01

    We advocate the use of an alternative calculus in biomedical image analysis, known as multiplicative (a.k.a. non-Newtonian) calculus. It provides a natural framework in problems in which positive images or positive definite matrix fields and positivity preserving operators are of interest. Indeed,

  20. SAR Imaging of Wave Tails: Recognition of Second Mode Internal Wave Patterns and Some Mechanisms of their Formation

    da Silva, Jose C. B.; Magalhaes, J. M.; Buijsman, M. C.; Garcia, C. A. E.

    2016-08-01

    Mode-2 internal waves are usually not as energetic as larger mode-1 Internal Solitary Waves (ISWs), but they have attracted a great deal of attention in recent years because they have been identified as playing a significant role in mixing shelf waters [1]. This mixing is particularly effective for mode-2 ISWs because the location of these waves in the middle of the pycnocline plays an important role in eroding the barrier between the base of the surface mixed layer and the stratified deep layer below. An urgent problem in physical oceanography is therefore to account for the magnitude and distribution of ISW-driven mixing, including mode-2 ISWs. Several generation mechanisms of mode-2 ISWs have been identified. These include: (1) mode-1 ISWs propagating onshore (shoaling) and entering the breaking instability stage, or propagating over a steep sill; (2) a mode-1 ISW propagating offshore (antishoaling) over steep slopes of the shelf break, and undergoing modal transformation; (3) intrusion of the whole head of a gravity current into a three-layer fluid; (4) impingement of an internal tidal beam on the pycnocline, itself emanating from critical bathymetry; (5) nonlinear disintegration of internal tide modes; (6) lee wave mechanism. In this paper we provide methods to identify internal wave features denominated "Wave Tails" in SAR images of the ocean surface, which are many times associated with second mode internal waves. The SAR case studies that are presented portray evidence of the aforementioned generation mechanisms, and we further discuss possible methods to discriminate between the various types of mode-2 ISWs in SAR images, that emerge from these physical mechanisms. Some of the SAR images correspond to numerical simulations with the MITgcm in fully nonlinear and nonhydrostatic mode and in a 2D configuration with realistic stratification, bathymetry and other environmental conditions.Results of a global survey with some of these observations are presented

  1. 2002/2003 IfSAR data for Southern California: Radar Reflectance Image

    National Oceanic and Atmospheric Administration, Department of Commerce — This metadata document describes the collection and processing of topographic elevation point data derived from Interferometric Synthetic Aperture Radar (IfSAR)...

  2. Coral reef detection using SAR/RADARSAT-1 images at Costa dos Corais, PE/AL, Brazil

    Frederico de Moraes Rudorff

    2008-06-01

    Full Text Available The present work aimed to examine the potentials of SAR RADARSAT-1 images to detect emergent coral reefs at the Environmental Protection Area of "Costa dos Corais". Multi-view filters were applied and tested for speckle noise reduction. A digital unsupervised classification based on image segmentation was performed and the classification accuracy was evaluated by an error matrix built between the SAR image classification and a reference map obtained from a TM Landsat-5 classification. The adaptative filters showed the best results for speckle suppression and border preservation, especially the Kuan, Gamma MAP, Lee, Frost and Enhanced Frost filters. Small similarity and area thresholds (5 and 10, respectively were used for the image segmentation due to the reduced dimensions and the narrow and elongated forms of the reefs. The classification threshold of 99% had a better user's accuracy, but a lower producer's accuracy because it is a more restrictive threshold; therefore, it may be possible that it had a greater omission on reef classification. The results indicate that SAR images have a good potential for the detection of emergent coral reefs.O presente trabalho examinou o potencial de imagens SAR do RADARSAT-1 na detecção de recifes de coral expostos na Área de Proteção Ambiental das Costa dos Corais. Filtros de multi-visada foram aplicados e testados para redução do ruído speckle. Uma classificação não supervisionada baseada em uma imagem segmentada foi realizada e a acurácia da classificação foi avaliada através de uma matriz de erro construída entre a imagem classificada e o mapa de referência. Os filtros adaptativos apresentaram os melhores desempenhos para supressão de speckle e preservação de bordas, especialmente os filtros Kuan, Gamma MAP, Lee, Frost and Enhanced Frost. Os pequenos limiares de similaridade e de área (10 e 5, respectivamente foram melhores devido à forma fina e alongada dos recifes. O limiar de

  3. Oil seepage polarimetric contrast analysis in a time series of TerraSAR-X images

    de Macedo, Carina Regina; Nunziata, Ferdinando; Velotto, Domenico; Migliaccio, Maurizio

    2017-01-01

    Natural hydrocarbon seeps are broadly distributed across the Gulf of Mexico. Such seeps emit oil and gas into the water column, increasing the phytoplankton biomass and impacting regionally the productivity, carbon and nutrient cycling [1]. A fraction of this oil reaches to the sea surface and can be detected by SAR data. Although the ability of SAR data to detect oil features present in ocean's surface is wide exploited in the literature, it is known that the detection of those features is a...

  4. Bistatic SAR: Proof of Concept.

    Yocky, David A.; Doren, Neall E.; Bacon, Terry A.; Wahl, Daniel E.; Eichel, Paul H.; Jakowatz, Charles V,; Delaplain, Gilbert G.; Dubbert, Dale F.; Tise, Bertice L.; White, Kyle R.

    2014-10-01

    Typical synthetic aperture RADAR (SAR) imaging employs a co-located RADAR transmitter and receiver. Bistatic SAR imaging separates the transmitter and receiver locations. A bistatic SAR configuration allows for the transmitter and receiver(s) to be in a variety of geometric alignments. Sandia National Laboratories (SNL) / New Mexico proposed the deployment of a ground-based RADAR receiver. This RADAR receiver was coupled with the capability of digitizing and recording the signal collected. SNL proposed the possibility of creating an image of targets the illuminating SAR observes. This document describes the developed hardware, software, bistatic SAR configuration, and its deployment to test the concept of a ground-based bistatic SAR. In the proof-of-concept experiments herein, the RADAR transmitter will be a commercial SAR satellite and the RADAR receiver will be deployed at ground level, observing and capturing RADAR ground/targets illuminated by the satellite system.

  5. Secure image retrieval with multiple keys

    Liang, Haihua; Zhang, Xinpeng; Wei, Qiuhan; Cheng, Hang

    2018-03-01

    This article proposes a secure image retrieval scheme under a multiuser scenario. In this scheme, the owner first encrypts and uploads images and their corresponding features to the cloud; then, the user submits the encrypted feature of the query image to the cloud; next, the cloud compares the encrypted features and returns encrypted images with similar content to the user. To find the nearest neighbor in the encrypted features, an encryption with multiple keys is proposed, in which the query feature of each user is encrypted by his/her own key. To improve the key security and space utilization, global optimization and Gaussian distribution are, respectively, employed to generate multiple keys. The experiments show that the proposed encryption can provide effective and secure image retrieval for each user and ensure confidentiality of the query feature of each user.

  6. An Improved InSAR Image Co-Registration Method for Pairs with Relatively Big Distortions or Large Incoherent Areas

    Zhenwei Chen

    2016-09-01

    Full Text Available Co-registration is one of the most important steps in interferometric synthetic aperture radar (InSAR data processing. The standard offset-measurement method based on cross-correlating uniformly distributed patches takes no account of specific geometric transformation between images or characteristics of ground scatterers. Hence, it is inefficient and difficult to obtain satisfying co-registration results for image pairs with relatively big distortion or large incoherent areas. Given this, an improved co-registration strategy is proposed in this paper which takes both the geometric features and image content into consideration. Firstly, some geometric transformations including scale, flip, rotation, and shear between images were eliminated based on the geometrical information, and the initial co-registration polynomial was obtained. Then the registration points were automatically detected by integrating the signal-to-clutter-ratio (SCR thresholds and the amplitude information, and a further co-registration process was performed to refine the polynomial. Several comparison experiments were carried out using 2 TerraSAR-X data from the Hong Kong airport and 21 PALSAR data from the Donghai Bridge. Experiment results demonstrate that the proposed method brings accuracy and efficiency improvements for co-registration and processing abilities in the cases of big distortion between images or large incoherent areas in the images. For most co-registrations, the proposed method can enhance the reliability and applicability of co-registration and thus promote the automation to a higher level.

  7. An Improved InSAR Image Co-Registration Method for Pairs with Relatively Big Distortions or Large Incoherent Areas.

    Chen, Zhenwei; Zhang, Lei; Zhang, Guo

    2016-09-17

    Co-registration is one of the most important steps in interferometric synthetic aperture radar (InSAR) data processing. The standard offset-measurement method based on cross-correlating uniformly distributed patches takes no account of specific geometric transformation between images or characteristics of ground scatterers. Hence, it is inefficient and difficult to obtain satisfying co-registration results for image pairs with relatively big distortion or large incoherent areas. Given this, an improved co-registration strategy is proposed in this paper which takes both the geometric features and image content into consideration. Firstly, some geometric transformations including scale, flip, rotation, and shear between images were eliminated based on the geometrical information, and the initial co-registration polynomial was obtained. Then the registration points were automatically detected by integrating the signal-to-clutter-ratio (SCR) thresholds and the amplitude information, and a further co-registration process was performed to refine the polynomial. Several comparison experiments were carried out using 2 TerraSAR-X data from the Hong Kong airport and 21 PALSAR data from the Donghai Bridge. Experiment results demonstrate that the proposed method brings accuracy and efficiency improvements for co-registration and processing abilities in the cases of big distortion between images or large incoherent areas in the images. For most co-registrations, the proposed method can enhance the reliability and applicability of co-registration and thus promote the automation to a higher level.

  8. Ultra Wide X-Band Microwave Imaging of Concealed Weapons and Explosives Using 3D-SAR Technique

    P. Millot

    2015-01-01

    Full Text Available In order to detect and image concealed weapons and explosives, an electromagnetic imaging tool with its related signal processing is presented. The aim is to penetrate clothes and to find personal-born weapons and explosives under clothes. The chosen UWB frequency range covers the whole X-band. The frequency range is justified after transmission measurements of numerous clothes that are dry or slightly wet. The apparatus and the 3D near-field SAR processor are described. A strategy for contour identification is presented with results of some simulants of weapon and explosive. A conclusion is drawn on the possible future of this technique.

  9. Wave directional spectrum from SAR imagery

    Fernandes, A.A.; Sarma, Y.V.B.; Menon, H.B.; Vethamony, P.

    Gaussian smoothed SAR image spectra have been evaluated from 512 x 512 pixel subscenes of image mode ERS-1 SAR scenes off Goa, Visakhapatnam, Paradeep and Portugal. The two recently acquired scenes off Portugal showed the signature of swell...

  10. Exploitation of Amplitude and Phase of Satellite SAR Images for Landslide Mapping: The Case of Montescaglioso (South Italy

    Federico Raspini

    2015-11-01

    Full Text Available Pre- event and event landslide deformations have been detected and measured for the landslide that occurred on 3 December 2013 on the south-western slope of the Montescaglioso village (Basilicata Region, southern Italy. In this paper, ground displacements have been mapped through an integrated analysis based on a series of high resolution SAR (Synthetic Aperture Radar images acquired by the Italian constellation of satellites COSMO-SkyMed. Analysis has been performed by exploiting both phase (through multi-image SAR interferometry and amplitude information (through speckle tracking techniques of the satellite images. SAR Interferometry, applied to images taken before the event, revealed a general pre-event movement, in the order of a few mm/yr, in the south-western slope of the Montescaglioso village. Highest pre-event velocities, ranging between 8 and 12 mm/yr, have been recorded in the sector of the slope where the first movement of the landslide took place. Speckle tracking, applied to images acquired before and after the event, allowed the retrieval of the 3D deformation field produced by the landslide. It also showed that ground displacements produced by the landslide have a dominant SSW component, with values exceeding 10 m for large sectors of the landslide area, with local peaks of 20 m in its central and deposit areas. Two minor landslides with a dominant SSE direction, which were detected in the upper parts of the slope, likely also occurred as secondary phenomena as consequence of the SSW movement of the main Montescaglioso landslide.

  11. Time Series Analysis OF SAR Image Fractal Maps: The Somma-Vesuvio Volcanic Complex Case Study

    Pepe, Antonio; De Luca, Claudio; Di Martino, Gerardo; Iodice, Antonio; Manzo, Mariarosaria; Pepe, Susi; Riccio, Daniele; Ruello, Giuseppe; Sansosti, Eugenio; Zinno, Ivana

    2016-04-01

    The fractal dimension is a significant geophysical parameter describing natural surfaces representing the distribution of the roughness over different spatial scale; in case of volcanic structures, it has been related to the specific nature of materials and to the effects of active geodynamic processes. In this work, we present the analysis of the temporal behavior of the fractal dimension estimates generated from multi-pass SAR images relevant to the Somma-Vesuvio volcanic complex (South Italy). To this aim, we consider a Cosmo-SkyMed data-set of 42 stripmap images acquired from ascending orbits between October 2009 and December 2012. Starting from these images, we generate a three-dimensional stack composed by the corresponding fractal maps (ordered according to the acquisition dates), after a proper co-registration. The time-series of the pixel-by-pixel estimated fractal dimension values show that, over invariant natural areas, the fractal dimension values do not reveal significant changes; on the contrary, over urban areas, it correctly assumes values outside the natural surfaces fractality range and show strong fluctuations. As a final result of our analysis, we generate a fractal map that includes only the areas where the fractal dimension is considered reliable and stable (i.e., whose standard deviation computed over the time series is reasonably small). The so-obtained fractal dimension map is then used to identify areas that are homogeneous from a fractal viewpoint. Indeed, the analysis of this map reveals the presence of two distinctive landscape units corresponding to the Mt. Vesuvio and Gran Cono. The comparison with the (simplified) geological map clearly shows the presence in these two areas of volcanic products of different age. The presented fractal dimension map analysis demonstrates the ability to get a figure about the evolution degree of the monitored volcanic edifice and can be profitably extended in the future to other volcanic systems with

  12. A typical MR imaging of multiple sclerosis

    Katagiri, Shinako; Kan, Shinichi; Ikeda, Toshiaki; Nishiyama, Syougo; Nishimaki, Hiroshi; Matsubayashi, Takashi; Hata, Takashi [Kitasato Univ., Sagamihara, Kanagawa (Japan). School of Medicine

    1995-06-01

    MR imaging is very useful in detecting the intracranial lesion of multiple sclerosis (MS). We present six patients of MS with atypical MR imaging findings. Six patients aged 27-56 years (mean 36 years), and sexuality of six patients were 2 men and 4 females. Three patient`s clinical course had episodes of optic neuritis. The plaque`s size of the predominant lesion of the patients ranged from 3.0 to 9.0 cm in diameter. The plaques were oval, elliptically and other shaped. At acute stage, MR imaging detected perfocal edema and focal mass effect in three cases of our study. Two out of six cases showed multiple irregularly enhancing lesion with Gadolinium-DTPA. Plaques of all cases did not disappear completely in final MR imaging study. (author).

  13. A typical MR imaging of multiple sclerosis

    Katagiri, Shinako; Kan, Shinichi; Ikeda, Toshiaki; Nishiyama, Syougo; Nishimaki, Hiroshi; Matsubayashi, Takashi; Hata, Takashi

    1995-01-01

    MR imaging is very useful in detecting the intracranial lesion of multiple sclerosis (MS). We present six patients of MS with atypical MR imaging findings. Six patients aged 27-56 years (mean 36 years), and sexuality of six patients were 2 men and 4 females. Three patient's clinical course had episodes of optic neuritis. The plaque's size of the predominant lesion of the patients ranged from 3.0 to 9.0 cm in diameter. The plaques were oval, elliptically and other shaped. At acute stage, MR imaging detected perfocal edema and focal mass effect in three cases of our study. Two out of six cases showed multiple irregularly enhancing lesion with Gadolinium-DTPA. Plaques of all cases did not disappear completely in final MR imaging study. (author)

  14. Attenuation of multiples in image space

    Alvarez, Gabriel F.

    In complex subsurface areas, attenuation of 3D specular and diffracted multiples in data space is difficult and inaccurate. In those areas, image space is an attractive alternative. There are several reasons: (1) migration increases the signal-to-noise ratio of the data; (2) primaries are mapped to coherent events in Subsurface Offset Domain Common Image Gathers (SODCIGs) or Angle Domain Common Image Gathers (ADCIGs); (3) image space is regular and smaller; (4) attenuating the multiples in data space leaves holes in the frequency-Wavenumber space that generate artifacts after migration. I develop a new equation for the residual moveout of specular multiples in ADCIGs and use it for the kernel of an apex-shifted Radon transform to focus and separate the primaries from specular and diffracted multiples. Because of small amplitude, phase and kinematic errors in the multiple estimate, we need adaptive matching and subtraction to estimate the primaries. I pose this problem as an iterative least-squares inversion that simultaneously matches the estimates of primaries and multiples to the data. Standard methods match only the estimate of the multiples. I demonstrate with real and synthetic data that the method produces primaries and multiples with little cross-talk. In 3D, the multiples exhibit residual moveout in SODCIGs in in-line and cross-line offsets. They map away from zero subsurface offsets when migrated with the faster velocity of the primaries. In ADCIGs the residual moveout of the primaries as a function of the aperture angle, for a given azimuth, is flat for those angles that illuminate the reflector. The multiples have residual moveout towards increasing depth for increasing aperture angles at all azimuths. As a function of azimuth, the primaries have better azimuth resolution than the multiples at larger aperture angles. I show, with a real 3D dataset, that even below salt, where illumination is poor, the multiples are well attenuated in ADCIGs with the new

  15. Free Surface Downgoing VSP Multiple Imaging

    Maula, Fahdi; Dac, Nguyen

    2018-03-01

    The common usage of a vertical seismic profile is to capture the reflection wavefield (upgoing wavefield) so that it can be used for further well tie or other interpretations. Borehole Seismic (VSP) receivers capture the reflection from below the well trajectory, traditionally no seismic image information above trajectory. The non-traditional way of processing the VSP multiple can be used to expand the imaging above the well trajectory. This paper presents the case study of using VSP downgoing multiples for further non-traditional imaging applications. In general, VSP processing, upgoing and downgoing arrivals are separated during processing. The up-going wavefield is used for subsurface illumination, whereas the downgoing wavefield and multiples are normally excluded from the processing. In a situation where the downgoing wavefield passes the reflectors several times (multiple), the downgoing wavefield carries reflection information. Its benefit is that it can be used for seismic tie up to seabed, and possibility for shallow hazards identifications. One of the concepts of downgoing imaging is widely known as mirror-imaging technique. This paper presents a case study from deep water offshore Vietnam. The case study is presented to demonstrate the robustness of the technique, and the limitations encountered during its processing.

  16. A SAR-ADC using unit bridge capacitor and with calibration for the front-end electronics of PET imaging

    Liu, Wei [School of Computer Science and Engineering, Northwestern Polytechnical University, Xi' an 710072, Shaanxi (China); Wei, Tingcun, E-mail: weitc@nwpu.edu.cn [School of Computer Science and Engineering, Northwestern Polytechnical University, Xi' an 710072, Shaanxi (China); Li, Bo; Yang, Lifeng; Xue, Feifei [School of Computer Science and Engineering, Northwestern Polytechnical University, Xi' an 710072, Shaanxi (China); Hu, Yongcai [Institut Pluridisciplinaire Hubert CURIEN, Strasbourg (France)

    2016-05-11

    This paper presents a 12-bit 1 MS/s successive approximation register-analog to digital converter (SAR-ADC) for the 32-channel front-end electronics of CZT-based PET imaging system. To reduce the capacitance mismatch, instead of the fractional capacitor, the unit capacitor is used as the bridge capacitor in the split-capacitor digital to analog converter (DAC) circuit. In addition, in order to eliminate the periodical DNL errors of −1 LSB which often exists in the SAR-ADC using the charge-redistributed DAC, a calibration algorithm is proposed and verified by the experiments. The proposed 12-bit 1 MS/s SAR-ADC is designed and implemented using a 0.35 μm CMOS technology, it occupies only an active area of 986×956 μm{sup 2}. The measurement results show that, at the power supply of 3.3/5.0 V and the sampling rate of 1 MS/s, the ADC with calibration has a signal-to-noise-and-distortion ratio (SINAD) of 67.98 dB, the power dissipation of 5 mW, and a figure of merit (FOM) of 2.44 pJ/conv.-step. This ADC is with the features of high accuracy, low power and small layout area, it is especially suitable to the one-chip integration of the front-end readout electronics.

  17. Using SAR images to delineate ocean oil slicks with a texture-classifying neural network algorithm (TCNNA)

    Garcia-Pineda, O.; MacDonald, I.R. [Florida State Univ., Tallahassee, FL (United States). Dept. of Oceanography; Zimmer, B. [Texas A and M Univ., Corpus Christi, TX (United States). Dept. of Mathematics and Statistics; Howard, M. [Texas A and M Univ., College Station, TX (United States). Dept. of Oceanography; Pichel, W. [National Oceanic and Atmospheric Administration, Camp Springs, MD (United States). Center for Satellite Applications and Research, National Environmental Satellite, Data and Information Service; Li, X. [National Oceanic and Atmospheric Administration, Camp Springs, MD (United States). Systems Group, National Environmental Satellite, Data and Information

    2009-10-15

    Synthetic aperture radar (SAR) is used to detect surfactant layers produced by floating oil on the ocean surface. This study presented details of a texture-classifying neural network algorithm (TCNNA) designed to process SAR data from a wide selection of beam modes. Patterns from SAR imagery were extracted in a semi-supervised procedure using a combination of edge-detection filters; texture descriptors; collection information; and environmental data. Various natural oil seeps in the Gulf of Mexico were used as case studies. An analysis of the case studies demonstrated that the TCNNA was able to extract targets and rapidly interpret images collected under a range of environmental conditions. Results presented by the TCNNA were used to evaluate the effects of different environmental conditions on the expressions of oil slicks detected by the data. Optimal incidence angle ranges and wind speed ranges for surfactant film detection were also presented. Results obtained by the TCNNA can be stored and manipulated in geographic information system (GIS) data layers. 26 refs., 1 tab., 7 figs.

  18. Interesting images: Multiple coronary artery aneurysms.

    Howard, Jonathon M; Viswanath, Omar; Armas, Alfredo; Santana, Orlando; Rosen, Gerald P

    2017-01-01

    We present the case of a 65-year-old male who presented with stable angina and dyspnea on exertion. His initial workup yielded a positive treadmill stress test for reversible apical ischemia, and transthoracic echocardiogram demonstrated impaired systolic function. Cardiac catheterization was then performed, revealing severe atherosclerotic disease including multiple coronary artery aneurysms. As a result, the patient was advised to and subsequently underwent a coronary artery bypass graft. This case highlights the presence of multiple coronary artery aneurysms and the ability to appreciate these pathologic findings on multiple imaging modalities, including coronary angiogram, transesophageal echocardiography, and direct visualization through the surgical field.

  19. MULTI-TEMPORAL SAR INTERFEROMETRY FOR LANDSLIDE MONITORING

    R. Dwivedi

    2016-06-01

    Full Text Available In the past few years, SAR Interferometry specially InSAR and D-InSAR were extensively used for deformation monitoring related applications. Due to temporal and spatial decorrelation in dense vegetated areas, effectiveness of InSAR and D-InSAR observations were always under scrutiny. Multi-temporal InSAR methods are developed in recent times to retrieve the deformation signal from pixels with different scattering characteristics. Presently, two classes of multi-temporal InSAR algorithms are available- Persistent Scatterer (PS and Small Baseline (SB methods. This paper discusses the Stanford Method for Persistent Scatterer (StaMPS based PS-InSAR and the Small Baselines Subset (SBAS techniques to estimate the surface deformation in Tehri dam reservoir region in Uttarkhand, India. Both PS-InSAR and SBAS approaches used sixteen ENVISAT ASAR C-Band images for generating single master and multiple master interferograms stack respectively and their StaMPS processing resulted in time series 1D-Line of Sight (LOS mean velocity maps which are indicative of deformation in terms of movement towards and away from the satellites. From 1D LOS velocity maps, localization of landslide is evident along the reservoir rim area which was also investigated in the previous studies. Both PS-InSAR and SBAS effectively extract measurement pixels in the study region, and the general results provided by both approaches show a similar deformation pattern along the Tehri reservoir region. Further, we conclude that StaMPS based PS-InSAR method performs better in terms of extracting more number of measurement pixels and in the estimation of mean Line of Sight (LOS velocity as compared to SBAS method. It is also proposed to take up a few major landslides area in Uttarakhand for slope stability assessment.

  20. An Adaptive Moving Target Imaging Method for Bistatic Forward-Looking SAR Using Keystone Transform and Optimization NLCS.

    Li, Zhongyu; Wu, Junjie; Huang, Yulin; Yang, Haiguang; Yang, Jianyu

    2017-01-23

    Bistatic forward-looking SAR (BFSAR) is a kind of bistatic synthetic aperture radar (SAR) system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I) large and unknown range cell migration (RCM) (including range walk and high-order RCM); (II) the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler) are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS) technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method.

  1. An Adaptive Moving Target Imaging Method for Bistatic Forward-Looking SAR Using Keystone Transform and Optimization NLCS

    Zhongyu Li

    2017-01-01

    Full Text Available Bistatic forward-looking SAR (BFSAR is a kind of bistatic synthetic aperture radar (SAR system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I large and unknown range cell migration (RCM (including range walk and high-order RCM; (II the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method.

  2. High Dynamic Range Imaging Using Multiple Exposures

    Hou, Xinglin; Luo, Haibo; Zhou, Peipei; Zhou, Wei

    2017-06-01

    It is challenging to capture a high-dynamic range (HDR) scene using a low-dynamic range (LDR) camera. This paper presents an approach for improving the dynamic range of cameras by using multiple exposure images of same scene taken under different exposure times. First, the camera response function (CRF) is recovered by solving a high-order polynomial in which only the ratios of the exposures are used. Then, the HDR radiance image is reconstructed by weighted summation of the each radiance maps. After that, a novel local tone mapping (TM) operator is proposed for the display of the HDR radiance image. By solving the high-order polynomial, the CRF can be recovered quickly and easily. Taken the local image feature and characteristic of histogram statics into consideration, the proposed TM operator could preserve the local details efficiently. Experimental result demonstrates the effectiveness of our method. By comparison, the method outperforms other methods in terms of imaging quality.

  3. The Temporal and Spatial Variability of the Confined Aquifer Head and Storage Properties in the San Luis Valley, Colorado Inferred From Multiple InSAR Missions

    Chen, Jingyi; Knight, Rosemary; Zebker, Howard A.

    2017-11-01

    Interferometric Synthetic Aperture Radar (InSAR) data from multiple satellite missions were combined to study the temporal and spatial variability of head and storage properties in a confined aquifer system on a decadal time scale. The area of study was a 4,500 km2 agricultural basin in the San Luis Valley (SLV), Colorado. We had available previous analyses of C-band ERS-1/2 data from June 1992 to November 2000, and L-band ALOS PALSAR data from October 2009 to March 2011. We used C-band Envisat data to fill in the time period from November 2006 to July 2010. In processing the Envisat data, we successfully employed a phase interpolation between persistent scatterer pixels to reduce the impact of vegetation decorrelation, which can significantly reduce the quality of C-band InSAR data over agricultural basins. In comparing the results from the L-band ALOS data and C-band Envisat data in a 10 month overlapping time period, we found that the shorter wavelength of C-band InSAR allowed us to preserve small deformation signals that were not detectable using L-band ALOS data. A significant result was the finding that the elastic storage properties of the SLV confined aquifer system remained stable over the 20 year time period and vary slowly in space, allowing us to combine InSAR data acquired from multiple missions to fill the temporal and spatial gaps in well data. The InSAR estimated head levels were validated with well measurements, which indicate little permanent water-storage loss over the study time period in the SLV.

  4. The retrieval of two-dimensional distribution of the earth's surface aerodynamic roughness using SAR image and TM thermal infrared image

    ZHANG; Renhua; WANG; Jinfeng; ZHU; Caiying; SUN; Xiaomin

    2004-01-01

    After having analyzed the requirement on the aerodynamic earth's surface roughness in two-dimensional distribution in the research field of interaction between land surface and atmosphere, this paper presents a new way to calculate the aerodynamic roughness using the earth's surface geometric roughness retrieved from SAR (Synthetic Aperture Radar) and TM thermal infrared image data. On the one hand, the SPM (Small Perturbation Model) was used as a theoretical SAR backscattering model to describe the relationship between the SAR backscattering coefficient and the earth's surface geometric roughness and its dielectric constant retrieved from the physical model between the soil thermal inertia and the soil surface moisture with the simultaneous TM thermal infrared image data and the ground microclimate data. On the basis of the SAR image matching with the TM image, the non-volume scattering surface geometric information was obtained from the SPM model at the TM image pixel scale, and the ground pixel surface's equivalent geometric roughness-height standard RMS (Root Mean Square) was achieved from the geometric information by the transformation of the typical topographic factors. The vegetation (wheat, tree) height retrieved from spectrum model was also transferred into its equivalent geometric roughness. A completely two-dimensional distribution map of the equivalent geometric roughness over the experimental area was produced by the data mosaic technique. On the other hand, according to the atmospheric eddy currents theory, the aerodynamic surface roughness was iterated out with the atmosphere stability correction method using the wind and the temperature profiles data measured at several typical fields such as bare soil field and vegetation field. After having analyzed the effect of surface equivalent geometric roughness together with dynamic and thermodynamic factors on the aerodynamic surface roughness within the working area, this paper first establishes a scale

  5. Assessment of radargrammetric DSMs from TerraSAR-X Stripmap images in a mountainous relief area of the Amazon region

    de Oliveira, Cleber Gonzales; Paradella, Waldir Renato; da Silva, Arnaldo de Queiroz

    The Brazilian Amazon is a vast territory with an enormous need for mapping and monitoring of renewable and non-renewable resources. Due to the adverse environmental condition (rain, cloud, dense vegetation) and difficult access, topographic information is still poor, and when available needs to be updated or re-mapped. In this paper, the feasibility of using Digital Surface Models (DSMs) extracted from TerraSAR-X Stripmap stereo-pair images for detailed topographic mapping was investigated for a mountainous area in the Carajás Mineral Province, located on the easternmost border of the Brazilian Amazon. The quality of the radargrammetric DSMs was evaluated regarding field altimetric measurements. Precise topographic field information acquired from a Global Positioning System (GPS) was used as Ground Control Points (GCPs) for the modeling of the stereoscopic DSMs and as Independent Check Points (ICPs) for the calculation of elevation accuracies. The analysis was performed following two ways: (1) the use of Root Mean Square Error (RMSE) and (2) calculations of systematic error (bias) and precision. The test for significant systematic error was based on the Student's-t distribution and the test of precision was based on the Chi-squared distribution. The investigation has shown that the accuracy of the TerraSAR-X Stripmap DSMs met the requirements for 1:50,000 map (Class A) as requested by the Brazilian Standard for Cartographic Accuracy. Thus, the use of TerraSAR-X Stripmap images can be considered a promising alternative for detailed topographic mapping in similar environments of the Amazon region, where available topographic information is rare or presents low quality.

  6. Power Transmission Tower Series Extraction in PolSAR Image Based on Time-Frequency Analysis and A-Contrario Theory

    Dongqing Peng

    2016-11-01

    Full Text Available Based on Time-Frequency (TF analysis and a-contrario theory, this paper presents a new approach for extraction of linear arranged power transmission tower series in Polarimetric Synthetic Aperture Radar (PolSAR images. Firstly, the PolSAR multidimensional information is analyzed using a linear TF decomposition approach. The stationarity of each pixel is assessed by testing the maximum likelihood ratio statistics of the coherency matrix. Then, based on the maximum likelihood log-ratio image, a Cell-Averaging Constant False Alarm Rate (CA-CFAR detector with Weibull clutter background and a post-processing operator is used to detect point-like targets in the image. Finally, a searching approach based on a-contrario theory is applied to extract the linear arranged targets from detected point-like targets. The experimental results on three sets of PolSAR data verify the effectiveness of this approach.

  7. Different scale land subsidence and ground fissure monitoring with multiple InSAR techniques over Fenwei basin, China

    C. Zhao

    2015-11-01

    Full Text Available Fenwei basin, China, composed by several sub-basins, has been suffering severe geo-hazards in last 60 years, including large scale land subsidence and small scale ground fissure, which caused serious infrastructure damages and property losses. In this paper, we apply different InSAR techniques with different SAR data to monitor these hazards. Firstly, combined small baseline subset (SBAS InSAR method and persistent scatterers (PS InSAR method is used to multi-track Envisat ASAR data to retrieve the large scale land subsidence covering entire Fenwei basin, from which different land subsidence magnitudes are analyzed of different sub-basins. Secondly, PS-InSAR method is used to monitor the small scale ground fissure deformation in Yuncheng basin, where different spatial deformation gradient can be clearly discovered. Lastly, different track SAR data are contributed to retrieve two-dimensional deformation in both land subsidence and ground fissure region, Xi'an, China, which can be benefitial to explain the occurrence of ground fissure and the correlation between land subsidence and ground fissure.

  8. SIMULATION-BASED EVALUATION OF LIGHT POSTS AND STREET SIGNS AS 3-D GEOLOCATION TARGETS IN SAR IMAGES

    S. Auer

    2017-05-01

    Full Text Available The assignment of phase center positions (in 2D or 3D derived from SAR data to physical object is challenging for many man-made structures such as buildings or bridges. In contrast, light poles and traffic signs are promising targets for tasks based on 3-D geolocation as they often show a prominent and spatially isolated appearance. For a detailed understanding of the nature of both targets, this paper presents results of a dedicated simulation case study, which is based on ray tracing methods (simulator RaySAR. For the first time, the appearance of the targets is analyzed in 2D (image plane and 3D space (world coordinates of scene model and reflecting surfaces are identified for related dominant image pixels. The case studies confirms the crucial impact of spatial resolution in the context of light poles and traffic signs and the appropriateness of light poles as target for 3-D geolocation in case of horizontal ground surfaces beneath.

  9. Estimation of the Above Ground Biomass of Tropical Forests using Polarimetric and Tomographic SAR Data Acquired at P Band and 3-D Imaging Techniques

    Ferro-Famil, L.; El Hajj Chehade, B.; Ho Tong Minh, D.; Tebaldini, S.; LE Toan, T.

    2016-12-01

    Developing and improving methods to monitor forest biomass in space and time is a timely challenge, especially for tropical forests, for which SAR imaging at larger wavelength presents an interesting potential. Nevertheless, directly estimating tropical forest biomass from classical 2-D SAR images may reveal a very complex and ill-conditioned problem, since a SAR echo is composed of numerous contributions, whose features and importance depend on many geophysical parameters, such has ground humidity, roughness, topography… that are not related to biomass. Recent studies showed that SAR modes of diversity, i.e. polarimetric intensity ratios or interferometric phase centers, do not fully resolve this under-determined problem, whereas Pol-InSAR tree height estimates may be related to biomass through allometric relationships, with, in general over tropical forests, significant levels of uncertainty and lack of robustness. In this context, 3-D imaging using SAR tomography represents an appealing solution at larger wavelengths, for which wave penetration properties ensures a high quality mapping of a tropical forest reflectivity in the vertical direction. This paper presents a series of studies led, in the frame of the preparation of the next ESA mission BIOMASS, on the estimation of biomass over a tropical forest in French Guiana, using Polarimetric SAR Tomographic (Pol-TomSAR) data acquired at P band by ONERA. It is then shown that Pol-TomoSAR significantly improves the retrieval of forest above ground biomass (AGB) in a high biomass forest (200 up to 500 t/ha), with an error of only 10% at 1.5-ha resolution using a reflectivity estimates sampled at a predetermined elevation. The robustness of this technique is tested by applying the same approach over another site, and results show a similar relationship between AGB and tomographic reflectivity over both sites. The excellent ability of Pol-TomSAR to retrieve both canopy top heights and ground topography with an error

  10. Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging.

    Yi, Tianzhu; He, Zhihua; He, Feng; Dong, Zhen; Wu, Manqing

    2017-11-07

    This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR) data processing. Several nonlinear chirp scaling (NLCS) algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC). However, the azimuth depth of focusing (ADOF) is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS) algorithm that is proposed in this paper uses the method of series reverse (MSR) to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data.

  11. Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging

    Tianzhu Yi

    2017-11-01

    Full Text Available This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR data processing. Several nonlinear chirp scaling (NLCS algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC. However, the azimuth depth of focusing (ADOF is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS algorithm that is proposed in this paper uses the method of series reverse (MSR to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data.

  12. A Methodology to Detect and Update Active Deformation Areas Based on Sentinel-1 SAR Images

    Anna Barra

    2017-09-01

    Full Text Available This work is focused on deformation activity mapping and monitoring using Sentinel-1 (S-1 data and the DInSAR (Differential Interferometric Synthetic Aperture Radar technique. The main goal is to present a procedure to periodically update and assess the geohazard activity (volcanic activity, landslides and ground-subsidence of a given area by exploiting the wide area coverage and the high coherence and temporal sampling (revisit time up to six days provided by the S-1 satellites. The main products of the procedure are two updatable maps: the deformation activity map and the active deformation areas map. These maps present two different levels of information aimed at different levels of geohazard risk management, from a very simplified level of information to the classical deformation map based on SAR interferometry. The methodology has been successfully applied to La Gomera, Tenerife and Gran Canaria Islands (Canary Island archipelago. The main obtained results are discussed.

  13. Analysis of the fractal dimension of volcano geomorphology through Synthetic Aperture Radar (SAR) amplitude images acquired in C and X band.

    Pepe, S.; Di Martino, G.; Iodice, A.; Manzo, M.; Pepe, A.; Riccio, D.; Ruello, G.; Sansosti, E.; Tizzani, P.; Zinno, I.

    2012-04-01

    In the last two decades several aspects relevant to volcanic activity have been analyzed in terms of fractal parameters that effectively describe natural objects geometry. More specifically, these researches have been aimed at the identification of (1) the power laws that governed the magma fragmentation processes, (2) the energy of explosive eruptions, and (3) the distribution of the associated earthquakes. In this paper, the study of volcano morphology via satellite images is dealt with; in particular, we use the complete forward model developed by some of the authors (Di Martino et al., 2012) that links the stochastic characterization of amplitude Synthetic Aperture Radar (SAR) images to the fractal dimension of the imaged surfaces, modelled via fractional Brownian motion (fBm) processes. Based on the inversion of such a model, a SAR image post-processing has been implemented (Di Martino et al., 2010), that allows retrieving the fractal dimension of the observed surfaces, dictating the distribution of the roughness over different spatial scales. The fractal dimension of volcanic structures has been related to the specific nature of materials and to the effects of active geodynamic processes. Hence, the possibility to estimate the fractal dimension from a single amplitude-only SAR image is of fundamental importance for the characterization of volcano structures and, moreover, can be very helpful for monitoring and crisis management activities in case of eruptions and other similar natural hazards. The implemented SAR image processing performs the extraction of the point-by-point fractal dimension of the scene observed by the sensor, providing - as an output product - the map of the fractal dimension of the area of interest. In this work, such an analysis is performed on Cosmo-SkyMed, ERS-1/2 and ENVISAT images relevant to active stratovolcanoes in different geodynamic contexts, such as Mt. Somma-Vesuvio, Mt. Etna, Vulcano and Stromboli in Southern Italy, Shinmoe

  14. Lagrangian-based Backtracking of Oil Spill Dynamics from SAR Images: Application to Montara Case

    Gautama, Budhi Gunadharma; Mercier, Gregoire; Fablet, Ronan; Longepe, Nicolas

    2016-08-01

    Within the framework of INDESO project (Infrastructure Development Space Oceanography), we address the issue of oilspill and aim at developing an operational SAR- based system for monitoring this issue in Indonesian waters from space. In this work, we focus on the backtrack- ing of an oilspill detected from SAR observations. As a case-study, we consider one large oil spill event that happened in Indonesian waters in 2009, referred to as the Montara oilspill. On 21 August 2009, the Montara Wellhead Platform had an uncontrolled release of hydrocarbons from one of the platform wells. It was estimated that 400 barrels (or approximately 64 tonnes) of crude oil were being lost per day. The uncontrolled release continued until 3 November 2009 and response operations continued until 3 December 2009. In this work, we develop a Langragian analysis and associated numerical inversion tools with a view to further analyzing the oil spread due to the Montara Wellhead Platform. Our model relies on a 2D Lagrangian transport model developed by CLS (Collecte Localisation Satellite). Our model involves four main parameters : the weights of wind- related and current-related advection, the origin and the duration of the oil leakage. Given SAR oilspill detections, we propose a numerical inversion of the parameters of the Lagrangian model, so that the simulated drift match the SAR observations of the oil spill. We demonstrate the relevance of the proposed model and numerical scheme for the Montara oilspill and further discuss their operational interest for the space-based oilspill backtracking and forecasting.

  15. A new scheme for urban impervious surface classification from SAR images

    Zhang, Hongsheng; Lin, Hui; Wang, Yunpeng

    2018-05-01

    Urban impervious surfaces have been recognized as a significant indicator for various environmental and socio-economic studies. There is an increasingly urgent demand for timely and accurate monitoring of the impervious surfaces with satellite technology from local to global scales. In the past decades, optical remote sensing has been widely employed for this task with various techniques. However, there are still a range of challenges, e.g. handling cloud contamination on optical data. Therefore, the Synthetic Aperture Radar (SAR) was introduced for the challenging task because it is uniquely all-time- and all-weather-capable. Nevertheless, with an increasing number of SAR data applied, the methodology used for impervious surfaces classification remains unchanged from the methods used for optical datasets. This shortcoming has prevented the community from fully exploring the potential of using SAR data for impervious surfaces classification. We proposed a new scheme that is comparable to the well-known and fundamental Vegetation-Impervious surface-Soil (V-I-S) model for mapping urban impervious surfaces. Three scenes of fully polarimetric Radsarsat-2 data for the cities of Shenzhen, Hong Kong and Macau were employed to test and validate the proposed methodology. Experimental results indicated that the overall accuracy and Kappa coefficient were 96.00% and 0.8808 in Shenzhen, 93.87% and 0.8307 in Hong Kong and 97.48% and 0.9354 in Macau, indicating the applicability and great potential of the new scheme for impervious surfaces classification using polarimetric SAR data. Comparison with the traditional scheme indicated that this new scheme was able to improve the overall accuracy by up to 4.6% and Kappa coefficient by up to 0.18.

  16. Novel Polarimetric SAR Interferometry Algorithms, Phase I

    National Aeronautics and Space Administration — Polarimetric radar interferometry (PolInSAR) is a new SAR imaging mode that is rapidly becoming an important technique for bare earth topographic mapping, tree...

  17. Magnetic resonance imaging in multiple sclerosis

    Kesselring, J.; Ormerod, I.E.C.; Miller, D.H.; Du Boulay, G.H.; McDonald, W.I.

    1989-01-01

    In 1983 the Multiple Sclerosis Society of Great Britain and Northern Ireland set up the Multiple Sclerosis NMR Research Group at the Institute of Neurology and the National Hospital, Queen Square. The first aim of the Group was to define the role of MRI in the diagnosis and differential diagnosis of multiple sclerosis, and this Atlas represents a summary of that work. Our strategy was to determine the pattern of MRI abnormalities in clinically definite MS and to compare it with those of isolated clinical syndromes of the kind seen in MS (e.g. optic neuritis) and of other disorders with which MS can be confused clinically or radiologically. We have also been involved in a major program of experimental work designed to elucidate the origin of the abnormal signals in MRI. To describe this in full detail would go beyond the scope of the Atlas, but we have incorporated such results as far as they illuminate our clinical problems. The imager used was a 0.5 Tesla Picker superconducting system. Technical advances have been rapid since we began. Nevertheless, the quality of the images obtained at our relatively low field has enabled us to establish the patterns of abnormality in the brain in MS and the diseases which must be distinguished from it. (orig./MG)

  18. Remote Sensing Image Registration Using Multiple Image Features

    Kun Yang

    2017-06-01

    Full Text Available Remote sensing image registration plays an important role in military and civilian fields, such as natural disaster damage assessment, military damage assessment and ground targets identification, etc. However, due to the ground relief variations and imaging viewpoint changes, non-rigid geometric distortion occurs between remote sensing images with different viewpoint, which further increases the difficulty of remote sensing image registration. To address the problem, we propose a multi-viewpoint remote sensing image registration method which contains the following contributions. (i A multiple features based finite mixture model is constructed for dealing with different types of image features. (ii Three features are combined and substituted into the mixture model to form a feature complementation, i.e., the Euclidean distance and shape context are used to measure the similarity of geometric structure, and the SIFT (scale-invariant feature transform distance which is endowed with the intensity information is used to measure the scale space extrema. (iii To prevent the ill-posed problem, a geometric constraint term is introduced into the L2E-based energy function for better behaving the non-rigid transformation. We evaluated the performances of the proposed method by three series of remote sensing images obtained from the unmanned aerial vehicle (UAV and Google Earth, and compared with five state-of-the-art methods where our method shows the best alignments in most cases.

  19. Benefits and limitations of imaging multiples: Mirror migration

    Hanafy, Sherif M.; Huang, Yunsong; Schuster, Gerard T.

    2015-01-01

    The benefits and limitations of imaging multiples are reviewed for mirror migration. Synthetic and field data examples are used to characterize the effectiveness of migrating multiples relative to primary imaging.

  20. Benefits and limitations of imaging multiples: Mirror migration

    Hanafy, Sherif M.

    2015-07-01

    The benefits and limitations of imaging multiples are reviewed for mirror migration. Synthetic and field data examples are used to characterize the effectiveness of migrating multiples relative to primary imaging.

  1. Feature-Based Nonlocal Polarimetric SAR Filtering

    Xiaoli Xing

    2017-10-01

    Full Text Available Polarimetric synthetic aperture radar (PolSAR images are inherently contaminated by multiplicative speckle noise, which complicates the image interpretation and image analyses. To reduce the speckle effect, several adaptive speckle filters have been developed based on the weighted average of the similarity measures commonly depending on the model or probability distribution, which are often affected by the distribution parameters and modeling texture components. In this paper, a novel filtering method introduces the coefficient of variance ( CV and Pauli basis (PB to measure the similarity, and the two features are combined with the framework of the nonlocal mean filtering. The CV is used to describe the complexity of various scenes and distinguish the scene heterogeneity; moreover, the Pauli basis is able to express the polarimetric information in PolSAR image processing. This proposed filtering combines the CV and Pauli basis to improve the estimation accuracy of the similarity weights. Then, the similarity of the features is deduced according to the test statistic. Subsequently, the filtering is proceeded by using the nonlocal weighted estimation. The performance of the proposed filter is tested with the simulated images and real PolSAR images, which are acquired by AIRSAR system and ESAR system. The qualitative and quantitative experiments indicate the validity of the proposed method by comparing with the widely-used despeckling methods.

  2. Which Fault Segments Ruptured in the 2008 Wenchuan Earthquake and Which Did Not? New Evidence from Near‐Fault 3D Surface Displacements Derived from SAR Image Offsets

    Feng, Guangcai; Jonsson, Sigurjon; Klinger, Yann

    2017-01-01

    The 2008 Mw 7.9 Wenchuan earthquake ruptured a complex thrust‐faulting system at the eastern edge of the Tibetan plateau and west of Sichuan basin. Though the earthquake has been extensively studied, several details about the earthquake, such as which fault segments were activated in the earthquake, are still not clear. This is in part due to difficult field access to the fault zone and in part due to limited near‐fault observations in Interferometric Synthetic Aperture Radar (InSAR) observations because of decorrelation. In this study, we address this problem by estimating SAR image offsets that provide near‐fault ground displacement information and exhibit clear displacement discontinuities across activated fault segments. We begin by reanalyzing the coseismic InSAR observations of the earthquake and then mostly eliminate the strong ionospheric signals that were plaguing previous studies by using additional postevent images. We also estimate the SAR image offsets and use their results to retrieve the full 3D coseismic surface displacement field. The coseismic deformation from the InSAR and image‐offset measurements are compared with both Global Positioning System and field observations. The results indicate that our observations provide significantly better information than previous InSAR studies that were affected by ionospheric disturbances. We use the results to present details of the surface‐faulting offsets along the Beichuan fault from the southwest to the northeast and find that there is an obvious right‐lateral strike‐slip component (as well as thrust faulting) along the southern Beichuan fault (in Yingxiu County), which was strongly underestimated in earlier studies. Based on the results, we provide new evidence to show that the Qingchuan fault was not ruptured in the 2008 Wenchuan earthquake, a topic debated in field observation studies, but show instead that surface faulting occurred on a northward extension of the Beichuan fault during

  3. Which Fault Segments Ruptured in the 2008 Wenchuan Earthquake and Which Did Not? New Evidence from Near‐Fault 3D Surface Displacements Derived from SAR Image Offsets

    Feng, Guangcai

    2017-03-15

    The 2008 Mw 7.9 Wenchuan earthquake ruptured a complex thrust‐faulting system at the eastern edge of the Tibetan plateau and west of Sichuan basin. Though the earthquake has been extensively studied, several details about the earthquake, such as which fault segments were activated in the earthquake, are still not clear. This is in part due to difficult field access to the fault zone and in part due to limited near‐fault observations in Interferometric Synthetic Aperture Radar (InSAR) observations because of decorrelation. In this study, we address this problem by estimating SAR image offsets that provide near‐fault ground displacement information and exhibit clear displacement discontinuities across activated fault segments. We begin by reanalyzing the coseismic InSAR observations of the earthquake and then mostly eliminate the strong ionospheric signals that were plaguing previous studies by using additional postevent images. We also estimate the SAR image offsets and use their results to retrieve the full 3D coseismic surface displacement field. The coseismic deformation from the InSAR and image‐offset measurements are compared with both Global Positioning System and field observations. The results indicate that our observations provide significantly better information than previous InSAR studies that were affected by ionospheric disturbances. We use the results to present details of the surface‐faulting offsets along the Beichuan fault from the southwest to the northeast and find that there is an obvious right‐lateral strike‐slip component (as well as thrust faulting) along the southern Beichuan fault (in Yingxiu County), which was strongly underestimated in earlier studies. Based on the results, we provide new evidence to show that the Qingchuan fault was not ruptured in the 2008 Wenchuan earthquake, a topic debated in field observation studies, but show instead that surface faulting occurred on a northward extension of the Beichuan fault during

  4. 基于MRF的多时相SAR影像非监督变化检测%Unsupervised Change Detection in Multitemporal SAR Images Using MRF Models

    江利明; 廖明生; 张路; 林珲

    2007-01-01

    An unsupervised change-detection method that considers the spatial contextual information in a log-ratio difference image generated from multitemporal SAR images is proposed. A Markov random filed (MRF) model is particularly employed to exploit statistical spatial correlation of intensity levels among neighboring pixels. Under the assumption of the independency of pixels and mixed Gaussian distribution in the log-ratio difference image, a stochastic and iterative EM-MPM change-detection algorithm based on an MRF model is developed. The EM-MPM algorithm is based on a maximiser of posterior marginals (MPM) algorithm for image segmentation and an expectation-maximum (EM) algorithm for parameter estimation in a completely automatic way. The experiment results obtained on multitemporal ERS-2 SAR images show the effectiveness of the proposed method.

  5. SARS - Diagnosis

    SARS - Diagnosis. Mainly by exclusion of known causes of atypical pneumonia; * X ray Chest; * PCR on body fluids- primers defined by WHO centres available from website.-ve result does not exclude SARS. * Sequencing of amplicons; * Viral Cultures – demanding; * Antibody tests.

  6. Imaging Formation Algorithm of the Ground and Space-Borne Hybrid BiSAR Based on Parameters Estimation from Direct Signal

    Qingjun Zhang

    2014-01-01

    Full Text Available This paper proposes a novel image formation algorithm for the bistatic synthetic aperture radar (BiSAR with the configuration of a noncooperative transmitter and a stationary receiver in which the traditional imaging algorithm failed because the necessary imaging parameters cannot be estimated from the limited information from the noncooperative data provider. In the new algorithm, the essential parameters for imaging, such as squint angle, Doppler centroid, and Doppler chirp-rate, will be estimated by full exploration of the recorded direct signal (direct signal is the echo from satellite to stationary receiver directly from the transmitter. The Doppler chirp-rate is retrieved by modeling the peak phase of direct signal as a quadratic polynomial. The Doppler centroid frequency and the squint angle can be derived from the image contrast optimization. Then the range focusing, the range cell migration correction (RCMC, and the azimuth focusing are implemented by secondary range compression (SRC and the range cell migration, respectively. At last, the proposed algorithm is validated by imaging of the BiSAR experiment configured with china YAOGAN 10 SAR as the transmitter and the receiver platform located on a building at a height of 109 m in Jiangsu province. The experiment image with geometric correction shows good accordance with local Google images.

  7. Image Alignment for Multiple Camera High Dynamic Range Microscopy

    Eastwood, Brian S.; Childs, Elisabeth C.

    2012-01-01

    This paper investigates the problem of image alignment for multiple camera high dynamic range (HDR) imaging. HDR imaging combines information from images taken with different exposure settings. Combining information from multiple cameras requires an alignment process that is robust to the intensity differences in the images. HDR applications that use a limited number of component images require an alignment technique that is robust to large exposure differences. We evaluate the suitability fo...

  8. The Advanced Rapid Imaging and Analysis (ARIA) Project: Providing Standard and On-Demand SAR products for Hazard Science and Hazard Response

    Owen, S. E.; Hua, H.; Rosen, P. A.; Agram, P. S.; Webb, F.; Simons, M.; Yun, S. H.; Sacco, G. F.; Liu, Z.; Fielding, E. J.; Lundgren, P.; Moore, A. W.

    2017-12-01

    A new era of geodetic imaging arrived with the launch of the ESA Sentinel-1A/B satellites in 2014 and 2016, and with the 2016 confirmation of the NISAR mission, planned for launch in 2021. These missions assure high quality, freely and openly distributed regularly sampled SAR data into the indefinite future. These unprecedented data sets are a watershed for solid earth sciences as we progress towards the goal of ubiquitous InSAR measurements. We now face the challenge of how to best address the massive volumes of data and intensive processing requirements. Should scientists individually process the same data independently themselves? Should a centralized service provider create standard products that all can use? Are there other approaches to accelerate science that are cost effective and efficient? The Advanced Rapid Imaging and Analysis (ARIA) project, a joint venture co-sponsored by California Institute of Technology (Caltech) and by NASA through the Jet Propulsion Laboratory (JPL), is focused on rapidly generating higher level geodetic imaging products and placing them in the hands of the solid earth science and local, national, and international natural hazard communities by providing science product generation, exploration, and delivery capabilities at an operational level. However, there are challenges in defining the optimal InSAR data products for the solid earth science community. In this presentation, we will present our experience with InSAR users, our lessons learned the advantages of on demand and standard products, and our proposal for the most effective path forward.

  9. Adaptive thresholding algorithm based on SAR images and wind data to segment oil spills along the northwest coast of the Iberian Peninsula

    Mera, David; Cotos, José M.; Varela-Pet, José; Garcia-Pineda, Oscar

    2012-01-01

    Highlights: ► We present an adaptive thresholding algorithm to segment oil spills. ► The segmentation algorithm is based on SAR images and wind field estimations. ► A Database of oil spill confirmations was used for the development of the algorithm. ► Wind field estimations have demonstrated to be useful for filtering look-alikes. ► Parallel programming has been successfully used to minimize processing time. - Abstract: Satellite Synthetic Aperture Radar (SAR) has been established as a useful tool for detecting hydrocarbon spillage on the ocean’s surface. Several surveillance applications have been developed based on this technology. Environmental variables such as wind speed should be taken into account for better SAR image segmentation. This paper presents an adaptive thresholding algorithm for detecting oil spills based on SAR data and a wind field estimation as well as its implementation as a part of a functional prototype. The algorithm was adapted to an important shipping route off the Galician coast (northwest Iberian Peninsula) and was developed on the basis of confirmed oil spills. Image testing revealed 99.93% pixel labelling accuracy. By taking advantage of multi-core processor architecture, the prototype was optimized to get a nearly 30% improvement in processing time.

  10. Rice status and microwave characteristics: Analysis of rice paddy fields at Kojima Bay [Okayama, Japan] using multi-frequency and polarimetric Pi-SAR radar data images

    Ishitsuka, N.; Saito, G.; Ouchi, K.; Davidson, G.; Mohri, K.; Uratsuka, S.

    2003-01-01

    Abstract South-east Asia has a rainy-season at the crop growing period, and it is difficult to observe agricultural land in this season using optical remote sensing. Synthetic Aperture Radar (SAR) can observe the earth's surface without being influenced by of clouds. However, it is less useful for observing agricultural land, because satellite SAR has only one data band. Recently, SAR is able to provide multi band and multi polarimetric data. Pi-SAR, an airborne SAR developed by NASDA and CRL, can provide L and X bands and fully polarimetric data. Rice is the main crop in Asia, and we studied the characteristic microwave scatter on rice paddy fields using Pi-SAR data. Our study area was the rice paddy fields in Kojima reclaimed land in Japan. We had two fully polarimetric data sets from 13 July 1999 and 4 October 2000. First, we processed the color polarimetric composite image. Next we calibrated the phase of each polarimetric data using river area by the Kimura method. After that we performed decomposition analysis and drew polarimetric signatures for understanding the status of rice paddy fields. At the rice planting period, rice paddy fields are filled with water and rice plants are very small. The SAR microwave scatters on water surfaces like a mirror, called 'mirror (or specular) reflection'. This phenomenon makes backscatter a small value at the water-covered area. The image from July is about one month after trans-planting and rice plants are 20-40 cm in height. X-band microwave scatters on the rice surface, but L-band microwave passes through rice bodies and shows mirror refraction on water surfaces. Some strong backscatter occur on rice paddy fields especially VV polarization because of bragg scattering. The fields where bragg scattering returns strong VV scatter because the space between rice stems cause resonation in the L-band wavelength. We can easily understand bragg scatter by using polarimetric data. Using the image from October at

  11. Multiple image x-radiography for functional lung imaging

    Aulakh, G. K.; Mann, A.; Belev, G.; Wiebe, S.; Kuebler, W. M.; Singh, B.; Chapman, D.

    2018-01-01

    Detection and visualization of lung tissue structures is impaired by predominance of air. However, by using synchrotron x-rays, refraction of x-rays at the interface of tissue and air can be utilized to generate contrast which may in turn enable quantification of lung optical properties. We utilized multiple image radiography, a variant of diffraction enhanced imaging, at the Canadian light source to quantify changes in unique x-ray optical properties of lungs, namely attenuation, refraction and ultra small-angle scatter (USAXS or width) contrast ratios as a function of lung orientation in free-breathing or respiratory-gated mice before and after intra-nasal bacterial endotoxin (lipopolysaccharide) instillation. The lung ultra small-angle scatter and attenuation contrast ratios were significantly higher 9 h post lipopolysaccharide instillation compared to saline treatment whereas the refraction contrast decreased in magnitude. In ventilated mice, end-expiratory pressures result in an increase in ultra small-angle scatter contrast ratio when compared to end-inspiratory pressures. There were no detectable changes in lung attenuation or refraction contrast ratio with change in lung pressure alone. In effect, multiple image radiography can be applied towards following optical properties of lung air-tissue barrier over time during pathologies such as acute lung injury.

  12. Characterizing and estimating noise in InSAR and InSAR time series with MODIS

    Barnhart, William D.; Lohman, Rowena B.

    2013-01-01

    InSAR time series analysis is increasingly used to image subcentimeter displacement rates of the ground surface. The precision of InSAR observations is often affected by several noise sources, including spatially correlated noise from the turbulent atmosphere. Under ideal scenarios, InSAR time series techniques can substantially mitigate these effects; however, in practice the temporal distribution of InSAR acquisitions over much of the world exhibit seasonal biases, long temporal gaps, and insufficient acquisitions to confidently obtain the precisions desired for tectonic research. Here, we introduce a technique for constraining the magnitude of errors expected from atmospheric phase delays on the ground displacement rates inferred from an InSAR time series using independent observations of precipitable water vapor from MODIS. We implement a Monte Carlo error estimation technique based on multiple (100+) MODIS-based time series that sample date ranges close to the acquisitions times of the available SAR imagery. This stochastic approach allows evaluation of the significance of signals present in the final time series product, in particular their correlation with topography and seasonality. We find that topographically correlated noise in individual interferograms is not spatially stationary, even over short-spatial scales (<10 km). Overall, MODIS-inferred displacements and velocities exhibit errors of similar magnitude to the variability within an InSAR time series. We examine the MODIS-based confidence bounds in regions with a range of inferred displacement rates, and find we are capable of resolving velocities as low as 1.5 mm/yr with uncertainties increasing to ∼6 mm/yr in regions with higher topographic relief.

  13. Reconstructed Image Spatial Resolution of Multiple Coincidences Compton Imager

    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.

  14. Large scale rock slope release planes imaged by differential ground based InSAR at Randa, Switzerland

    Gischig, V.; Loew, S.; Kos, A.; Raetzo, H.

    2009-04-01

    In April and May of 1991 a steep rock slope above the village of Randa (Valais, Switzerland) failed in two events, releasing a total rock volume of 30 million m3. The rock mass behind the back scarp contains several million cubic meters of unstable gneisses and schists which are moving with a maximum rate of about 2 cm/yr. Different geodetic, geotechnical and geophysical techniques were applied to monitor this new instability and to determine its spatial extent. However, the boundaries of the instability could only be roughly estimated so far. For this reason five ground based differential InSAR surveys (GB-DInSAR) were carried out between 2005 and 2007 from the opposite valley flank at a distance to target of 1.3 to 1.9 km. These surveys provide displacements maps of four different time intervals with a spatial resolution of 2 to 6 m and an accuracy of less than 1 mm. These datasets reveal interesting new insights into the spatial distribution of displacements and significantly contribute to the kinematic interpretation of the ongoing movements. We found that the lower boundary of the instability is a narrow rupture plane which coincides with a primary lithological boundary on the slope. The intersection line between this basal rupture plane and the steep rock cliff extents over at least 200 m meters. It is possible to identify this structure on helicopter-based high resolution images and a LiDAR DTM of the failure surface. The eastern boundary of the instability also presents itself as a sharp line separating stable bedrock from a strongly fractured rock mass moving about 1 cm/yr along the line of sight. This lateral release plane is formed by a steeply east dipping tectonic fault plane, with subhorizontal striations and an exposed surface area of about 10'000 square meters. In the north-east of the instability the lateral boundaries crop out on surfaces that have an acute angle to the line of sight or lie in the shadow of the radar. Here the boundaries of the

  15. DARK SPOT DETECTION USING INTENSITY AND THE DEGREE OF POLARIZATION IN FULLY POLARIMETRIC SAR IMAGES FOR OIL POLUTION MONITORING

    F. Zakeri

    2015-12-01

    Full Text Available Oil spill surveillance is of great environmental and economical interest, directly contributing to improve environmental protection. Monitoring of oil spills using synthetic aperture radar (SAR has received a considerable attention over the past few years, notably because of SAR data abilities like all-weather and day-and-night capturing. The degree of polarization (DoP is a less computationally complex quantity characterizing a partially polarized electromagnetic field. The key to the proposed approach is making use of DoP as polarimetric information besides intensity ones to improve dark patches detection as the first step of oil spill monitoring. In the proposed approach first simple intensity threshold segmentation like Otsu method is applied to the image. Pixels with intensities below the threshold are regarded as potential dark spot pixels while the others are potential background pixels. Second, the DoP of potential dark spot pixels is estimated. Pixels with DoP below a certain threshold are the real dark-spot pixels. Choosing the threshold is a critical and challenging step. In order to solve choosing the appropriate threshold, we introduce a novel but simple method based on DoP of potential dark spot pixels. Finally, an area threshold is used to eliminate any remaining false targets. The proposed approach is tested on L band NASA/JPL UAVSAR data, covering the Deepwater Horizon oil spill in the Gulf of Mexico. Comparing the obtained results from the new method with conventional approaches like Otsu, K-means and GrowCut shows better achievement of the proposed algorithm. For instance, mean square error (MSE 65%, Overall Accuracy 20% and correlation 40% are improved.

  16. Dark SPOT Detection Using Intensity and the Degree of Polarization in Fully Polarimetric SAR Images for Oil Polution Monitoring

    Zakeri, F.; Amini, J.

    2015-12-01

    Oil spill surveillance is of great environmental and economical interest, directly contributing to improve environmental protection. Monitoring of oil spills using synthetic aperture radar (SAR) has received a considerable attention over the past few years, notably because of SAR data abilities like all-weather and day-and-night capturing. The degree of polarization (DoP) is a less computationally complex quantity characterizing a partially polarized electromagnetic field. The key to the proposed approach is making use of DoP as polarimetric information besides intensity ones to improve dark patches detection as the first step of oil spill monitoring. In the proposed approach first simple intensity threshold segmentation like Otsu method is applied to the image. Pixels with intensities below the threshold are regarded as potential dark spot pixels while the others are potential background pixels. Second, the DoP of potential dark spot pixels is estimated. Pixels with DoP below a certain threshold are the real dark-spot pixels. Choosing the threshold is a critical and challenging step. In order to solve choosing the appropriate threshold, we introduce a novel but simple method based on DoP of potential dark spot pixels. Finally, an area threshold is used to eliminate any remaining false targets. The proposed approach is tested on L band NASA/JPL UAVSAR data, covering the Deepwater Horizon oil spill in the Gulf of Mexico. Comparing the obtained results from the new method with conventional approaches like Otsu, K-means and GrowCut shows better achievement of the proposed algorithm. For instance, mean square error (MSE) 65%, Overall Accuracy 20% and correlation 40% are improved.

  17. Improved techniques to utilize remotely sensed data from multi-frequency imaging radar polarimeter; Tashuha tahenha SAR data no riyoho no kenkyu

    Okada, K [Sumitomo Metal Mining Co. Ltd., Osaka (Japan); Maruyama, Y [Earth Remote Sensing Data Analysis Center, Tokyo (Japan); Tapley, I

    1997-05-27

    It was intended to serve for establishing specifications for a next generation SAR such as PALSAR through studying methods for evaluating and utilizing the multi-frequency, multi-polarized wave SAR data. Placing an emphasis on utilization of the NASA`s AIRSAR, identification was made on backscatter amount recorded on the SAR data, terrestrial constitutional substances, patterns of the ground surface, micro-topography and such terrestrial conditions as vegetation and land utilization. Their mutual relationships were also analyzed. A noise reduction method usable on multi-band data can be applied to the AIRSAR data, and can reduce noise effectively. Images with more volume of information can be acquired from multi-band images with the same polarization wave than from multi-polarization wave images with the same band. As a result of estimating terrestrial permitivity by using the method invented by Dubois and van Zyl, most of the subject area is judged to have terrestrial substances dried at the time of having acquired the images. A colluvium rich with exposed rock regions and gravels was identified as an area having higher permitivity than the former area. Images of terrestrial roughness were divided largely into smooth flat lands, sand and gravel distributed regions, exposed rock regions, and plant distributed regions along river basins. 3 refs., 2 figs., 1 tab.

  18. Images crossing borders: image and workflow sharing on multiple levels.

    Ross, Peeter; Pohjonen, Hanna

    2011-04-01

    Digitalisation of medical data makes it possible to share images and workflows between related parties. In addition to linear data flow where healthcare professionals or patients are the information carriers, a new type of matrix of many-to-many connections is emerging. Implementation of shared workflow brings challenges of interoperability and legal clarity. Sharing images or workflows can be implemented on different levels with different challenges: inside the organisation, between organisations, across country borders, or between healthcare institutions and citizens. Interoperability issues vary according to the level of sharing and are either technical or semantic, including language. Legal uncertainty increases when crossing national borders. Teleradiology is regulated by multiple European Union (EU) directives and legal documents, which makes interpretation of the legal system complex. To achieve wider use of eHealth and teleradiology several strategic documents were published recently by the EU. Despite EU activities, responsibility for organising, providing and funding healthcare systems remains with the Member States. Therefore, the implementation of new solutions requires strong co-operation between radiologists, societies of radiology, healthcare administrators, politicians and relevant EU authorities. The aim of this article is to describe different dimensions of image and workflow sharing and to analyse legal acts concerning teleradiology in the EU.

  19. Enhancement of Tropical Land Cover Mapping with Wavelet-Based Fusion and Unsupervised Clustering of SAR and Landsat Image Data

    LeMoigne, Jacqueline; Laporte, Nadine; Netanyahuy, Nathan S.; Zukor, Dorothy (Technical Monitor)

    2001-01-01

    The characterization and the mapping of land cover/land use of forest areas, such as the Central African rainforest, is a very complex task. This complexity is mainly due to the extent of such areas and, as a consequence, to the lack of full and continuous cloud-free coverage of those large regions by one single remote sensing instrument, In order to provide improved vegetation maps of Central Africa and to develop forest monitoring techniques for applications at the local and regional scales, we propose to utilize multi-sensor remote sensing observations coupled with in-situ data. Fusion and clustering of multi-sensor data are the first steps towards the development of such a forest monitoring system. In this paper, we will describe some preliminary experiments involving the fusion of SAR and Landsat image data of the Lope Reserve in Gabon. Similarly to previous fusion studies, our fusion method is wavelet-based. The fusion provides a new image data set which contains more detailed texture features and preserves the large homogeneous regions that are observed by the Thematic Mapper sensor. The fusion step is followed by unsupervised clustering and provides a vegetation map of the area.

  20. Magnetic resonance imaging in multiple sclerosis

    Kojima, Shigeyuki; Hirayama, Keizo

    1989-01-01

    Magnetic resonance imaging (MRI) of the brain was performed in a total of 45 patients with multiple sclerosis (MS), comprising 27 with brain symptoms and 18 without it. The results were compared with X-ray computed tomography (CT). Some of the 45 MS patients were also examined by neurophysiological studies for comparison. MRI showed demyelinating plaques of the brain in a total of 31 patients (69%) - 20 symptomatic and 11 asymptomatic patients. For symptomatic patients, MRI was capable of detecting brain lesions in 6 (86%) of 7 acute stage patients and 14 (70%) of 20 non-acute stage patients. It was also capable of detecting brain lesions in 21 (70%) of 30 clinically definite MR patients and 10 (67%) of 15 clinically probable MS patients. Concurrently available X-ray CT revealed brain lesions in 9 symptomatic patients (33%) and one asymptomatic patient (6%). Visual evoked potentials examined in 31 patients showed abnormality in one (11%) of 9 patients without symptoms of optic neuritis and all (100%) of the other 22 patients with symptoms. In 19 evaluable patients, auditory brainstem responses were abnormal in one (11%) of 9 patients without brainstem symptoms and 3 (30%) of 10 patients with symptoms. MRI of the brain was far superior to X-ray CT, visual evoked potentials and auditory brainstem responses in detecting clinically unsuspected lesions. We proposed new diagnostic criteria including MRI findings of the brain in the Japanese MS diagnostic criteria. MRI of the spinal cord was performed in 12 MS patients with spinal cord symptoms by sagittal and coronal images. It demonstrated demyelinating lesions within the cervical and superior thoracic cord in 8 MS acute stage patients. Spinal cord lesions were longitudinally continuous as long as many spinal segments, with swelling in 6 patients and atrophy in 2 patients. MRI of spinal cord was useful in deciding superior and inferior limits of cord lesions and in visualizing cord swelling or atrophy. (Namekawa, K)

  1. The Advanced Rapid Imaging and Analysis (ARIA) Project: Status of SAR products for Earthquakes, Floods, Volcanoes and Groundwater-related Subsidence

    Owen, S. E.; Yun, S. H.; Hua, H.; Agram, P. S.; Liu, Z.; Sacco, G. F.; Manipon, G.; Linick, J. P.; Fielding, E. J.; Lundgren, P.; Farr, T. G.; Webb, F.; Rosen, P. A.; Simons, M.

    2017-12-01

    The Advanced Rapid Imaging and Analysis (ARIA) project for Natural Hazards is focused on rapidly generating high-level geodetic imaging products and placing them in the hands of the solid earth science and local, national, and international natural hazard communities by providing science product generation, exploration, and delivery capabilities at an operational level. Space-based geodetic measurement techniques including Interferometric Synthetic Aperture Radar (InSAR), differential Global Positioning System, and SAR-based change detection have become critical additions to our toolset for understanding and mapping the damage and deformation caused by earthquakes, volcanic eruptions, floods, landslides, and groundwater extraction. Up until recently, processing of these data sets has been handcrafted for each study or event and has not generated products rapidly and reliably enough for response to natural disasters or for timely analysis of large data sets. The ARIA project, a joint venture co-sponsored by the California Institute of Technology and by NASA through the Jet Propulsion Laboratory, has been capturing the knowledge applied to these responses and building it into an automated infrastructure to generate imaging products in near real-time that can improve situational awareness for disaster response. In addition to supporting the growing science and hazard response communities, the ARIA project has developed the capabilities to provide automated imaging and analysis capabilities necessary to keep up with the influx of raw SAR data from geodetic imaging missions such as ESA's Sentinel-1A/B, now operating with repeat intervals as short as 6 days, and the upcoming NASA NISAR mission. We will present the progress and results we have made on automating the analysis of Sentinel-1A/B SAR data for hazard monitoring and response, with emphasis on recent developments and end user engagement in flood extent mapping and deformation time series for both volcano

  2. Landslide precursory deformation interpretation using ALOS-2/PALSAR-2 InSAR image along Min River in Maoxien, Sichuan Province, China

    Sato, H. P.

    2017-12-01

    Maoxien area in Sichuan Province, China has many landslide. For example, landslide (rock avalanche) occurred on the slope in Xinmocun Village in Maoxeien on 24 June 2017. I produced and interpreetd InSAR image using ALOS/PALSAR data observed on 19 Jul 2007-3 Sep 2007 and on 27 Jan 2011-14 Mar 2011, and ALOS-2/PALSAR-2 data observed on 26 Jul 2015-13 Dec 2015 and on 13 Dec 2015-11 Dec 2016. These images give good coherence and it was easy to identify local landslide surface deformation. As a result, e.g., two slopes were estimated to have local landslide surface deformation; one is at 103.936587 deg E and 32.04462 deg N, another is at 103.674754 deg E and 31.852838 N. However, the slope in Xinmocun Village was not identified as landslide precursory deformation. In the poster I will present more InSAR image observed after 11 Dec 2016 and discuss the possibility of local landslide surface deformaton using InSAR image. ALOS/PALSAR and ALOS-2/PALSAR-2 data were provided by JAXA through Landslide Working Group in JAXA and through Special Research 2015-B-02 of Earthquake Research Institute/Tokyo University. This study was supported by KAKENHI (17H02973).

  3. Estimation of Bridge Height over Water from Polarimetric SAR Image Data Using Mapping and Projection Algorithm and De-Orientation Theory

    Wang, Haipeng; Xu, Feng; Jin, Ya-Qiu; Ouchi, Kazuo

    An inversion method of bridge height over water by polarimetric synthetic aperture radar (SAR) is developed. A geometric ray description to illustrate scattering mechanism of a bridge over water surface is identified by polarimetric image analysis. Using the mapping and projecting algorithm, a polarimetric SAR image of a bridge model is first simulated and shows that scattering from a bridge over water can be identified by three strip lines corresponding to single-, double-, and triple-order scattering, respectively. A set of polarimetric parameters based on the de-orientation theory is applied to analysis of three types scattering, and the thinning-clustering algorithm and Hough transform are then employed to locate the image positions of these strip lines. These lines are used to invert the bridge height. Fully polarimetric image data of airborne Pi-SAR at X-band are applied to inversion of the height and width of the Naruto Bridge in Japan. Based on the same principle, this approach is also applicable to spaceborne ALOSPALSAR single-polarization data of the Eastern Ocean Bridge in China. The results show good feasibility to realize the bridge height inversion.

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

    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.

  5. The InSAeS4 Airborne X-Band Interferometric SAR System: A First Assessment on Its Imaging and Topographic Mapping Capabilities

    Stefano Perna

    2016-01-01

    Full Text Available We present in this work a first assessment of the imaging and topographic mapping capabilities of the InSAeS4 system, which is a single-pass interferometric airborne X-Band Synthetic Aperture Radar (SAR. In particular, we first provide a brief description of the InSAeS4 sensor. Then, we discuss the results of our analysis on the SAR and interferometric SAR products relevant to the first flight-test campaign. More specifically, we have exploited as reference the GPS measurements relevant to nine Corner Reflectors (CRs deployed over the illuminated area during the campaign and a laser scanner Digital Elevation Model (DEM. From the analysis carried out on the CRs we achieved a mean geometric resolution, for the SAR products, of about 0.14 m in azimuth and 0.49 m in range, a positioning misalignment with standard deviation of 0.07 m in range and 0.08 m in azimuth, and a height error with standard deviation of 0.51 m. From the comparison with the laser scanner DEM we estimated a height error with standard deviation of 1.57 m.

  6. Iterative Redeployment of Illumination and Sensing (IRIS): Application to STW-SAR Imaging

    Marble, Jay; Raich, Raviv; Hero, Alfred O

    2006-01-01

    .... The IRIS algorithm has the following features: (1) use of a sparse Bayesian image model that captures the free-space dominated propagation characteristics of interiors of man-made structures such as caves and residences; (2...

  7. Dual Super-Systolic Core for Real-Time Reconstructive Algorithms of High-Resolution Radar/SAR Imaging Systems

    Atoche, Alejandro Castillo; Castillo, Javier Vázquez

    2012-01-01

    A high-speed dual super-systolic core for reconstructive signal processing (SP) operations consists of a double parallel systolic array (SA) machine in which each processing element of the array is also conceptualized as another SA in a bit-level fashion. In this study, we addressed the design of a high-speed dual super-systolic array (SSA) core for the enhancement/reconstruction of remote sensing (RS) imaging of radar/synthetic aperture radar (SAR) sensor systems. The selected reconstructive SP algorithms are efficiently transformed in their parallel representation and then, they are mapped into an efficient high performance embedded computing (HPEC) architecture in reconfigurable Xilinx field programmable gate array (FPGA) platforms. As an implementation test case, the proposed approach was aggregated in a HW/SW co-design scheme in order to solve the nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) from a remotely sensed scene. We show how such dual SSA core, drastically reduces the computational load of complex RS regularization techniques achieving the required real-time operational mode. PMID:22736964

  8. Area-efficient readout with 14-bit SAR-ADC for CMOS image sensors

    Aziza Sassi Ben

    2016-01-01

    Full Text Available This paper proposes a readout design for CMOS image sensors. It has been squeezed into a 7.5um pitch under a 0.28um 1P3M technology. The ADC performs one 14-bit conversion in only 1.5us and targets a theoretical DNL feature about +1.3/-1 at 14-bit accuracy. Correlated Double Sampling (CDS is performed both in the analog and digital domains to preserve the image quality.

  9. Local SAR in High Pass Birdcage and TEM Body Coils for Multiple Human Body Models in Clinical Landmark Positions at 3T

    Yeo, Desmond TB; Wang, Zhangwei; Loew, Wolfgang; Vogel, Mika W; Hancu, Ileana

    2011-01-01

    Purpose To use EM simulations to study the effects of body type, landmark position, and RF body coil type on peak local SAR in 3T MRI. Materials and Methods Numerically computed peak local SAR for four human body models (HBMs) in three landmark positions (head, heart, pelvic) were compared for a high-pass birdcage and a transverse electromagnetic 3T body coil. Local SAR values were normalized to the IEC whole-body average SAR limit of 2.0 W/kg for normal scan mode. Results Local SAR distributions were highly variable. Consistent with previous reports, the peak local SAR values generally occurred in the neck-shoulder area, near rungs, or between tissues of greatly differing electrical properties. The HBM type significantly influenced the peak local SAR, with stockier HBMs, extending extremities towards rungs, displaying the highest SAR. There was also a trend for higher peak SAR in the head-centric and heart-centric positions. The impact of the coil-types studied was not statistically significant. Conclusion The large variability in peak local SAR indicates the need to include more than one HBM or landmark position when evaluating safety of body coils. It is recommended that a HBM with arms near the rungs be included, to create physically realizable high-SAR scenarios. PMID:21509880

  10. Comparing Accuracy of Airborne Laser Scanning and TerraSAR-X Radar Images in the Estimation of Plot-Level Forest Variables

    Juha Hyyppä

    2010-01-01

    Full Text Available In this study we compared the accuracy of low-pulse airborne laser scanning (ALS data, multi-temporal high-resolution noninterferometric TerraSAR-X radar data and a combined feature set derived from these data in the estimation of forest variables at plot level. The TerraSAR-X data set consisted of seven dual-polarized (HH/HV or VH/VV Stripmap mode images from all seasons of the year. We were especially interested in distinguishing between the tree species. The dependent variables estimated included mean volume, basal area, mean height, mean diameter and tree species-specific mean volumes. Selection of best possible feature set was based on a genetic algorithm (GA. The nonparametric k-nearest neighbour (k-NN algorithm was applied to the estimation. The research material consisted of 124 circular plots measured at tree level and located in the vicinity of Espoo, Finland. There are large variations in the elevation and forest structure in the study area, making it demanding for image interpretation. The best feature set contained 12 features, nine of them originating from the ALS data and three from the TerraSAR-X data. The relative RMSEs for the best performing feature set were 34.7% (mean volume, 28.1% (basal area, 14.3% (mean height, 21.4% (mean diameter, 99.9% (mean volume of Scots pine, 61.6% (mean volume of Norway spruce and 91.6% (mean volume of deciduous tree species. The combined feature set outperformed an ALS-based feature set marginally; in fact, the latter was better in the case of species-specific volumes. Features from TerraSAR-X alone performed poorly. However, due to favorable temporal resolution, satellite-borne radar imaging is a promising data source for updating large-area forest inventories based on low-pulse ALS.

  11. Study on monitoring ecological restoration in Jiuli mining area by SAR image

    Wei, Na; Chen, Fu; Tang, Qian

    2011-10-01

    The ecological restoration in mining area is one of the study hot spots in the field of resources and environment at present. The vegetation biomass is used as the ecological restoration evaluation index in mining area in the paper. The synthetic aperture radar image after ecological restoration in mining area is used to classify different kinds of vegetation covers. Integrating the field data and the data of L band, the average total backward scattering coefficient which corresponds to the synthetic aperture radar image is calculated and the relation model between the average total backward scattering coefficient and vegetation biomass is established. At last the vegetation biomass is assessed in Jiuli mining area. The results show that the vegetation biomass characteristics which are assessed by using synthetic aperture radar image data and the field data of vegetation biomass characteristics have better consistency in Jiuli mining area. The effects of ecological restoration can be evaluated by using this relation model effectively and accurately.

  12. Semi-automated procedures for shoreline extraction using single RADARSAT-1 SAR image

    Al Fugura, A.'kif; Billa, Lawal; Pradhan, Biswajeet

    2011-12-01

    Coastline identification is important for surveying and mapping reasons. Coastline serves as the basic point of reference and is used on nautical charts for navigation purposes. Its delineation has become crucial and more important in the wake of the many recent earthquakes and tsunamis resulting in complete change and redraw of some shorelines. In a tropical country like Malaysia, presence of cloud cover hinders the application of optical remote sensing data. In this study a semi-automated technique and procedures are presented for shoreline delineation from RADARSAT-1 image. A scene of RADARSAT-1 satellite image was processed using enhanced filtering technique to identify and extract the shoreline coast of Kuala Terengganu, Malaysia. RADSARSAT image has many advantages over the optical data because of its ability to penetrate cloud cover and its night sensing capabilities. At first, speckles were removed from the image by using Lee sigma filter which was used to reduce random noise and to enhance the image and discriminate the boundary between land and water. The results showed an accurate and improved extraction and delineation of the entire coastline of Kuala Terrenganu. The study demonstrated the reliability of the image averaging filter in reducing random noise over the sea surface especially near the shoreline. It enhanced land-water boundary differentiation, enabling better delineation of the shoreline. Overall, the developed techniques showed the potential of radar imagery for accurate shoreline mapping and will be useful for monitoring shoreline changes during high and low tides as well as shoreline erosion in a tropical country like Malaysia.

  13. Magnetic resonance imaging in multiple system atrophy

    Aotsuka, Akiyo; Shinotoh, Hitoshi; Hirayama, Keizo [Chiba Univ. (Japan). School of Medicine; Ikehira, Hiroo; Hashimoto, Takahiro

    1992-08-01

    We studied 18 patients with multiple system atrophy (MSA) by high field strength MRI: 6 striatonigral degeneration (SND), 4 Shy-Drager syndrome (SDS), and 8 olivo-ponto-cerebellar atrophy (OPCA). We also studied 30 Parkinson's disease (PD) and 10 age-matched controls. The diagnosis of SND, SDS, and OPCA were based on criteria after Hirayama et al (1985). Bradykinesia, rigidity, and tremor were assessed with the summed scores of the signs used as the extrapyramidal scores. The mean extrapyramidal scores were not significantly different in patients with SND, SDS, OPCA, and PD. MRI studies were performed on 1.5 tesla MRI unit, using a T[sub 2]-weighted spin echo pulse sequence (TR2500 ms/TE40 ms). The width of the pars compacta signal in all subjects was measured by the method of Duguid et al (1986). Intensity profiles were made on a straight line perpendicular to the pars compacta through the center of the red nucleus on an image of the midbrain. We measured the width of the valley at half-height between the peaks of an index of the width of the pars compacta signal. The mean widths of the pars compacta signal were: 2.8[+-]0.4 mm (SND), 2.8[+-]0.7 mm (SDS), 3.6[+-]0.6 mm (OPCA), 2.7[+-]0.3 mm (PD), and 4.3[+-]0.6 mm (control). The mean widths of the pars compacta signal in PD, SND, and SDS were significantly narrower than that in the control group (p<0.05), while the OPCA group was not significantly narrower. The results may indicate that the time course of nigral involvement is milder in OPCA than in SND and SDS. The extrapyramidal signs in OPCA may be attributed mainly to the degeneration of the putamen rather than to that of the substantia nigra. Abnormal hypointensity in the posterolateral putamen was found in only one SND patient and in two OPCA patients, even though this finding has been frequently observed in MSA. Since no PD patients exhibited this finding, it may of some value in differentiating MSA from PD. (author).

  14. a Method for the Extraction of Long-Term Deformation Characteristics of Long-Span High-Speed Railway Bridges Using High-Resolution SAR Images

    Jia, H. G.; Liu, L. Y.

    2016-06-01

    Natural causes and high-speed train load will result in the structural deformation of long-span bridges, which greatly influence the safety operation of high-speed railway. Hence it is necessary to conduct the deformation monitoring and regular status assessment for long-span bridges. However for some traditional surveying technique, e.g. control-point-based surveying techniques, a lot of human and material resources are needed to perform the long-term monitoring for the whole bridge. In this study we detected the long-term bridge deformation time-series by persistent scatterer interferometric synthetic aperture radar (PSInSAR) technique using the high-resolution SAR images and external digital elevation model. A test area in Nanjing city in China is chosen and TerraSAR-X images and Tandem-X for this area have been used. There is the Dashengguan bridge in high speed railway in this area as study object to evaluate this method. Experiment results indicate that the proposed method can effectively extract the long-term deformation of long-span high-speed railway bridge with higher accuracy.

  15. A METHOD FOR THE EXTRACTION OF LONG-TERM DEFORMATION CHARACTERISTICS OF LONG-SPAN HIGH-SPEED RAILWAY BRIDGES USING HIGH-RESOLUTION SAR IMAGES

    H. G. Jia

    2016-06-01

    Full Text Available Natural causes and high-speed train load will result in the structural deformation of long-span bridges, which greatly influence the safety operation of high-speed railway. Hence it is necessary to conduct the deformation monitoring and regular status assessment for long-span bridges. However for some traditional surveying technique, e.g. control-point-based surveying techniques, a lot of human and material resources are needed to perform the long-term monitoring for the whole bridge. In this study we detected the long-term bridge deformation time-series by persistent scatterer interferometric synthetic aperture radar (PSInSAR technique using the high-resolution SAR images and external digital elevation model. A test area in Nanjing city in China is chosen and TerraSAR-X images and Tandem-X for this area have been used. There is the Dashengguan bridge in high speed railway in this area as study object to evaluate this method. Experiment results indicate that the proposed method can effectively extract the long-term deformation of long-span high-speed railway bridge with higher accuracy.

  16. Optical cell sorting with multiple imaging modalities

    Banas, Andrew; Carrissemoux, Caro; Palima, Darwin

    2017-01-01

    healthy cells. With the richness of visual information, a lot of microscopy techniques have been developed and have been crucial in biological studies. To utilize their complementary advantages we adopt both fluorescence and brightfield imaging in our optical cell sorter. Brightfield imaging has...... the advantage of being non-invasive, thus maintaining cell viability. Fluorescence imaging, on the other hand, takes advantages of the chemical specificity of fluorescence markers and can validate machine vision results from brightfield images. Visually identified cells are sorted using optical manipulation...

  17. Image Alignment for Multiple Camera High Dynamic Range Microscopy.

    Eastwood, Brian S; Childs, Elisabeth C

    2012-01-09

    This paper investigates the problem of image alignment for multiple camera high dynamic range (HDR) imaging. HDR imaging combines information from images taken with different exposure settings. Combining information from multiple cameras requires an alignment process that is robust to the intensity differences in the images. HDR applications that use a limited number of component images require an alignment technique that is robust to large exposure differences. We evaluate the suitability for HDR alignment of three exposure-robust techniques. We conclude that image alignment based on matching feature descriptors extracted from radiant power images from calibrated cameras yields the most accurate and robust solution. We demonstrate the use of this alignment technique in a high dynamic range video microscope that enables live specimen imaging with a greater level of detail than can be captured with a single camera.

  18. Selective interferometric imaging of internal multiples

    Zuberi, M. A H; Alkhalifah, Tariq Ali

    2013-01-01

    are required to construct a Green’s function with all the scattered energy. As an alternative, we develop a three-step procedure, which images the first-order internal scattering using the background Green’s function (from the surface to each image point

  19. Seismic reflection imaging, accounting for primary and multiple reflections

    Wapenaar, Kees; van der Neut, Joost; Thorbecke, Jan; Broggini, Filippo; Slob, Evert; Snieder, Roel

    2015-04-01

    Imaging of seismic reflection data is usually based on the assumption that the seismic response consists of primary reflections only. Multiple reflections, i.e. waves that have reflected more than once, are treated as primaries and are imaged at wrong positions. There are two classes of multiple reflections, which we will call surface-related multiples and internal multiples. Surface-related multiples are those multiples that contain at least one reflection at the earth's surface, whereas internal multiples consist of waves that have reflected only at subsurface interfaces. Surface-related multiples are the strongest, but also relatively easy to deal with because the reflecting boundary (the earth's surface) is known. Internal multiples constitute a much more difficult problem for seismic imaging, because the positions and properties of the reflecting interfaces are not known. We are developing reflection imaging methodology which deals with internal multiples. Starting with the Marchenko equation for 1D inverse scattering problems, we derived 3D Marchenko-type equations, which relate reflection data at the surface to Green's functions between virtual sources anywhere in the subsurface and receivers at the surface. Based on these equations, we derived an iterative scheme by which these Green's functions can be retrieved from the reflection data at the surface. This iterative scheme requires an estimate of the direct wave of the Green's functions in a background medium. Note that this is precisely the same information that is also required by standard reflection imaging schemes. However, unlike in standard imaging, our iterative Marchenko scheme retrieves the multiple reflections of the Green's functions from the reflection data at the surface. For this, no knowledge of the positions and properties of the reflecting interfaces is required. Once the full Green's functions are retrieved, reflection imaging can be carried out by which the primaries and multiples are

  20. Real-time multiple image manipulations

    Arenson, J.S.; Shalev, S.; Legris, J.; Goertzen, Y.

    1984-01-01

    There are many situations in which it is desired to manipulate two or more images under real-time operator control. The authors have investigated a number of such cases in order to determine their value and applicability in clinical medicine and laboratory research. Several examples are presented in detail. The DICOM-8 video image computer system was used due to its capability of storing two 512 x 512 x 8 bit images and operating on them, and/or an incoming video frame, with any of a number of real time operations including addition, subtraction, inversion, averaging, logical AND, NAND, OR, NOR, NOT, XOR and XNOR, as well as combinations of these. Some applications involve manipulations of or among the stored images. In others, a stored image is used as a mask or template for positioning or adjusting a second image to be grabbed via a video camera. The accuracy of radiotherapy treatment is verified by comparing port films with the original radiographic planning film, which is previously digitized and stored. Moving the port film on the light box while viewing the real-time subtraction image allows for adjustments of zoom, translation and rotation, together with contrast and edge enhancement

  1. Pareto-depth for multiple-query image retrieval.

    Hsiao, Ko-Jen; Calder, Jeff; Hero, Alfred O

    2015-02-01

    Most content-based image retrieval systems consider either one single query, or multiple queries that include the same object or represent the same semantic information. In this paper, we consider the content-based image retrieval problem for multiple query images corresponding to different image semantics. We propose a novel multiple-query information retrieval algorithm that combines the Pareto front method with efficient manifold ranking. We show that our proposed algorithm outperforms state of the art multiple-query retrieval algorithms on real-world image databases. We attribute this performance improvement to concavity properties of the Pareto fronts, and prove a theoretical result that characterizes the asymptotic concavity of the fronts.

  2. Bistatic SAR/ISAR/FSR geometry, signal models and imaging algorithms

    Lazarov, Andon Dimitrov

    2013-01-01

    Bistatic radar consists of a radar system which comprises a transmitter and receiver which are separated by a distance comparable to the expected target distance. This book provides a general theoretical description of such bistatic technology in the context of synthetic aperture, inverse synthetic aperture and forward scattering radars from the point of view of analytical geometrical and signal formation as well as processing theory. Signal formation and image reconstruction algorithms are developed with the application of high informative linear frequency and phase code modulating techniques

  3. Urban Monitoring Based on SENTINEL-1 Data Using Permanent Scatterer Interferometry and SAR Tomography

    Crosetto, M.; Budillon, A.; Johnsy, A.; Schirinzi, G.; Devanthéry, N.; Monserrat, O.; Cuevas-González, M.

    2018-04-01

    A lot of research and development has been devoted to the exploitation of satellite SAR images for deformation measurement and monitoring purposes since Differential Interferometric Synthetic Apertura Radar (InSAR) was first described in 1989. In this work, we consider two main classes of advanced DInSAR techniques: Persistent Scatterer Interferometry and Tomographic SAR. Both techniques make use of multiple SAR images acquired over the same site and advanced procedures to separate the deformation component from the other phase components, such as the residual topographic component, the atmospheric component, the thermal expansion component and the phase noise. TomoSAR offers the advantage of detecting either single scatterers presenting stable proprieties over time (Persistent Scatterers) and multiple scatterers interfering within the same range-azimuth resolution cell, a significant improvement for urban areas monitoring. This paper addresses a preliminary inter-comparison of the results of both techniques, for a test site located in the metropolitan area of Barcelona (Spain), where interferometric Sentinel-1 data were analysed.

  4. An Unsupervised Change Detection Method Using Time-Series of PolSAR Images from Radarsat-2 and GaoFen-3.

    Liu, Wensong; Yang, Jie; Zhao, Jinqi; Shi, Hongtao; Yang, Le

    2018-02-12

    The traditional unsupervised change detection methods based on the pixel level can only detect the changes between two different times with same sensor, and the results are easily affected by speckle noise. In this paper, a novel method is proposed to detect change based on time-series data from different sensors. Firstly, the overall difference image of the time-series PolSAR is calculated by omnibus test statistics, and difference images between any two images in different times are acquired by R j test statistics. Secondly, the difference images are segmented with a Generalized Statistical Region Merging (GSRM) algorithm which can suppress the effect of speckle noise. Generalized Gaussian Mixture Model (GGMM) is then used to obtain the time-series change detection maps in the final step of the proposed method. To verify the effectiveness of the proposed method, we carried out the experiment of change detection using time-series PolSAR images acquired by Radarsat-2 and Gaofen-3 over the city of Wuhan, in China. Results show that the proposed method can not only detect the time-series change from different sensors, but it can also better suppress the influence of speckle noise and improve the overall accuracy and Kappa coefficient.

  5. Combined DEM Extration Method from StereoSAR and InSAR

    Zhao, Z.; Zhang, J. X.; Duan, M. Y.; Huang, G. M.; Yang, S. C.

    2015-06-01

    A pair of SAR images acquired from different positions can be used to generate digital elevation model (DEM). Two techniques exploiting this characteristic have been introduced: stereo SAR and interferometric SAR. They permit to recover the third dimension (topography) and, at the same time, to identify the absolute position (geolocation) of pixels included in the imaged area, thus allowing the generation of DEMs. In this paper, StereoSAR and InSAR combined adjustment model are constructed, and unify DEM extraction from InSAR and StereoSAR into the same coordinate system, and then improve three dimensional positioning accuracy of the target. We assume that there are four images 1, 2, 3 and 4. One pair of SAR images 1,2 meet the required conditions for InSAR technology, while the other pair of SAR images 3,4 can form stereo image pairs. The phase model is based on InSAR rigorous imaging geometric model. The master image 1 and the slave image 2 will be used in InSAR processing, but the slave image 2 is only used in the course of establishment, and the pixels of the slave image 2 are relevant to the corresponding pixels of the master image 1 through image coregistration coefficient, and it calculates the corresponding phase. It doesn't require the slave image in the construction of the phase model. In Range-Doppler (RD) model, the range equation and Doppler equation are a function of target geolocation, while in the phase equation, the phase is also a function of target geolocation. We exploit combined adjustment model to deviation of target geolocation, thus the problem of target solution is changed to solve three unkonwns through seven equations. The model was tested for DEM extraction under spaceborne InSAR and StereoSAR data and compared with InSAR and StereoSAR methods respectively. The results showed that the model delivered a better performance on experimental imagery and can be used for DEM extraction applications.

  6. Measurement and imaging of infragravity waves in sea ice using InSAR

    Mahoney, Andrew R.; Dammann, Dyre O.; Johnson, Mark A.; Eicken, Hajo; Meyer, Franz J.

    2016-06-01

    Using short-temporal baseline interferometric synthetic aperture radar, we capture instantaneous images of a persistent field of infragravity waves propagating through sea ice near Barrow, Alaska, during January 2015. We estimate wave amplitudes to be between 1.2 and 1.8 mm. Curvature of wavefronts is consistent with refraction of waves entering shallow water from a source region north of Barrow. A shallow water wave model indicates that the geometry of the wavefronts is relatively insensitive to the source location, but other evidence suggests the waves may have originated in the North Atlantic, making this perhaps the longest observed propagation path for waves through ice. We also note that steepening of the waves entering shallow water can increase the peak strain by an order of magnitude, suggesting that infragravity waves may play a role in determining the location of the landfast ice edge with respect to water depth.

  7. INTEGRATED FUSION METHOD FOR MULTIPLE TEMPORAL-SPATIAL-SPECTRAL IMAGES

    H. Shen

    2012-08-01

    Full Text Available Data fusion techniques have been widely researched and applied in remote sensing field. In this paper, an integrated fusion method for remotely sensed images is presented. Differently from the existed methods, the proposed method has the performance to integrate the complementary information in multiple temporal-spatial-spectral images. In order to represent and process the images in one unified framework, two general image observation models are firstly presented, and then the maximum a posteriori (MAP framework is used to set up the fusion model. The gradient descent method is employed to solve the fused image. The efficacy of the proposed method is validated using simulated images.

  8. Design and characterization of a 12-bit 10MS/s 10mW pipelined SAR ADC for CZT-based hard X-ray imager

    Xue, F.; Gao, W.; Duan, Y.; Zheng, R.; Hu, Y.

    2018-02-01

    This paper presents a 12-bit pipelined successive approximation register (SAR) ADC for CZT-based hard X-ray Imager. The proposed ADC is comprised of a first-stage 6-bit SAR-based Multiplying Digital Analog Converter (MDAC) and a second-stage 8-bit SAR ADC. A novel MDAC architecture using Vcm-based Switching method is employed to maximize the energy efficiency and improve the linearity of the ADC. Moreover, the unit-capacitor array instead of the binary-weighted capacitor array is adopted to improve the conversion speed and linearity of the ADC in the first-stage MDAC. In addition, a new layout design method for the binary-weighted capacitor array is proposed to reduce the capacitor mismatches and make the routing become easier and less-time-consuming. Finally, several radiation-hardened-by-design technologies are adopted in the layout design against space radiation effects. The prototype chip was fabricated in 0.18 μm mixed-signal 1.8V/3.3V process and operated at 1.8 V supply. The chip occupies a core area of only 0.58 mm2. The proposed pipelined SAR ADC achieves a peak signal-to-noise-and-distortion ratio (SNDR) of 66.7 dB and a peak spurious-free dynamic range (SFDR) of 78.6 dB at 10 MS/s sampling rate and consumes 10 mW. The figure of merit (FOM) of the proposed ADC is 0.56 pJ/conversion-step.

  9. Use of ERS-2 Sar and Landsat TM Images for Geological Mapping and Mineral Exploration Of Sol Hamid Area, South Eastern Desert, Egypt

    Ramadan, T.M.

    2003-01-01

    Sol hamid area is chiefy occupied by neo proterozoic rocks, partly covered by miocene sediments and recent sand sheets and dunes. The neo proterozoic rocks include ophiolitic ultramafic to mafic rocks, meta volcano-sedimentary rocks, meta volcanics, gabbros-diorite rocks, granodiorites, biotite granites and alkali granites. Magnesite, chromite, iron ores, manganese and barite ore deposits are hosted in different at the study area. ERS-2 SAR data enabled to obtain an image that reveals some buried fluvial features beneath the surface cover of desert sand. These features are not observable in Landsat TM image of similar resolution. In this work, Principal Component Analysis (PCA) technique was used for merging ERS-2 SAR and Landsat TM images to make use of the potential of data fusion technique of image processing in the interpretation of geological features. This procedure has resulted in enhancing subsurface structure such as faults that control distribution of several deposits in the study area. This study represents an example to demonstrate the utility of merging various remote sensing data for exploring mineral deposits in arid region

  10. Radar image and data fusion for natural hazards characterisation

    Lu, Zhong; Dzurisin, Daniel; Jung, Hyung-Sup; Zhang, Jixian; Zhang, Yonghong

    2010-01-01

    Fusion of synthetic aperture radar (SAR) images through interferometric, polarimetric and tomographic processing provides an all - weather imaging capability to characterise and monitor various natural hazards. This article outlines interferometric synthetic aperture radar (InSAR) processing and products and their utility for natural hazards characterisation, provides an overview of the techniques and applications related to fusion of SAR/InSAR images with optical and other images and highlights the emerging SAR fusion technologies. In addition to providing precise land - surface digital elevation maps, SAR - derived imaging products can map millimetre - scale elevation changes driven by volcanic, seismic and hydrogeologic processes, by landslides and wildfires and other natural hazards. With products derived from the fusion of SAR and other images, scientists can monitor the progress of flooding, estimate water storage changes in wetlands for improved hydrological modelling predictions and assessments of future flood impacts and map vegetation structure on a global scale and monitor its changes due to such processes as fire, volcanic eruption and deforestation. With the availability of SAR images in near real - time from multiple satellites in the near future, the fusion of SAR images with other images and data is playing an increasingly important role in understanding and forecasting natural hazards.

  11. Benefits and limitations of imaging multiples: Interferometric and resonant migration

    Guo, Bowen; Yu, Jianhua; Huang, Yunsong; Hanafy, Sherif M.; Schuster, Gerard T.

    2015-01-01

    The benefits and limitations of imaging multiples are reviewed for interferometric migration and resonant migration. Synthetic and field data examples are used to characterize the effectiveness of the methods.

  12. Benefits and limitations of imaging multiples: Interferometric and resonant migration

    Guo, Bowen

    2015-07-01

    The benefits and limitations of imaging multiples are reviewed for interferometric migration and resonant migration. Synthetic and field data examples are used to characterize the effectiveness of the methods.

  13. Multiple sclerosis and magnetic resonance imaging

    Truyen, Luc; Gheuens, Jan; Parizel, P.M.; Van de Vyver, F.L.; Martin, J.J.

    1991-01-01

    In previous studies it has been showed that standardization of the MRI examination and inclusion of sagittal proton-density images results in higher sensitivity and improved correlation with clinical findings. In the present study the usefulness of this MRI protocol in the follow-up of MS patients is evaluated. (author). 5 refs.; 2 figs.; 1 tab

  14. Multiple event 2D image intensifier scintillation detector

    Thieberger, P.; Wegner, H.E.; Lee, R.C.

    1981-01-01

    An image intensifier scintillation detector has been developed for the simultaneous detection of multiple light or heavy ions down to very low energies. The relative X-Y positions of each ion are read out by digitization of a television image of the light amplified scintillations. The maximum data rate is limited by the present television scan speed to 15 multiple events per second and to about one event second by the microcomputer presently used to store and process the data. (orig.)

  15. Magnetic resonance imaging of the spine in multiple myeloma

    Tanaka, Masato; Nakahara, Shinnosuke; Koura, Hiroshi; Kai, Nobuo; Asaumi, Koji; Tanaka, Shunsuke; Sezaki, Tatsuo; Fukuda, Shunichi; Sunami, Kazutaka

    2000-01-01

    The characteristics of diagnostic imaging of the spine in multiple myeloma were examined. Twenty-one patients with stage II-III multiple myeloma (male=12, female=9, mean age=64) underwent MRI of the spine. Other diagnostic imaging modalities used in these patients included, CT bone scintigraphy, and radiography. All images of the spine were assessed and compared with the MRI images. The type of progression was evaluated based on the tumor distribution classification established by Sezaki. T1-weighted images of all 21 patients showed low signals in vertebral bodies, including 14 cases with a focal low signal intensity and 7 cases with diffuse low signal intensity. On the T2-weighted images, 15 of the 21 cases (71%) showed equivalent signals, while T2*-weighted images obtained by the field-echo method yielded high signals in 10 out of 11 cases. It was difficult to differentiate between senile osteoporosis and multiple myeloma by MRI, but CT images clearly distinguished between them. The results suggested that fat-suppressive T1-contrast images and T2*-weighted images are useful in detecting lesions, especially focal low signal intensity lesions. Patients with the multiple-lesion-tumor type of disease were more likely to develop paralysis more than those with the diffuse myeloproliferative type. Thus, the tumor distribution classification established by Sezaki was useful in considering radiotherapy for the treatment of patients at risk of paralysis. Bone scintigraphy revealed accumulation only in spinal lesions caused by compression fractures, while CT appeared to be useful in localizing the diffuse myeloproliferative type of lesions. The problems associated with diagnosis by MRI are differentiation of multiple myeloma from senile osteoporosis and metastatic bone tumors of the spine. There are few specific findings in multiple myeloma. (K.H.)

  16. Magnetic resonance imaging in the diagnostics of multiple sclerosis

    Larsen, J.P.; Tjoerstad, K.; Kaass, B.; Oedegaard, H.

    1987-01-01

    Multiple sclerosis is an important and frequent neurological disease and the diagnosis might be difficult. The clinical criteria of multiple sclerosis and the role of laboratory examinations in the diagnosis of the disease are discussed. In particular the help offered by the magnetic resonance imaging method is the subject of this paper. Three patients are reported and discussed

  17. An efficient multiple exposure image fusion in JPEG domain

    Hebbalaguppe, Ramya; Kakarala, Ramakrishna

    2012-01-01

    In this paper, we describe a method to fuse multiple images taken with varying exposure times in the JPEG domain. The proposed algorithm finds its application in HDR image acquisition and image stabilization for hand-held devices like mobile phones, music players with cameras, digital cameras etc. Image acquisition at low light typically results in blurry and noisy images for hand-held camera's. Altering camera settings like ISO sensitivity, exposure times and aperture for low light image capture results in noise amplification, motion blur and reduction of depth-of-field respectively. The purpose of fusing multiple exposures is to combine the sharp details of the shorter exposure images with high signal-to-noise-ratio (SNR) of the longer exposure images. The algorithm requires only a single pass over all images, making it efficient. It comprises of - sigmoidal boosting of shorter exposed images, image fusion, artifact removal and saturation detection. Algorithm does not need more memory than a single JPEG macro block to be kept in memory making it feasible to be implemented as the part of a digital cameras hardware image processing engine. The Artifact removal step reuses the JPEGs built-in frequency analysis and hence benefits from the considerable optimization and design experience that is available for JPEG.

  18. MR imaging of multiple sclerosis in the cervical cord

    Shakudo, Miyuki; Takemoto, Kazumasa; Inoue, Yuichi; Onoyama, Yasuto; Nishimura, Masataka; Fujita, Masayuki.

    1987-01-01

    This is a case of a 34-year-old woman with multiple sclerosis (MS) in whom an enlarged cervical spinal cord with long T 1 and T 2 relaxation times was demonstrated on MR images. This report seems to be the first description of MR imaging of MS with an enlarged spinal cord. (author)

  19. The linearized inversion of the generalized interferometric multiple imaging

    Aldawood, Ali

    2016-09-06

    The generalized interferometric multiple imaging (GIMI) procedure can be used to image duplex waves and other higher order internal multiples. Imaging duplex waves could help illuminate subsurface zones that are not easily illuminated by primaries such as vertical and nearly vertical fault planes, and salt flanks. To image first-order internal multiple, the GIMI framework consists of three datuming steps, followed by applying the zero-lag cross-correlation imaging condition. However, the standard GIMI procedure yields migrated images that suffer from low spatial resolution, migration artifacts, and cross-talk noise. To alleviate these problems, we propose a least-squares GIMI framework in which we formulate the first two steps as a linearized inversion problem when imaging first-order internal multiples. Tests on synthetic datasets demonstrate the ability to localize subsurface scatterers in their true positions, and delineate a vertical fault plane using the proposed method. We, also, demonstrate the robustness of the proposed framework when imaging the scatterers or the vertical fault plane with erroneous migration velocities.

  20. The linearized inversion of the generalized interferometric multiple imaging

    Aldawood, Ali; Hoteit, Ibrahim; Alkhalifah, Tariq Ali

    2016-01-01

    such as vertical and nearly vertical fault planes, and salt flanks. To image first-order internal multiple, the GIMI framework consists of three datuming steps, followed by applying the zero-lag cross-correlation imaging condition. However, the standard GIMI

  1. Multiple images of our galaxy in closed, multiply connected cosmologies

    Fagundes, H.V.

    1985-01-01

    Friedmanian cosmology with multiply connected spatial sections allows multiple images of cosmic sources, in particular of the galaxy itself. This is illustrated with a specific example of a closed hyperbolic model and a brief mention of a spherical model. Such images may eventually become observable (or recognized as such), thus providing a new test of relativistic cosmology. (Author) [pt

  2. Permanent scatterer InSAR processing: Forsmark

    Dehls, John F.

    2006-04-01

    It has been speculated that slow, aseismic movement may be occurring along some of the fracture zones crosscutting the Forsmark area. The purpose of this study is to determine if it is possible to measure such movement using dInSAR. Differential SAR Interferometry (DInSAR) is a technique that compares the phases of multiple radar images of an area to measure surface change. The method has the potential to detect millimetric surface deformation along the sensor - target line-of-sight. Differences in phase between two images are easily viewed by combining, or interfering, the two phase-images. In the resulting image, the waves will either reinforce or cancel one another, depending upon the relative phases. The resulting image is called an interferogram and contains concentric bands of colour, or fringes, that are related to topography and/or surface deformation. New algorithms use many images acquired over a long time period to determine the movement history of individual objects, referred to as permanent scatterers. In the current project, standard PSInSAR processing was performed on 40 ERS-1 and ERS-2 scenes. The total area processed is approximately 1,500 km 2 . Slightly less than 20,000 permanent scatterers were identified.The highest densities were obtained along the coast and on the islands, where natural outcrops are more abundant. Two main classes of objects act as permanent scatterers in this area. The first are natural reflectors, such as rocks. The second are man-made reflectors, such as parts of buildings. Numerous local movements were found in the study area, relating to building subsidence, or compaction of anthropogenic fill. The dataset was divided into three groups for analysis, based upon the location of regional lineaments provided by SKB. Both statistical and geostatistical techniques were used. The median velocity of the three blocks did not differ by more than 0.2 mm/yr. This is not considered significant, given the possible magnitude of errors

  3. Permanent scatterer InSAR processing: Forsmark

    Dehls, John F [Geological Survey of Norway, Trondheim (Norway)

    2006-04-15

    It has been speculated that slow, aseismic movement may be occurring along some of the fracture zones crosscutting the Forsmark area. The purpose of this study is to determine if it is possible to measure such movement using dInSAR. Differential SAR Interferometry (DInSAR) is a technique that compares the phases of multiple radar images of an area to measure surface change. The method has the potential to detect millimetric surface deformation along the sensor - target line-of-sight. Differences in phase between two images are easily viewed by combining, or interfering, the two phase-images. In the resulting image, the waves will either reinforce or cancel one another, depending upon the relative phases. The resulting image is called an interferogram and contains concentric bands of colour, or fringes, that are related to topography and/or surface deformation. New algorithms use many images acquired over a long time period to determine the movement history of individual objects, referred to as permanent scatterers. In the current project, standard PSInSAR processing was performed on 40 ERS-1 and ERS-2 scenes. The total area processed is approximately 1,500 km{sup 2}. Slightly less than 20,000 permanent scatterers were identified.The highest densities were obtained along the coast and on the islands, where natural outcrops are more abundant. Two main classes of objects act as permanent scatterers in this area. The first are natural reflectors, such as rocks. The second are man-made reflectors, such as parts of buildings. Numerous local movements were found in the study area, relating to building subsidence, or compaction of anthropogenic fill. The dataset was divided into three groups for analysis, based upon the location of regional lineaments provided by SKB. Both statistical and geostatistical techniques were used. The median velocity of the three blocks did not differ by more than 0.2 mm/yr. This is not considered significant, given the possible magnitude of

  4. Autonomy of image and use of single or multiple sense modalities in original verbal image production.

    Khatena, J

    1978-06-01

    The use of a single or of multiple sense modalities in the production of original verbal images as related to autonomy of imagery was explored. 72 college adults were administered Onomatopoeia and Images and the Gordon Test of Visual Imagery Control. A modified scoring procedure for the Gordon scale differentiated imagers who were moderate or low in autonomy. The two groups produced original verbal images using multiple sense modalities more frequently than a single modality.

  5. Structured diagnostic imaging in patients with multiple trauma

    Linsenmaier, U.; Rieger, J.; Rock, C.; Pfeifer, K.J.; Reiser, M.; Kanz, K.G.

    2002-01-01

    Purpose. Development of a concept for structured diagnostic imaging in patients with multiple trauma.Material and methods. Evaluation of data from a prospective trial with over 2400 documented patients with multiple trauma. All diagnostic and therapeutic steps, primary and secondary death and the 90 days lethality were documented.Structured diagnostic imaging of multiple injured patients requires the integration of an experienced radiologist in an interdisciplinary trauma team consisting of anesthesia, radiology and trauma surgery. Radiology itself deserves standardized concepts for equipment, personnel and logistics to perform diagnostic imaging for a 24-h-coverage with constant quality.Results. This paper describes criteria for initiation of a shock room or emergency room treatment, strategies for documentation and interdisciplinary algorithms for the early clinical care coordinating diagnostic imaging and therapeutic procedures following standardized guidelines. Diagnostic imaging consists of basic diagnosis, radiological ABC-rule, radiological follow-up and structured organ diagnosis using CT. Radiological trauma scoring allows improved quality control of diagnosis and therapy of multiple injured patients.Conclusion. Structured diagnostic imaging of multiple injured patients leads to a standardization of diagnosis and therapy and ensures constant process quality. (orig.) [de

  6. Magnetic resonance imaging in clinically-definite multiple sclerosis

    Noakes, J.B.; Herkes, G.K.; Frith, J.A.

    1990-01-01

    Forty-two patients with clinically-definite multiple sclerosis were examined by magnetic resonance imaging using a 1.5-T instrument. Magnetic resonance imaging detected an abnormality in 90% of patients. In four patients, no lesions were demonstrated. The number, size and site of the lesions by magnetic resonance imaging were compared with the patients' clinical status and other variables. The Kurtzke disability status scale score increased in patients with corpus callosum atrophy, brainstem and basal ganglia lesions, and correlated with the total number of lesions. No correlation was shown between the findings of magnetic resonance imaging and disease duration, age, sex or pattern-reversal visual-evoked potentials. The variety of magnetic resonance images that could be obtained in patients with clinically-definite multiple sclerosis is highlighted. 24 refs., 8 figs., 1 tab

  7. MR imaging studies of multiple myeloma in the vertebral column

    Albert, S.; Leeds, N.E.

    1990-01-01

    This paper studies the sensitivity and characteristics of MR imaging in the diagnosis of myeloma in the vertebral column. The cervical, thoracic, and lumbar spines of 12 patients with known multiple myeloma were imaged with small flip angle, fast gradient-echo, proton-density (FPD) as well as spin-echo T1-weighted, T2-weighted, and intermediate (SE 2,000/20-30) imaging. The FPD images were acquired with pulse sequence gradient recalled acquisition in a steady state at a magnetic field strength of 1.5T with use of a license-plate and a circular surface coil

  8. Imaging the complex geometry of a magma reservoir using FEM-based linear inverse modeling of InSAR data: application to Rabaul Caldera, Papua New Guinea

    Ronchin, Erika; Masterlark, Timothy; Dawson, John; Saunders, Steve; Martì Molist, Joan

    2017-06-01

    We test an innovative inversion scheme using Green's functions from an array of pressure sources embedded in finite-element method (FEM) models to image, without assuming an a-priori geometry, the composite and complex shape of a volcano deformation source. We invert interferometric synthetic aperture radar (InSAR) data to estimate the pressurization and shape of the magma reservoir of Rabaul caldera, Papua New Guinea. The results image the extended shallow magmatic system responsible for a broad and long-term subsidence of the caldera between 2007 February and 2010 December. Elastic FEM solutions are integrated into the regularized linear inversion of InSAR data of volcano surface displacements in order to obtain a 3-D image of the source of deformation. The Green's function matrix is constructed from a library of forward line-of-sight displacement solutions for a grid of cubic elementary deformation sources. Each source is sequentially generated by removing the corresponding cubic elements from a common meshed domain and simulating the injection of a fluid mass flux into the cavity, which results in a pressurization and volumetric change of the fluid-filled cavity. The use of a single mesh for the generation of all FEM models avoids the computationally expensive process of non-linear inversion and remeshing a variable geometry domain. Without assuming an a-priori source geometry other than the configuration of the 3-D grid that generates the library of Green's functions, the geodetic data dictate the geometry of the magma reservoir as a 3-D distribution of pressure (or flux of magma) within the source array. The inversion of InSAR data of Rabaul caldera shows a distribution of interconnected sources forming an amorphous, shallow magmatic system elongated under two opposite sides of the caldera. The marginal areas at the sides of the imaged magmatic system are the possible feeding reservoirs of the ongoing Tavurvur volcano eruption of andesitic products on the

  9. Lossless Image Compression Based on Multiple-Tables Arithmetic Coding

    Rung-Ching Chen

    2009-01-01

    Full Text Available This paper is intended to present a lossless image compression method based on multiple-tables arithmetic coding (MTAC method to encode a gray-level image f. First, the MTAC method employs a median edge detector (MED to reduce the entropy rate of f. The gray levels of two adjacent pixels in an image are usually similar. A base-switching transformation approach is then used to reduce the spatial redundancy of the image. The gray levels of some pixels in an image are more common than those of others. Finally, the arithmetic encoding method is applied to reduce the coding redundancy of the image. To promote high performance of the arithmetic encoding method, the MTAC method first classifies the data and then encodes each cluster of data using a distinct code table. The experimental results show that, in most cases, the MTAC method provides a higher efficiency in use of storage space than the lossless JPEG2000 does.

  10. Imaging irregular magma reservoirs with InSAR and GPS observations: Application to Kilauea and Copahue volcanoes

    Lundgren, P.; Camacho, A.; Poland, M. P.; Miklius, A.; Samsonov, S. V.; Milillo, P.

    2013-12-01

    The availability of synthetic aperture radar (SAR) interferometry (InSAR) data has increased our awareness of the complexity of volcano deformation sources. InSAR's spatial completeness helps identify or clarify source process mechanisms at volcanoes (i.e. Mt. Etna east flank motion; Lazufre crustal magma body; Kilauea dike complexity) and also improves potential model realism. In recent years, Bayesian inference methods have gained widespread use because of their ability to constrain not only source model parameters, but also their uncertainties. They are computationally intensive, however, which tends to limit them to a few geometrically rather simple source representations (for example, spheres). An alternative approach involves solving for irregular pressure and/or density sources from a three-dimensional (3-D) grid of source/density cells. This method has the ability to solve for arbitrarily shaped bodies of constant absolute pressure/density difference. We compare results for both Bayesian (a Markov chain Monte Carlo algorithm) and the irregular source methods for two volcanoes: Kilauea, Hawaii, and Copahue, Argentina-Chile border. Kilauea has extensive InSAR and GPS databases from which to explore the results for the irregular method with respect to the Bayesian approach, prior models, and an extensive set of ancillary data. One caveat, however, is the current restriction in the irregular model inversion to volume-pressure sources (and at a single excess pressure change), which limits its application in cases where sources such as faults or dikes are present. Preliminary results for Kilauea summit deflation during the March 2011 Kamoamoa eruption suggests a northeast-elongated magma body lying roughly 1-1.5 km below the surface. Copahue is a southern Andes volcano that has been inflating since early 2012, with intermittent summit eruptive activity since late 2012. We have an extensive InSAR time series from RADARSAT-2 and COSMO-SkyMed data, although both are

  11. Utilization of multiple frequencies in 3D nonlinear microwave imaging

    Jensen, Peter Damsgaard; Rubæk, Tonny; Mohr, Johan Jacob

    2012-01-01

    The use of multiple frequencies in a nonlinear microwave algorithm is considered. Using multiple frequencies allows for obtaining the improved resolution available at the higher frequencies while retaining the regularizing effects of the lower frequencies. However, a number of different challenges...... at lower frequencies are used as starting guesses for reconstructions at higher frequencies. The performance is illustrated using simulated 2-D data and data obtained with the 3-D DTU microwave imaging system....

  12. Increasing Benefit of Magnetic Resonance Imaging in Multiple Sclerosis

    Pyhtinen, J.; Karttunen, A.; Tikkakoski, T. [Radiologian Klinikka, Oulu (Finland)

    2006-11-15

    Magnetic resonance imaging (MRI) has emerged as an essential tool of multiple sclerosis (MS) diagnosis and has opened up completely new prospects in MS research and treatment trials. It is a sensitive method that gives direct evidence of tissue pathology and has greatly increased our knowledge of MS. In clinical work, MRI is used to confirm and exclude the diagnosis of MS. The international recommendation is that every suspected MS patient should undergo at least one brain MRI. T2-weighted images are the standard tool in clinical work, and functional imaging methods are mainly used in MS research. The subtypes and the course of the disease cause variation in MRI findings. Here, we present a general overview of MR findings in MS. Brain, magnetic resonance imaging, multiple sclerosis, spinal cord.

  13. Increasing Benefit of Magnetic Resonance Imaging in Multiple Sclerosis

    Pyhtinen, J.; Karttunen, A.; Tikkakoski, T.

    2006-01-01

    Magnetic resonance imaging (MRI) has emerged as an essential tool of multiple sclerosis (MS) diagnosis and has opened up completely new prospects in MS research and treatment trials. It is a sensitive method that gives direct evidence of tissue pathology and has greatly increased our knowledge of MS. In clinical work, MRI is used to confirm and exclude the diagnosis of MS. The international recommendation is that every suspected MS patient should undergo at least one brain MRI. T2-weighted images are the standard tool in clinical work, and functional imaging methods are mainly used in MS research. The subtypes and the course of the disease cause variation in MRI findings. Here, we present a general overview of MR findings in MS. Brain, magnetic resonance imaging, multiple sclerosis, spinal cord

  14. A Performance Comparison Of A CFAR Ship Detection Algorithm Using Envisat, RadarSat, COSMO-SkyMed and Terra SAR-X Images

    Lorenzzetti, Joao A.; Paes, Rafael L.; Gheradi, Douglas M.

    2010-04-01

    In this paper we discuss the results of a CFAR ship detection algorithm for a series of SAR images of the Brazilian coast. The following configuration for the CFAR target/buffer/background windows gave the best results: 3x3/5x5/13x13 for a PFA of 0.1% for pixel spacing greater than 50m. For pixel spacing less than 50m, best results were achieved for PFA of 1% and windows sizes of 5x5/7x7/15x15. Results indicate that CFAR as implemented gave good results as measured by the Figure of Merit, as defined by Foulkes and Booth (2000), which varied from 0.79 for CosmoSkymed to 0.88 for Envisat. Results obtained should be taken so far only as an indication of the performance of the implemented CFAR due to the limited sample of images.

  15. Significance of multiple scattering in imaging through turbid media

    Zardecki, A.; Gerstl, S.A.W.

    1986-01-01

    The degradation of image quality in a turbid medium is analyzed within the framework of the small-angle approximation, the diffusion approximation, and a rigorous two-dimensional radiative transfer equation. These three approaches allow us to emphasize different aspects of the imaging problem when multiple scattering effects are important. For a medium with a forward-peaked phase function, the separation of multiple scattering into a series of scatterings of various order provides a fruitful technique. The use of the diffusion approximation and transport theory extends the determination of the modulation transfer function to a turbid medium with an arbitrary degree of anisotropy

  16. System and method for image registration of multiple video streams

    Dillavou, Marcus W.; Shum, Phillip Corey; Guthrie, Baron L.; Shenai, Mahesh B.; Deaton, Drew Steven; May, Matthew Benton

    2018-02-06

    Provided herein are methods and systems for image registration from multiple sources. A method for image registration includes rendering a common field of interest that reflects a presence of a plurality of elements, wherein at least one of the elements is a remote element located remotely from another of the elements and updating the common field of interest such that the presence of the at least one of the elements is registered relative to another of the elements.

  17. High-field MR imaging of spinal cord multiple sclerosis

    De La Paz, R.L.; Floris, R.; Norman, D.; Enzmann, D.R.

    1987-01-01

    Fifty-one high-field MR imaging studies (1.5 T, General Electric Signa) of the spinal cord were performed in 42 patients (27 female, 15 male; mean age, 40 years) with clinically definitive (n = 34) or probable (n = 8) multiple sclerosis and suspected spinal cord lesions. MR imaging showed focal spinal cord abnormalities in 38 (75%) of 51 studies. T2-weighted images were abnormal (showing foci of high signal intensity) in 38 studies, T1-weighted images were abnormal (showing areas of low signal intensity or mass effect) in 16 (42%) of 38, and GRASS images were abnormal (showing foci of high signal intensity) in 9 (82%) of 11 cases. Brain MR imaging showed periventricular lesions typical of multiple sclerosis in 34 (81%) of 42 studies. Spinal cord studies were positive in eight cases with normal brain MR images, and brain studies were positive in 13 instances of normal spinal cord MR images. Four lesions were at the cervicomedullary junction, 44 in the cervical spinal cord, and three in the thoracic cord. Mass effect in cord lesions, simulating neoplasm, was seen in seven patients during the acute symptomatic phase. Serial studies in three patients with decreasing symptoms showed a reduction after 3-4 weeks and resolution of the mass effect after 2-6 months

  18. Diffusion weighted MR imaging in the diagnosis of multiple sclerosis

    Hagen, T.; Schweigerer-Schroeter, G.; Wellnitz, J.; Wuerstle, T.

    2000-01-01

    Magnetic resonance (MR) imaging is one of the best methods in diagnosis of multiple sclerosis, particularly in disclosure of active demyelinating lesions. Aim of this study was to compare diffusion weighted imaging and contrast enhancement in the detection of active lesions. A MR study with a contrast enhanced T1-weighted pulse sequence with magnetization transfer presaturation and a diffusion weighted echoplanar pulse sequence (b=1000 s/mm 2 ) was performed in 17 patients (11 women, 6 men) with multiple sclerosis. 29 of 239 lesions showed an increased signal intensity in diffusion weighted imaging, 24 lesions a contrast enhancement, but only 16 lesions were visible in both pulse sequences. In patients with short clinical symptomatology significant more lesions could be detected with diffusion-weighted pulse sequence in comparison to patients with long standing symptomatology showing more lesions with contrast enhancement. Hence it is likely, that both pulse sequences detect different histopathologic changes. The early detection of demyelinating lesions in diffusion weighted imaging is attributed to the extracellular edema, however the contrast enhancement is caused by a blood brain barrier abnormality. It can be expected that diffusion weighted imaging will have a high impact on imaging of multiple sclerosis not only in therapeutic trials, but also in clinical routine. (orig.) [de

  19. Challenges in clinical studies with multiple imaging probes

    Krohn, Kenneth A.; O'Sullivan, Finbarr; Crowley, John; Eary, Janet F.; Linden, Hannah M.; Link, Jeanne M.; Mankoff, David A.; Muzi, Mark; Rajendran, Joseph G.; Spence, Alexander M.; Swanson, Kristin R.

    2007-01-01

    This article addresses two related issues: (a) When a new imaging agent is proposed, how does the imager integrate it with other biomarkers, either sampled or imaged? (b) When we have multiple imaging agents, is the information additive or duplicative and how is this objectively determined? Molecular biology is leading to new treatment options with reduced normal tissue toxicity, and imaging should have a role in objectively evaluating new treatments. There are two roles for molecular characterization of disease. Molecular imaging measurements before therapy help predict the aggressiveness of disease and identify therapeutic targets and, therefore, help choose the optimal therapy for an individual. Measurements of specific biochemical processes made during or after therapy should be sensitive measures of tumor response. The rules of evidence are not fully developed for the prognostic role of imaging biomarkers, but the potential of molecular imaging provides compelling motivation to push forward with convincing validation studies. New imaging procedures need to be characterized for their effectiveness under realistic clinical conditions to improve the management of patients and achieve a better outcome. The purpose of this article is to promote a critical discussion within the molecular imaging community because our future value to the overall biomedical community will be in supporting better treatment outcomes rather than in detection

  20. Seismic imaging beneath an InSAR anomaly in eastern Washington State: Shallow faulting associated with an earthquake swarm in a low-hazard area

    Stephenson, William J.; Odum, Jackson K.; Wicks, Chuck; Pratt, Thomas L.; Blakely, Richard J.

    2016-01-01

    In 2001, a rare swarm of small, shallow earthquakes beneath the city of Spokane, Washington, caused ground shaking as well as audible booms over a five‐month period. Subsequent Interferometric Synthetic Aperture Radar (InSAR) data analysis revealed an area of surface uplift in the vicinity of the earthquake swarm. To investigate the potential faults that may have caused both the earthquakes and the topographic uplift, we collected ∼3  km of high‐resolution seismic‐reflection profiles to image the upper‐source region of the swarm. The two profiles reveal a complex deformational pattern within Quaternary alluvial, fluvial, and flood deposits, underlain by Tertiary basalts and basin sediments. At least 100 m of arching on a basalt surface in the upper 500 m is interpreted from both the seismic profiles and magnetic modeling. Two west‐dipping faults deform Quaternary sediments and project to the surface near the location of the Spokane fault defined from modeling of the InSAR data.

  1. The July 11, 1995 Myanmar-China earthquake: A representative event in the bookshelf faulting system of southeastern Asia observed from JERS-1 SAR images

    Ji, Lingyun; Wang, Qingliang; Xu, Jing; Ji, Cunwei

    2017-03-01

    On July 11, 1995, an Mw 6.8 earthquake struck eastern Myanmar near the Chinese border; hereafter referred to as the 1995 Myanmar-China earthquake. Coseismic surface displacements associated with this event are identified from JERS-1 (Japanese Earth Resources Satellite-1) SAR (Synthetic Aperture Radar) images. The largest relative displacement reached 60 cm in the line-of-sight direction. We speculate that a previously unrecognized dextral strike-slip subvertical fault striking NW-SE was responsible for this event. The coseismic slip distribution on the fault planes is inverted based on the InSAR-derived deformation. The results indicate that the fault slip was confined to two lobes. The maximum slip reached approximately 2.5 m at a depth of 5 km in the northwestern part of the focal region. The inverted geodetic moment was approximately Mw = 6.69, which is consistent with seismological results. The 1995 Myanmar-China earthquake is one of the largest recorded earthquakes that has occurred around the "bookshelf faulting" system between the Sagaing fault in Myanmar and the Red River fault in southwestern China.

  2. Automatic plankton image classification combining multiple view features via multiple kernel learning.

    Zheng, Haiyong; Wang, Ruchen; Yu, Zhibin; Wang, Nan; Gu, Zhaorui; Zheng, Bing

    2017-12-28

    Plankton, including phytoplankton and zooplankton, are the main source of food for organisms in the ocean and form the base of marine food chain. As the fundamental components of marine ecosystems, plankton is very sensitive to environment changes, and the study of plankton abundance and distribution is crucial, in order to understand environment changes and protect marine ecosystems. This study was carried out to develop an extensive applicable plankton classification system with high accuracy for the increasing number of various imaging devices. Literature shows that most plankton image classification systems were limited to only one specific imaging device and a relatively narrow taxonomic scope. The real practical system for automatic plankton classification is even non-existent and this study is partly to fill this gap. Inspired by the analysis of literature and development of technology, we focused on the requirements of practical application and proposed an automatic system for plankton image classification combining multiple view features via multiple kernel learning (MKL). For one thing, in order to describe the biomorphic characteristics of plankton more completely and comprehensively, we combined general features with robust features, especially by adding features like Inner-Distance Shape Context for morphological representation. For another, we divided all the features into different types from multiple views and feed them to multiple classifiers instead of only one by combining different kernel matrices computed from different types of features optimally via multiple kernel learning. Moreover, we also applied feature selection method to choose the optimal feature subsets from redundant features for satisfying different datasets from different imaging devices. We implemented our proposed classification system on three different datasets across more than 20 categories from phytoplankton to zooplankton. The experimental results validated that our system

  3. Magnetic resonance imaging abnormalities in multiple sclerosis: A review

    Saharian, M. A.; Shakaouri Rad, A.; Motamedi, M.; Pakdaman, H.; Radue, E. W.

    2007-01-01

    :During the last two decades, magnetic resonance imaging has been widely used In the diagnosis and treatment monitoring of multiple sclerosis. MRI, both conventional and non conventional methods, has transformed all aspects of M S research and clinical practice in recent years. Although advanced imaging methods have added much more to our knowledge about pathogenesis and natural history of the disease but their cost, availability, complexity and lack of validation have limited their use in routine clinical practice. Conventional MR techniques including proton density, T1/T2-Weighted images and fluid- attenuated inversion recovery sequences are now accepted in standard protocols for diagnosis and treatment outcome measures in clinical trials of multiple sclerosis. This review will focus on the type, morphology and evolution of M S lesions regarding conventional MRI and their use for treatment monitoring in daily clinical practice

  4. SAR Subsets for Selected Field Sites, 2007-2010

    National Aeronautics and Space Administration — ABSTRACT: This data set provides Synthetic Aperture Radar (SAR) images for 42 selected sites from various terrestrial ecology and meteorological monitoring networks...

  5. SAR Subsets for Selected Field Sites, 2007-2010

    National Aeronautics and Space Administration — This data set provides Synthetic Aperture Radar (SAR) images for 42 selected sites from various terrestrial ecology and meteorological monitoring networks including...

  6. AUTOMATED WETLAND DELINEATION FROM MULTI-FREQUENCY AND MULTI-POLARIZED SAR IMAGES IN HIGH TEMPORAL AND SPATIAL RESOLUTION

    L. Moser

    2016-06-01

    Full Text Available Water scarcity is one of the main challenges posed by the changing climate. Especially in semi-arid regions where water reservoirs are filled during the very short rainy season, but have to store enough water for the extremely long dry season, the intelligent handling of water resources is vital. This study focusses on Lac Bam in Burkina Faso, which is the largest natural lake of the country and of high importance for the local inhabitants for irrigated farming, animal watering, and extraction of water for drinking and sanitation. With respect to the competition for water resources an independent area-wide monitoring system is essential for the acceptance of any decision maker. The following contribution introduces a weather and illumination independent monitoring system for the automated wetland delineation with a high temporal (about two weeks and a high spatial sampling (about five meters. The similarities of the multispectral and multi-polarized SAR acquisitions by RADARSAT-2 and TerraSAR-X are studied as well as the differences. The results indicate that even basic approaches without pre-classification time series analysis or post-classification filtering are already enough to establish a monitoring system of prime importance for a whole region.

  7. Generalized internal multiple imaging (GIMI) using Feynman-like diagrams

    Zuberi, M. A. H.

    2014-05-19

    Single scattering events recorded in surface seismic data do not fully illuminate the subsurface structure, especially if it is complicated. In such cases, multiple internal scatterings (internal multiples) can help improve the illumination. We devise a generalized internal multiple imaging (GIMI) procedure that maps internal multiple energy to their true location with a relatively mild addition to the computational cost. GIMI theory relies heavily on seismic interferometry, which often involves cumbersome algebra, especially when one is dealing with high-order terms in the perturbation series. To make the derivations, and inference of the results easier, we introduce Feynman-like diagrams to represent different terms of the perturbation series (solution to the Lippman–Schwinger equation). The rules we define for the diagrams allow operations like convolution and cross-correlation in the series to be compressed in diagram form. The application of the theory to a double scattering example demonstrates the power of the method.

  8. Generalized internal multiple imaging (GIMI) using Feynman-like diagrams

    Zuberi, M. A. H.; Alkhalifah, Tariq Ali

    2014-01-01

    Single scattering events recorded in surface seismic data do not fully illuminate the subsurface structure, especially if it is complicated. In such cases, multiple internal scatterings (internal multiples) can help improve the illumination. We devise a generalized internal multiple imaging (GIMI) procedure that maps internal multiple energy to their true location with a relatively mild addition to the computational cost. GIMI theory relies heavily on seismic interferometry, which often involves cumbersome algebra, especially when one is dealing with high-order terms in the perturbation series. To make the derivations, and inference of the results easier, we introduce Feynman-like diagrams to represent different terms of the perturbation series (solution to the Lippman–Schwinger equation). The rules we define for the diagrams allow operations like convolution and cross-correlation in the series to be compressed in diagram form. The application of the theory to a double scattering example demonstrates the power of the method.

  9. Suitable post processing algorithms for X-ray imaging using oversampled displaced multiple images

    Thim, J; Reza, S; Nawaz, K; Norlin, B; O'Nils, M; Oelmann, B

    2011-01-01

    X-ray imaging systems such as photon counting pixel detectors have a limited spatial resolution of the pixels, based on the complexity and processing technology of the readout electronics. For X-ray imaging situations where the features of interest are smaller than the imaging system pixel size, and the pixel size cannot be made smaller in the hardware, alternative means of resolution enhancement require to be considered. Oversampling with the usage of multiple displaced images, where the pixels of all images are mapped to a final resolution enhanced image, has proven a viable method of reaching a sub-pixel resolution exceeding the original resolution. The effectiveness of the oversampling method declines with the number of images taken, the sub-pixel resolution increases, but relative to a real reduction of imaging pixel sizes yielding a full resolution image, the perceived resolution from the sub-pixel oversampled image is lower. This is because the oversampling method introduces blurring noise into the mapped final images, and the blurring relative to full resolution images increases with the oversampling factor. One way of increasing the performance of the oversampling method is by sharpening the images in post processing. This paper focus on characterizing the performance increase of the oversampling method after the use of some suitable post processing filters, for digital X-ray images specifically. The results show that spatial domain filters and frequency domain filters of the same type yield indistinguishable results, which is to be expected. The results also show that the effectiveness of applying sharpening filters to oversampled multiple images increase with the number of images used (oversampling factor), leaving 60-80% of the original blurring noise after filtering a 6 x 6 mapped image (36 images taken), where the percentage is depending on the type of filter. This means that the effectiveness of the oversampling itself increase by using sharpening

  10. Textureless Macula Swelling Detection with Multiple Retinal Fundus Images

    Giancardo, Luca [ORNL; Meriaudeau, Fabrice [ORNL; Karnowski, Thomas Paul [ORNL; Tobin Jr, Kenneth William [ORNL; Grisan, Enrico [University of Padua, Padua, Italy; Favaro, Paolo [Heriot-Watt University, Edinburgh; Ruggeri, Alfredo [University of Padua, Padua, Italy; Chaum, Edward [University of Tennessee, Knoxville (UTK)

    2010-01-01

    Retinal fundus images acquired with non-mydriatic digital fundus cameras are a versatile tool for the diagnosis of various retinal diseases. Because of the ease of use of newer camera models and their relatively low cost, these cameras can be employed by operators with limited training for telemedicine or Point-of-Care applications. We propose a novel technique that uses uncalibrated multiple-view fundus images to analyse the swelling of the macula. This innovation enables the detection and quantitative measurement of swollen areas by remote ophthalmologists. This capability is not available with a single image and prone to error with stereo fundus cameras. We also present automatic algorithms to measure features from the reconstructed image which are useful in Point-of-Care automated diagnosis of early macular edema, e.g., before the appearance of exudation. The technique presented is divided into three parts: first, a preprocessing technique simultaneously enhances the dark microstructures of the macula and equalises the image; second, all available views are registered using non-morphological sparse features; finally, a dense pyramidal optical flow is calculated for all the images and statistically combined to build a naiveheight- map of the macula. Results are presented on three sets of synthetic images and two sets of real world images. These preliminary tests show the ability to infer a minimum swelling of 300 microns and to correlate the reconstruction with the swollen location.

  11. Alteration zone Mapping in the Meiduk and Sar Cheshmeh Porphyry Copper Mining Districts of Iran using Advanced Land Imager (ALI Satellite Data

    A. Beiranvand Pour

    2015-10-01

    Full Text Available This study evaluates the capability of Earth Observing-1 (EO1 Advanced Land Imager (ALI data for hydrothermal alteration mapping in the Meiduk and Sar Cheshmeh porphyry copper mining districts, SE Iran. Feature-oriented principal components selection, 4/2, 8/9, 5/4 band ratioing were applied to ALI data for enhancing the hydrothermally altered rocks associated with porphyry copper mineralization, lithological units and vegetation. Mixture-tuned matched-filtering (MTMF was tested to discriminate the hydrothermal alteration areas of porphyry copper mineralization from surrounding environment using the shortwave infrared bands of ALI. Results indicate that the tested methods are able to yield spectral information for identifying vegetation, iron oxide/hydroxide and clay minerals, lithological units and the discrimination of hydrothermally altered rocks from unaltered rocks using ALI data.

  12. SAR Raw Data Generation for Complex Airport Scenes

    Jia Li

    2014-10-01

    Full Text Available The method of generating the SAR raw data of complex airport scenes is studied in this paper. A formulation of the SAR raw signal model of airport scenes is given. Via generating the echoes from the background, aircrafts and buildings, respectively, the SAR raw data of the unified SAR imaging geometry is obtained from their vector additions. The multipath scattering and the shadowing between the background and different ground covers of standing airplanes and buildings are analyzed. Based on the scattering characteristics, coupling scattering models and SAR raw data models of different targets are given, respectively. A procedure is given to generate the SAR raw data of airport scenes. The SAR images from the simulated raw data demonstrate the validity of the proposed method.

  13. Imaging moving objects from multiply scattered waves and multiple sensors

    Miranda, Analee; Cheney, Margaret

    2013-01-01

    In this paper, we develop a linearized imaging theory that combines the spatial, temporal and spectral components of multiply scattered waves as they scatter from moving objects. In particular, we consider the case of multiple fixed sensors transmitting and receiving information from multiply scattered waves. We use a priori information about the multipath background. We use a simple model for multiple scattering, namely scattering from a fixed, perfectly reflecting (mirror) plane. We base our image reconstruction and velocity estimation technique on a modification of a filtered backprojection method that produces a phase-space image. We plot examples of point-spread functions for different geometries and waveforms, and from these plots, we estimate the resolution in space and velocity. Through this analysis, we are able to identify how the imaging system depends on parameters such as bandwidth and number of sensors. We ultimately show that enhanced phase-space resolution for a distribution of moving and stationary targets in a multipath environment may be achieved using multiple sensors. (paper)

  14. Image Based Solution to Occlusion Problem for Multiple Robots Navigation

    Taj Mohammad Khan

    2012-04-01

    Full Text Available In machine vision, occlusions problem is always a challenging issue in image based mapping and navigation tasks. This paper presents a multiple view vision based algorithm for the development of occlusion-free map of the indoor environment. The map is assumed to be utilized by the mobile robots within the workspace. It has wide range of applications, including mobile robot path planning and navigation, access control in restricted areas, and surveillance systems. We used wall mounted fixed camera system. After intensity adjustment and background subtraction of the synchronously captured images, the image registration was performed. We applied our algorithm on the registered images to resolve the occlusion problem. This technique works well even in the existence of total occlusion for a longer period.

  15. Observation of a Large Landslide on La Reunion Island Using Differential Sar Interferometry (JERS and Radarsat and Correlation of Optical (Spot5 and Aerial Images

    Christophe Delacourt

    2009-01-01

    Full Text Available Slope instabilities are one of the most important geo-hazards in terms of socio-economic costs. The island of La Réunion (Indian Ocean is affected by constant slope movements and huge landslides due to a combination of rough topography, wet tropical climate and its specific geological context. We show that remote sensing techniques (Differential SAR Interferometry and correlation of optical images provide complementary means to characterize landslides on a regional scale. The vegetation cover generally hampers the analysis of C–band interferograms. We used JERS-1 images to show that the L-band can be used to overcome the loss of coherence observed in Radarsat C-band interferograms. Image correlation was applied to optical airborne and SPOT 5 sensors images. The two techniques were applied to a landslide near the town of Hellbourg in order to assess their performance for detecting and quantifying the ground motion associated to this landslide. They allowed the mapping of the unstable areas. Ground displacement of about 0.5 m yr-1 was measured.

  16. Imaging of multiple endocrine neoplasia (MEN II A)

    Tanaka, Hiroko; Kohno, Atsushi; Nojiri, Yoko

    1995-01-01

    A retrospective review of diagnostic imaging findings of 20 cases of multiple endocrine neoplasia II A (MEN II A) was performed. The characteristic findings of thyroidal medullary carcinomas were relatively well-defined hypo- to isoechoic masses on US and coarse calcifications on plain X-ray. The pheochromocytomas were smaller in size and less enhancing than the sporadic ones, and they revealed marked high intensity on T2WI of MRI. We consider that these imaging findings were useful for the supplementary diagnosis of MEN II A. (author)

  17. Measuring multiple nano-textured areas simultaneously with imaging scatterometry

    Madsen, Jonas Skovlund; Hansen, Poul Erik; Bilenberg, Brian

    2017-01-01

    and areas with defects can be avoided. These advantages make imaging scatterometry a very effective and user-friendly characterization method and allow us to determine the homogeneity of a nano- Textured surface by performing pixel-wise analyses. In the analysis an inverse modelling approach is used, where...... measured diffraction efficiencies are compared to simulated diffraction efficiencies using a least-square fitting approach. We demonstrate an imaging scatterometry setup built into an optical microscope. The setup is capable of measuring multiple 2D gratings with pitches of 200 nm simultaneously...

  18. Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR.

    Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

    2018-02-11

    In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner.

  19. Sensor-Oriented Path Planning for Multiregion Surveillance with a Single Lightweight UAV SAR

    Li, Jincheng; Chen, Jie; Wang, Pengbo; Li, Chunsheng

    2018-01-01

    In the surveillance of interested regions by unmanned aerial vehicle (UAV), system performance relies greatly on the motion control strategy of the UAV and the operation characteristics of the onboard sensors. This paper investigates the 2D path planning problem for the lightweight UAV synthetic aperture radar (SAR) system in an environment of multiple regions of interest (ROIs), the sizes of which are comparable to the radar swath width. Taking into account the special requirements of the SAR system on the motion of the platform, we model path planning for UAV SAR as a constrained multiobjective optimization problem (MOP). Based on the fact that the UAV route can be designed in the map image, an image-based path planner is proposed in this paper. First, the neighboring ROIs are merged by the morphological operation. Then, the parts of routes for data collection of the ROIs can be located according to the geometric features of the ROIs and the observation geometry of UAV SAR. Lastly, the route segments for ROIs surveillance are connected by a path planning algorithm named the sampling-based sparse A* search (SSAS) algorithm. Simulation experiments in real scenarios demonstrate that the proposed sensor-oriented path planner can improve the reconnaissance performance of lightweight UAV SAR greatly compared with the conventional zigzag path planner. PMID:29439447

  20. Evaluation of the Wishart test statistics for polarimetric SAR data

    Skriver, Henning; Nielsen, Allan Aasbjerg; Conradsen, Knut

    2003-01-01

    A test statistic for equality of two covariance matrices following the complex Wishart distribution has previously been used in new algorithms for change detection, edge detection and segmentation in polarimetric SAR images. Previously, the results for change detection and edge detection have been...... quantitatively evaluated. This paper deals with the evaluation of segmentation. A segmentation performance measure originally developed for single-channel SAR images has been extended to polarimetric SAR images, and used to evaluate segmentation for a merge-using-moment algorithm for polarimetric SAR data....

  1. PSInSAR technology and its use for monitoring of the Earth's surface deformation; Technologia PSInSAR a jej vyuzitie na monitorovanie deformacii zemskeho povrchu

    Batorova, K [Univerzita Komenskeho v Bratislave, Prirodovedecka fakulta, Katedra inzinierskej geologie, 84215 Bratislava (Slovakia)

    2012-04-25

    Method of permanent reflex points (PSInSAR) allows to monitor the time evolution of deformations of the Earth's surface with a millimeter precision. For deformation size determination there are used the maps of movement speed or time delay of line set of data that are obtained by evaluating of SAR images. SAR files must be processed using the basic mathematical calculation presented in the work, with an emphasis on the parameters used in geology. Extensive processing of multiple SAR imagery showed that they can be used during monitoring of the field with an accurate identification of the objects on the Earth's surface, which provide a stable reflection of radar rays transmitted from the satellite. These objects are known as permanent reflection points (PS). PS can be geo-referenced, allowing accurate determination of the movement size of the Earth's surface deformation. In this paper an example of using of PSInSAR technology for monitoring of slope movements on the territory of Slovakia is presented. (authors)

  2. Keynote presentation : SAR systems

    Halsema, D. van; Otten, M.P.G.; Maas, A.P.M.; Bolt, R.J.; Anitori, L.

    2011-01-01

    Synthetic Aperture Radar (SAR) systems are becoming increasingly important sensors in as well the military environment as in the civilian market. In this keynote presentation an overview will be given over more than 2 decades of SAR system∼ and SAR application development at TNO in the Netherlands.

  3. Parallel multiple instance learning for extremely large histopathology image analysis.

    Xu, Yan; Li, Yeshu; Shen, Zhengyang; Wu, Ziwei; Gao, Teng; Fan, Yubo; Lai, Maode; Chang, Eric I-Chao

    2017-08-03

    Histopathology images are critical for medical diagnosis, e.g., cancer and its treatment. A standard histopathology slice can be easily scanned at a high resolution of, say, 200,000×200,000 pixels. These high resolution images can make most existing imaging processing tools infeasible or less effective when operated on a single machine with limited memory, disk space and computing power. In this paper, we propose an algorithm tackling this new emerging "big data" problem utilizing parallel computing on High-Performance-Computing (HPC) clusters. Experimental results on a large-scale data set (1318 images at a scale of 10 billion pixels each) demonstrate the efficiency and effectiveness of the proposed algorithm for low-latency real-time applications. The framework proposed an effective and efficient system for extremely large histopathology image analysis. It is based on the multiple instance learning formulation for weakly-supervised learning for image classification, segmentation and clustering. When a max-margin concept is adopted for different clusters, we obtain further improvement in clustering performance.

  4. Exploring manifold structure of face images via multiple graphs

    Alghamdi, Masheal

    2013-01-01

    Geometric structure in the data provides important information for face image recognition and classification tasks. Graph regularized non-negative matrix factorization (GrNMF) performs well in this task. However, it is sensitive to the parameters selection. Wang et al. proposed multiple graph regularized non-negative matrix factorization (MultiGrNMF) to solve the parameter selection problem by testing it on medical images. In this paper, we introduce the MultiGrNMF algorithm in the context of still face Image classification, and conduct a comparative study of NMF, GrNMF, and MultiGrNMF using two well-known face databases. Experimental results show that MultiGrNMF outperforms NMF and GrNMF for most cases.

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

    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.

  6. Exploring manifold structure of face images via multiple graphs

    Alghamdi, Masheal

    2013-12-24

    Geometric structure in the data provides important information for face image recognition and classification tasks. Graph regularized non-negative matrix factorization (GrNMF) performs well in this task. However, it is sensitive to the parameters selection. Wang et al. proposed multiple graph regularized non-negative matrix factorization (MultiGrNMF) to solve the parameter selection problem by testing it on medical images. In this paper, we introduce the MultiGrNMF algorithm in the context of still face Image classification, and conduct a comparative study of NMF, GrNMF, and MultiGrNMF using two well-known face databases. Experimental results show that MultiGrNMF outperforms NMF and GrNMF for most cases.

  7. Wave directional spectrum from SAR imagery

    Fernandes, A.A.; Sarma, Y.V.B.; Menon, H.B.; Vethamony, P.

    < 2m and the zero-crossing period during the satellite overpass is small (< 6s, �O�O < 60m). We therefore utilized the visit of one of the authors (Sarma) to the Southampton Oceanographic Centre, U.K., to procure two ERS-1 digital image mode SAR...-dimensional FFT as well as a computer program for downloading SAR data from CCT. Finally we owe a debt of gratitude to J C da Silva, Southampton Oceanographic Centre, U K for sharing some of his SAR data with us. References Allan T. D. (Ed) (1983...

  8. What is missing? An operational inundation mapping framework by SAR data

    Shen, X.; Anagnostou, E. N.; Zeng, Z.; Kettner, A.; Hong, Y.

    2017-12-01

    Compared to optical sensors, synthetic aperture radar (SAR) works all-day all-weather. In addition, its spatial resolution does not decrease with the height of the platform and is thus applicable to a range of important studies. However, existing studies did not address the operational demands of real-time inundation mapping. The direct proof is that no water body product exists for any SAR-based satellites. Then what is missing between science and products? Automation and quality. What makes it so difficult to develop an operational inundation mapping technique based on SAR data? Spectrum-wise, unlike optical water indices such as MNDWI, AWEI etc., where a relative constant threshold may apply across acquisition of images, regions and sensors, the threshold to separate water from non-water pixels in each SAR images has to be individually chosen. The optimization of the threshold is the first obstacle to the automation of the SAR data algorithm. Morphologically, the quality and reliability of the results have been compromised by over-detection caused by smooth surface and shadowing area, the noise-like speckle and under-detection caused by strong-scatter disturbance. In this study, we propose a three-step framework that addresses all aforementioned issues of operational inundation mapping by SAR data. The framework consists of 1) optimization of Wishart distribution parameters of single/dual/fully-polarized SAR data, 2) morphological removal of over-detection, and 3) machine-learning based removal of under-detection. The framework utilizes not only the SAR data, but also the synergy of digital elevation model (DEM), and optical sensor-based products of fine resolution, including the water probability map, land cover classification map (optional), and river width. The framework has been validated throughout multiple areas in different parts of the world using different satellite SAR data and globally available ancillary data products. Therefore, it has the potential

  9. Optical image encryption scheme with multiple light paths based on compressive ghost imaging

    Zhu, Jinan; Yang, Xiulun; Meng, Xiangfeng; Wang, Yurong; Yin, Yongkai; Sun, Xiaowen; Dong, Guoyan

    2018-02-01

    An optical image encryption method with multiple light paths is proposed based on compressive ghost imaging. In the encryption process, M random phase-only masks (POMs) are generated by means of logistic map algorithm, and these masks are then uploaded to the spatial light modulator (SLM). The collimated laser light is divided into several beams by beam splitters as it passes through the SLM, and the light beams illuminate the secret images, which are converted into sparse images by discrete wavelet transform beforehand. Thus, the secret images are simultaneously encrypted into intensity vectors by ghost imaging. The distances between the SLM and secret images vary and can be used as the main keys with original POM and the logistic map algorithm coefficient in the decryption process. In the proposed method, the storage space can be significantly decreased and the security of the system can be improved. The feasibility, security and robustness of the method are further analysed through computer simulations.

  10. SAR Ambiguity Study for the Cassini Radar

    Hensley, Scott; Im, Eastwood; Johnson, William T. K.

    1993-01-01

    The Cassini Radar's synthetic aperture radar (SAR) ambiguity analysis is unique with respect to other spaceborne SAR ambiguity analyses owing to the non-orbiting spacecraft trajectory, asymmetric antenna pattern, and burst mode of data collection. By properly varying the pointing, burst mode timing, and radar parameters along the trajectory this study shows that the signal-to-ambiguity ratio of better than 15 dB can be achieved for all images obtained by the Cassini Radar.

  11. Estimating Elevation Angles From SAR Crosstalk

    Freeman, Anthony

    1994-01-01

    Scheme for processing polarimetric synthetic-aperture-radar (SAR) image data yields estimates of elevation angles along radar beam to target resolution cells. By use of estimated elevation angles, measured distances along radar beam to targets (slant ranges), and measured altitude of aircraft carrying SAR equipment, one can estimate height of target terrain in each resolution cell. Monopulselike scheme yields low-resolution topographical data.

  12. Importance of multidetector CT imaging in multiple trauma

    Linsenmaier, U.; Geyer, L.L.; Reiser, M.; Wirth, S.; Koerner, M.

    2014-01-01

    Diagnostic imaging of complex multiple trauma remains a challenge for any department providing modern emergency radiology (ER) service. An early and comprehensive approach for ER imaging is crucial for a priority-oriented and timely therapy concept with the aim of identifying potentially life-threatening injuries early and initiating appropriate treatment. The basic diagnostic approach still consists of focused ultrasound using focused assessment with sonography for trauma (FAST) and conventional radiography (CR), usually limited to a single supine chest x-ray for triaging patients undergoing immediate operations. Multidetector computed tomography (MDCT) has become established as early whole body CT (WBCT) as the undisputable diagnostic method. The detection rate of injuries by WBCT is outstanding and it improves the probability of survival by 20-25 % compared with all other previous methods. At the same time, the spatial and temporal resolution of MDCT was improved resulting in considerably shortened examination times but WBCT is still associated with a significant radiation exposure, even in the acute single use setting. Using modern scanner and dose reduction technology, including iterative reconstruction, a dose reduction of up to 40 % could be achieved. The substantial number of images in WBCT is another challenge; images must be processed priority-oriented, read and transferred to the picture archiving and communications system (PACS). For rapid diagnosis, volume image reading (VIR) offers additional options to keep the diagnostic process on time. Modern WBCT after multiple trauma is performed early, comprehensively and personalized so that WBCT improves the probability of survival by 20-25 %. (orig.) [de

  13. AUTOMATIC 3D MAPPING USING MULTIPLE UNCALIBRATED CLOSE RANGE IMAGES

    M. Rafiei

    2013-09-01

    Full Text Available Automatic three-dimensions modeling of the real world is an important research topic in the geomatics and computer vision fields for many years. By development of commercial digital cameras and modern image processing techniques, close range photogrammetry is vastly utilized in many fields such as structure measurements, topographic surveying, architectural and archeological surveying, etc. A non-contact photogrammetry provides methods to determine 3D locations of objects from two-dimensional (2D images. Problem of estimating the locations of 3D points from multiple images, often involves simultaneously estimating both 3D geometry (structure and camera pose (motion, it is commonly known as structure from motion (SfM. In this research a step by step approach to generate the 3D point cloud of a scene is considered. After taking images with a camera, we should detect corresponding points in each two views. Here an efficient SIFT method is used for image matching for large baselines. After that, we must retrieve the camera motion and 3D position of the matched feature points up to a projective transformation (projective reconstruction. Lacking additional information on the camera or the scene makes the parallel lines to be unparalleled. The results of SfM computation are much more useful if a metric reconstruction is obtained. Therefor multiple views Euclidean reconstruction applied and discussed. To refine and achieve the precise 3D points we use more general and useful approach, namely bundle adjustment. At the end two real cases have been considered to reconstruct (an excavation and a tower.

  14. Training Convolutional Neural Networks for Translational Invariance on SAR ATR

    Malmgren-Hansen, David; Engholm, Rasmus; Østergaard Pedersen, Morten

    2016-01-01

    In this paper we present a comparison of the robustness of Convolutional Neural Networks (CNN) to other classifiers in the presence of uncertainty of the objects localization in SAR image. We present a framework for simulating simple SAR images, translating the object of interest systematically...

  15. Use of SAR data for proliferation monitoring

    Lafitte, M.; Robin, J.P.

    2013-01-01

    Synthetic Aperture Radar (SAR) is an active and coherent system. SAR images are complex data which contain both amplitude and phase information. The analysis of single SAR data required a very good experience and a good understanding of SAR geometry regarding layover, shadowing, texture and speckle. Image analyst can depicts and describes most of the facilities related to nuclear proliferation and weapons of mass destruction (WMD). The Amplitude Change Detection (ACD) technique consists of a combination of two or three SAR amplitude data acquired with similar orbit and frequency parameters on different dates. That technique provides a very good overview of the changes and particularly regarding vehicles activity and constructions ongoing within the area of interest over the monitoring period. One of the particularities of the SAR systems is to be coherent. The phase of a single image is not exploitable. Thus when two or more SAR data have been acquired with identical orbit and frequency parameters, the phases shift are indicators of changes such as structural changes, terrain subsidence or motion. The Multi-Temporal Coherence (MTC) product merged the two type of information previously detailed: the ACD and coherence analysis. It consists of the combination of two amplitude images and the corresponding coherence computed image. The MTC image may highlights changes between two states of a target which on the ACD analysis appeared unchanged. EUSC uses the difference interferometry techniques in order to estimate volumes that have changed between two acquisition dates. The paper is followed by the slides of the presentation. (A.C.)

  16. Pseudomalignant myositis ossificans involving multiple masticatory muscles: Imaging evaluation

    Kamalapur, Muralidhar G; Patil, Pritam B; Joshi, Shyamsundar; Shastri, Dinesh

    2014-01-01

    Myositis ossificans is a rare cause of trismus. We present a case of pseudomalignant myositis ossificans involving medial pterygoid, lateral pterygoid, and temporalis muscles. Patient presented with gross limitation in mouth opening. There was no history of trauma. Computed tomography (CT) images revealed a bone density mass located in the region of medial and lateral pterygoid muscles on the right and temporalis muscle on the left. Magnetic resonance imaging (MRI) showed similar findings. Radiological diagnosis was pseudomalignant myositis ossificans. The masses were resected and histopathologic examination confirmed the above diagnosis. This report describes the characteristic CT and MRI features. The unique feature of this case is the absence of history of trauma with involvement of multiple masticatory muscles, which, to the best of our knowledge, has not been reported before

  17. Clinical and imaging assessment of cognitive dysfunction in multiple sclerosis

    Rocca, Maria A; Amato, Maria P; De Stefano, Nicola

    2015-01-01

    In patients with multiple sclerosis (MS), grey matter damage is widespread and might underlie many of the clinical symptoms, especially cognitive impairment. This relation between grey matter damage and cognitive impairment has been lent support by findings from clinical and MRI studies. However...... that causes clinical symptoms to trigger. Findings on cortical reorganisation support the contribution of brain plasticity and cognitive reserve in limiting cognitive deficits. The development of clinical and imaging biomarkers that can monitor disease development and treatment response is crucial to allow...

  18. Imaging outcomes for trials of remyelination in multiple sclerosis.

    Mallik, Shahrukh; Samson, Rebecca S; Wheeler-Kingshott, Claudia A M; Miller, David H

    2014-12-01

    Trials of potential neuroreparative agents are becoming more important in the spectrum of multiple sclerosis research. Appropriate imaging outcomes are required that are feasible from a time and practicality point of view, as well as being sensitive and specific to myelin, while also being reproducible and clinically meaningful. Conventional MRI sequences have limited specificity for myelination. We evaluate the imaging modalities which are potentially more specific to myelin content in vivo, such as magnetisation transfer ratio (MTR), restricted proton fraction f (from quantitative magnetisation transfer measurements), myelin water fraction and diffusion tensor imaging (DTI) metrics, in addition to positron emission tomography (PET) imaging. Although most imaging applications to date have focused on the brain, we also consider measures with the potential to detect remyelination in the spinal cord and in the optic nerve. At present, MTR and DTI measures probably offer the most realistic and feasible outcome measures for such trials, especially in the brain. However, no one measure currently demonstrates sufficiently high sensitivity or specificity to myelin, or correlation with clinical features, and it should be useful to employ more than one outcome to maximise understanding and interpretation of findings with these sequences. PET may be less feasible for current and near-future trials, but is a promising technique because of its specificity. In the optic nerve, visual evoked potentials can indicate demyelination and should be correlated with an imaging outcome (such as optic nerve MTR), as well as clinical measures. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  19. Multiple-Event, Single-Photon Counting Imaging Sensor

    Zheng, Xinyu; Cunningham, Thomas J.; Sun, Chao; Wang, Kang L.

    2011-01-01

    The single-photon counting imaging sensor is typically an array of silicon Geiger-mode avalanche photodiodes that are monolithically integrated with CMOS (complementary metal oxide semiconductor) readout, signal processing, and addressing circuits located in each pixel and the peripheral area of the chip. The major problem is its single-event method for photon count number registration. A single-event single-photon counting imaging array only allows registration of up to one photon count in each of its pixels during a frame time, i.e., the interval between two successive pixel reset operations. Since the frame time can t be too short, this will lead to very low dynamic range and make the sensor merely useful for very low flux environments. The second problem of the prior technique is a limited fill factor resulting from consumption of chip area by the monolithically integrated CMOS readout in pixels. The resulting low photon collection efficiency will substantially ruin any benefit gained from the very sensitive single-photon counting detection. The single-photon counting imaging sensor developed in this work has a novel multiple-event architecture, which allows each of its pixels to register as more than one million (or more) photon-counting events during a frame time. Because of a consequently boosted dynamic range, the imaging array of the invention is capable of performing single-photon counting under ultra-low light through high-flux environments. On the other hand, since the multiple-event architecture is implemented in a hybrid structure, back-illumination and close-to-unity fill factor can be realized, and maximized quantum efficiency can also be achieved in the detector array.

  20. The use of multifrequency and polarimetric SIR-C/X-SAR data in geologic studies of Bir Safsaf, Egypt

    Schaber, G.G.; McCauley, J.F.; Breed, C.S.

    1997-01-01

    Bir Safsaf, within the hyperarid 'core' of the Sahara in the Western Desert of Egypt, was recognized following the SIR-A and SIR-B missions in the 1980s as one of the key localities in northeast Africa, where penetration of dry sand by radar signals delineates previously unknown, sand-buried paleodrainage valleys ('radar-rivers') of middle Tertiary to Quaternary age. The Bir Safsaf area was targeted as a focal point for further research in sand penetration and geologic mapping using the multifrequency and polarimetric SIR-C/X-SAR sensors. Analysis of the SIR-C/X-SAR data from Bir Safsaf provides important new information on the roles of multiple SAR frequency and polarimetry in portraying specific types of geologic units, materials, and structures mostly hidden from view on the ground and on Landsat TM images by a relatively thin, but extensive blanket of blow sand. Basement rock units (granitoids and gneisses) and the fractures associated with them at Bir Safsaf are shown here for the first time to be clearly delineated using C- and L-band SAR images. The detectability of most geologic features is dependent primarily on radar frequency, as shown for wind erosion patterns in bedrock at X-band (3 cm wavelength), and for geologic units and sand and clay-filled fractures in weathered crystal-line basement rocks at C-band (6 cm) and L-band (24 cm). By contrast, Quaternary paleodrainage channels are detectable at all three radar frequencies owing, among other things, to an usually thin cover of blow sand. The SIR-C/X-SAR data investigated to date enable us to make specific recommendations about the utility of certain radar sensor configurations for geologic and paleoenvironmental reconnaissance in desert regions.Analysis of the shuttle imaging radar-C/X-synthetic aperture radar (SIR-C/X-SAR) data from Bir Safsaf provides important new information on the roles of multiple SAR frequency and polarimetry in portraying specific types of geologic units, materials, and

  1. Video Multiple Watermarking Technique Based on Image Interlacing Using DWT

    Mohamed M. Ibrahim

    2014-01-01

    Full Text Available Digital watermarking is one of the important techniques to secure digital media files in the domains of data authentication and copyright protection. In the nonblind watermarking systems, the need of the original host file in the watermark recovery operation makes an overhead over the system resources, doubles memory capacity, and doubles communications bandwidth. In this paper, a robust video multiple watermarking technique is proposed to solve this problem. This technique is based on image interlacing. In this technique, three-level discrete wavelet transform (DWT is used as a watermark embedding/extracting domain, Arnold transform is used as a watermark encryption/decryption method, and different types of media (gray image, color image, and video are used as watermarks. The robustness of this technique is tested by applying different types of attacks such as: geometric, noising, format-compression, and image-processing attacks. The simulation results show the effectiveness and good performance of the proposed technique in saving system resources, memory capacity, and communications bandwidth.

  2. Video multiple watermarking technique based on image interlacing using DWT.

    Ibrahim, Mohamed M; Abdel Kader, Neamat S; Zorkany, M

    2014-01-01

    Digital watermarking is one of the important techniques to secure digital media files in the domains of data authentication and copyright protection. In the nonblind watermarking systems, the need of the original host file in the watermark recovery operation makes an overhead over the system resources, doubles memory capacity, and doubles communications bandwidth. In this paper, a robust video multiple watermarking technique is proposed to solve this problem. This technique is based on image interlacing. In this technique, three-level discrete wavelet transform (DWT) is used as a watermark embedding/extracting domain, Arnold transform is used as a watermark encryption/decryption method, and different types of media (gray image, color image, and video) are used as watermarks. The robustness of this technique is tested by applying different types of attacks such as: geometric, noising, format-compression, and image-processing attacks. The simulation results show the effectiveness and good performance of the proposed technique in saving system resources, memory capacity, and communications bandwidth.

  3. Multiple imaging procedures including MRI for the bladder cancer

    Mikata, Noriharu; Suzuki, Makoto; Takeuchi, Takumi; Kunisawa, Yositaka; Fukutani, Keiko; Kawabe, Kazuki

    1986-01-01

    Endoscopic photography, double contrast cystography, transurethral echography, X-ray CT scan, and MRI (magnetic resonance imaging) were utilized for the staging diagnosis of the four patients with carcinoma of the bladder. In the first case, a 70-year-old man, since all of the five imaging procedures suggested a superficial and pedunculated tumor, his bladder cancer was considered T1. The classification of stage T3 carcinoma was made for the second 86-year-old male. Because all of his imaging examinations showed a tumor infiltrating deep muscle and penetrating the bladder wall. The third case was a 36-year-old male. His clinical stage was diagnosed as T2 or T3a by cystophotography, double contrast cystogram, ultrasonography, and X-ray CT scan. However, MRI showed only thickened bladder wall and the infiltrating tumor could not be distinguished from the hypertrophic wall. The last patient, a 85-year-old female, had a smaller Ta cancer. Her double contrast cystography revealed the small tumor at the lateral bladder wall. But, the tumor could not be detected by transaxial, sagittal and coronal scans. Multiple imaging procedures combining MRI and staging diagnosis of the bladder carcinoma were discussed. (author)

  4. Mars Mission Concepts: SAR and Solar Electric Propulsion

    Elsperman, M.; Klaus, K.; Smith, D. B.; Clifford, S. M.; Lawrence, S. J.

    2012-12-01

    Introduction: The time has come to leverage technology advances (including advances in autonomous operation and propulsion technology) to reduce the cost and increase the flight rate of planetary missions, while actively developing a scientific and engineering workforce to achieve national space objectives. Mission Science at Mars: A SAR imaging radar offers an ability to conduct high resolution investigations of the shallow (Models uniquely useful for exploration planning and science purposes. Since the SAR and the notional high-resolution stereo imaging system would be huge data volume producers - to maximize the science return we are currently considering the usage of laser communications systems; this notional spacecraft represents one pathway to evaluate the utility of laser communications in planetary exploration while providing useful science return.. Mission Concept: Using a common space craft for multiple missions reduces costs. Solar electric propulsion (SEP) provides the flexibility required for multiple mission objectives. SEP provides the greatest payload advantage albeit at the sacrifice of mission time. Our concept involves using a SEP enabled space craft (Boeing 702SP) with a highly capable SAR imager that also conducts autonomous rendezvous and docking experiments accomplished from Mars orbit. Our concept of operations is to launch on May 5, 2018 using a launch vehicle with 2000kg launch capacity with a C3 of 7.4. After reaching Mars it takes 145 days to spiral down to a 250 km orbit above the surface of Mars when Mars SAR operations begin. Summary/Conclusions: A robust and compelling Mars mission can be designed to meet the 2018 Mars launch window opportunity. Using advanced in-space power and propulsion technologies like High Power Solar Electric Propulsion provides enormous mission flexibility to execute the baseline science mission and conduct necessary Mars Sample Return Technology Demonstrations in Mars orbit on the same mission. An

  5. SAR Polarimetry

    vanZyl, Jakob J.

    2012-01-01

    Radar Scattering includes: Surface Characteristics, Geometric Properties, Dielectric Properties, Rough Surface Scattering, Geometrical Optics and Small Perturbation Method Solutions, Integral Equation Method, Magellan Image of Pancake Domes on Venus, Dickinson Impact Crater on Venus (Magellan), Lakes on Titan (Cassini Radar, Longitudinal Dunes on Titan (Cassini Radar), Rough Surface Scattering: Effect of Dielectric Constant, Vegetation Scattering, Effect of Soil Moisture. Polarimetric Radar includes: Principles of Polarimetry: Field Descriptions, Wave Polarizations: Geometrical Representations, Definition of Ellipse Orientation Angles, Scatter as Polarization Transformer, Scattering Matrix, Coordinate Systems, Scattering Matrix, Covariance Matrix, Pauli Basis and Coherency Matrix, Polarization Synthesis, Polarimeter Implementation.

  6. GEOPOSITIONING PRECISION ANALYSIS OF MULTIPLE IMAGE TRIANGULATION USING LRO NAC LUNAR IMAGES

    K. Di

    2016-06-01

    Full Text Available This paper presents an empirical analysis of the geopositioning precision of multiple image triangulation using Lunar Reconnaissance Orbiter Camera (LROC Narrow Angle Camera (NAC images at the Chang’e-3(CE-3 landing site. Nine LROC NAC images are selected for comparative analysis of geopositioning precision. Rigorous sensor models of the images are established based on collinearity equations with interior and exterior orientation elements retrieved from the corresponding SPICE kernels. Rational polynomial coefficients (RPCs of each image are derived by least squares fitting using vast number of virtual control points generated according to rigorous sensor models. Experiments of different combinations of images are performed for comparisons. The results demonstrate that the plane coordinates can achieve a precision of 0.54 m to 2.54 m, with a height precision of 0.71 m to 8.16 m when only two images are used for three-dimensional triangulation. There is a general trend that the geopositioning precision, especially the height precision, is improved with the convergent angle of the two images increasing from several degrees to about 50°. However, the image matching precision should also be taken into consideration when choosing image pairs for triangulation. The precisions of using all the 9 images are 0.60 m, 0.50 m, 1.23 m in along-track, cross-track, and height directions, which are better than most combinations of two or more images. However, triangulation with selected fewer images could produce better precision than that using all the images.

  7. An ML-Based Radial Velocity Estimation Algorithm for Moving Targets in Spaceborne High-Resolution and Wide-Swath SAR Systems

    Tingting Jin

    2017-04-01

    Full Text Available Multichannel synthetic aperture radar (SAR is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS compared with conventional SAR. Moving target indication (MTI is an important application of spaceborne HRWS SAR systems. In contrast to previous studies of SAR MTI, the HRWS SAR mainly faces the problem of under-sampled data of each channel, causing single-channel imaging and processing to be infeasible. In this study, the estimation of velocity is equivalent to the estimation of the cone angle according to their relationship. The maximum likelihood (ML based algorithm is proposed to estimate the radial velocity in the existence of Doppler ambiguities. After that, the signal reconstruction and compensation for the phase offset caused by radial velocity are processed for a moving target. Finally, the traditional imaging algorithm is applied to obtain a focused moving target image. Experiments are conducted to evaluate the accuracy and effectiveness of the estimator under different signal-to-noise ratios (SNR. Furthermore, the performance is analyzed with respect to the motion ship that experiences interference due to different distributions of sea clutter. The results verify that the proposed algorithm is accurate and efficient with low computational complexity. This paper aims at providing a solution to the velocity estimation problem in the future HRWS SAR systems with multiple receive channels.

  8. Multiple speckle illumination for optical-resolution photoacoustic imaging

    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

  9. Rotating Parabolic-Reflector Antenna Target in SAR Data: Model, Characteristics, and Parameter Estimation

    Bin Deng

    2013-01-01

    Full Text Available Parabolic-reflector antennas (PRAs, usually possessing rotation, are a particular type of targets of potential interest to the synthetic aperture radar (SAR community. This paper is aimed to investigate PRA’s scattering characteristics and then to extract PRA’s parameters from SAR returns, for supporting image interpretation and target recognition. We at first obtain both closed-form and numeric solutions to PRA’s backscattering by geometrical optics (GO, physical optics, and graphical electromagnetic computation, respectively. Based on the GO solution, a migratory scattering center model is at first presented for representing the movement of the specular point with aspect angle, and then a hybrid model, named the migratory/micromotion scattering center (MMSC model, is proposed for characterizing a rotating PRA in the SAR geometry, which incorporates PRA’s rotation into its migratory scattering center model. Additionally, we in detail analyze PRA’s radar characteristics on radar cross-section, high-resolution range profiles, time-frequency distribution, and 2D images, which also confirm the models proposed. A maximal likelihood estimator is developed for jointly solving the MMSC model for PRA’s multiple parameters by optimization. By exploiting the aforementioned characteristics, the coarse parameter estimation guarantees convergency upon global minima. The signatures recovered can be favorably utilized for SAR image interpretation and target recognition.

  10. Applicability of interferometric SAR technology to ground movement and pipeline monitoring

    Grivas, Dimitri A.; Bhagvati, Chakravarthy; Schultz, B. C.; Trigg, Alan; Rizkalla, Moness

    1998-03-01

    This paper summarizes the findings of a cooperative effort between NOVA Gas Transmission Ltd. (NGTL), the Italian Natural Gas Transmission Company (SNAM), and Arista International, Inc., to determine whether current remote sensing technologies can be utilized to monitor small-scale ground movements over vast geographical areas. This topic is of interest due to the potential for small ground movements to cause strain accumulation in buried pipeline facilities. Ground movements are difficult to monitor continuously, but their cumulative effect over time can have a significant impact on the safety of buried pipelines. Interferometric synthetic aperture radar (InSAR or SARI) is identified as the most promising technique of those considered. InSAR analysis involves combining multiple images from consecutive passes of a radar imaging platform. The resulting composite image can detect changes as small as 2.5 to 5.0 centimeters (based on current analysis methods and radar satellite data of 5 centimeter wavelength). Research currently in progress shows potential for measuring ground movements as small as a few millimeters. Data needed for InSAR analysis is currently commercially available from four satellites, and additional satellites are planned for launch in the near future. A major conclusion of the present study is that InSAR technology is potentially useful for pipeline integrity monitoring. A pilot project is planned to test operational issues.

  11. Diffusion Weighted Imaging in Acute Attacks of Multiple Sclerosis

    Davoudi, Yasmin; Foroughipour, Mohsen; Torabi, Reza; Layegh, Parvaneh; Matin, Nassim; Shoeibi, Ali

    2016-01-01

    Multiple sclerosis (MS) is one of the most common autoimmune disorders of the central nervous system. In spite of various imaging modalities, the definitive diagnosis of MS remains challenging. This study was designed to evaluate the usefulness of diffusion weighted imaging (DWI) in the diagnosis of acute MS attack and to compare its results with contrast enhanced MRI (CE-MRI). In this cross sectional study, seventy patients with definite diagnosis of relapsing-remitting MS were included. CE-MRI using 0.1 mmol/kg gadolinium as well as DWI sequences were performed for all patients. The percentage of patients with positive DWI was compared with the results of CE-MRI and the consistency between the two imaging modalities was evaluated. Moreover, the relationship between the time of onset of patient’s symptoms and test results for both methods were investigated. CE-MRI yielded positive results for 61 (87%) patients and DWI yielded positive for 53 (76%) patients. In fifty patients (71.42%), both tests were positive and in six cases (8.57%), both were negative. The test results of three patients turned out to be positive in DWI, while they tested negative in CE-MRI. There was no significant relationship between the results of CE-MRI as well as DWI and the time of imaging from the onset of symptoms. These data indicate that while CE-MRI will depict more positive results, there are cases in which DWI will show a positive result while CE-MRI is negative. We suggest that the combination of these two imaging modalities might yield more positive results in diagnosing acute MS attack giving rise to a more accurate diagnosis

  12. SAR Target Recognition via Supervised Discriminative Dictionary Learning and Sparse Representation of the SAR-HOG Feature

    Shengli Song

    2016-08-01

    Full Text Available Automatic target recognition (ATR in synthetic aperture radar (SAR images plays an important role in both national defense and civil applications. Although many methods have been proposed, SAR ATR is still very challenging due to the complex application environment. Feature extraction and classification are key points in SAR ATR. In this paper, we first design a novel feature, which is a histogram of oriented gradients (HOG-like feature for SAR ATR (called SAR-HOG. Then, we propose a supervised discriminative dictionary learning (SDDL method to learn a discriminative dictionary for SAR ATR and propose a strategy to simplify the optimization problem. Finally, we propose a SAR ATR classifier based on SDDL and sparse representation (called SDDLSR, in which both the reconstruction error and the classification error are considered. Extensive experiments are performed on the MSTAR database under standard operating conditions and extended operating conditions. The experimental results show that SAR-HOG can reliably capture the structures of targets in SAR images, and SDDL can further capture subtle differences among the different classes. By virtue of the SAR-HOG feature and SDDLSR, the proposed method achieves the state-of-the-art performance on MSTAR database. Especially for the extended operating conditions (EOC scenario “Training 17 ∘ —Testing 45 ∘ ”, the proposed method improves remarkably with respect to the previous works.

  13. ROADS CENTRE-AXIS EXTRACTION IN AIRBORNE SAR IMAGES: AN APPROACH BASED ON ACTIVE CONTOUR MODEL WITH THE USE OF SEMI-AUTOMATIC SEEDING

    R. G. Lotte

    2013-05-01

    Full Text Available Research works dealing with computational methods for roads extraction have considerably increased in the latest two decades. This procedure is usually performed on optical or microwave sensors (radar imagery. Radar images offer advantages when compared to optical ones, for they allow the acquisition of scenes regardless of atmospheric and illumination conditions, besides the possibility of surveying regions where the terrain is hidden by the vegetation canopy, among others. The cartographic mapping based on these images is often manually accomplished, requiring considerable time and effort from the human interpreter. Maps for detecting new roads or updating the existing roads network are among the most important cartographic products to date. There are currently many studies involving the extraction of roads by means of automatic or semi-automatic approaches. Each of them presents different solutions for different problems, making this task a scientific issue still open. One of the preliminary steps for roads extraction can be the seeding of points belonging to roads, what can be done using different methods with diverse levels of automation. The identified seed points are interpolated to form the initial road network, and are hence used as an input for an extraction method properly speaking. The present work introduces an innovative hybrid method for the extraction of roads centre-axis in a synthetic aperture radar (SAR airborne image. Initially, candidate points are fully automatically seeded using Self-Organizing Maps (SOM, followed by a pruning process based on specific metrics. The centre-axis are then detected by an open-curve active contour model (snakes. The obtained results were evaluated as to their quality with respect to completeness, correctness and redundancy.

  14. Satellite on-board real-time SAR processor prototype

    Bergeron, Alain; Doucet, Michel; Harnisch, Bernd; Suess, Martin; Marchese, Linda; Bourqui, Pascal; Desnoyers, Nicholas; Legros, Mathieu; Guillot, Ludovic; Mercier, Luc; Châteauneuf, François

    2017-11-01

    A Compact Real-Time Optronic SAR Processor has been successfully developed and tested up to a Technology Readiness Level of 4 (TRL4), the breadboard validation in a laboratory environment. SAR, or Synthetic Aperture Radar, is an active system allowing day and night imaging independent of the cloud coverage of the planet. The SAR raw data is a set of complex data for range and azimuth, which cannot be compressed. Specifically, for planetary missions and unmanned aerial vehicle (UAV) systems with limited communication data rates this is a clear disadvantage. SAR images are typically processed electronically applying dedicated Fourier transformations. This, however, can also be performed optically in real-time. Originally the first SAR images were optically processed. The optical Fourier processor architecture provides inherent parallel computing capabilities allowing real-time SAR data processing and thus the ability for compression and strongly reduced communication bandwidth requirements for the satellite. SAR signal return data are in general complex data. Both amplitude and phase must be combined optically in the SAR processor for each range and azimuth pixel. Amplitude and phase are generated by dedicated spatial light modulators and superimposed by an optical relay set-up. The spatial light modulators display the full complex raw data information over a two-dimensional format, one for the azimuth and one for the range. Since the entire signal history is displayed at once, the processor operates in parallel yielding real-time performances, i.e. without resulting bottleneck. Processing of both azimuth and range information is performed in a single pass. This paper focuses on the onboard capabilities of the compact optical SAR processor prototype that allows in-orbit processing of SAR images. Examples of processed ENVISAT ASAR images are presented. Various SAR processor parameters such as processing capabilities, image quality (point target analysis), weight and

  15. Severe acute respiratory syndrome (SARS)

    SARS; Respiratory failure - SARS ... Complications may include: Respiratory failure Liver failure Heart failure ... 366. McIntosh K, Perlman S. Coronaviruses, including severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). ...

  16. A Constellation of CubeSat InSAR Sensors for Rapid-Revisit Surface Deformation Studies

    Wye, L.; Lee, S.; Yun, S. H.; Zebker, H. A.; Stock, J. D.; Wicks, C. W., Jr.; Doe, R.

    2016-12-01

    The 2007 NRC Decadal Survey for Earth Sciences highlights three major Earth surface deformation themes: 1) solid-earth hazards and dynamics; 2) human health and security; and 3) land-use change, ecosystem dynamics and biodiversity. Space-based interferometric synthetic aperture radar (InSAR) is a key change detection tool for addressing these themes. Here, we describe the mission and radar payload design for a constellation of S-band InSAR sensors specifically designed to provide the global, high temporal resolution, sub-cm level deformation accuracy needed to address some of the major Earth system goals. InSAR observations with high temporal resolution are needed to properly monitor certain nonlinearly time-varying features (e.g., unstable volcanoes, active fault lines, and heavily-used groundwater or hydrocarbon reservoirs). Good temporal coverage is also needed to reduce atmospheric artifacts by allowing multiple acquisitions to be averaged together, since each individual SAR measurement is corrupted by up to several cm of atmospheric noise. A single InSAR platform is limited in how often it can observe a given scene without sacrificing global spatial coverage. Multiple InSAR platforms provide the spatial-temporal flexibility required to maximize the science return. However, building and launching multiple InSAR platforms is cost-prohibitive for traditional satellites. SRI International (SRI) and our collaborators are working to exploit developments in nanosatellite technology, in particular the emergence of the CubeSat standard, to provide high-cadence InSAR capabilities in an affordable package. The CubeSat Imaging Radar for Earth Science (CIRES) subsystem, a prototype SAR elec­tronics package developed by SRI with support from a 2014 NASA ESTO ACT award, is specifically scaled to be a drop-in radar solution for resource-limited delivery systems like CubeSats and small airborne vehicles. Here, we present our mission concept and flow-down requirements for a

  17. Heterogeneity of Multiple Sclerosis Lesions in Multislice Myelin Water Imaging.

    Tobias Djamsched Faizy

    Full Text Available To assess neuroprotection and remyelination in Multiple Sclerosis (MS, we applied a more robust myelin water imaging (MWI processing technique, including spatial priors into image reconstruction, which allows for lower SNR, less averages and shorter acquisition times. We sought to evaluate this technique in MS-patients and healthy controls (HC.Seventeen MS-patients and 14 age-matched HCs received a 3T Magnetic Resonance Imaging (MRI examination including MWI (8 slices, 12 minutes acquisition time, T2w and T1mprage pre and post gadolinium (GD administration. Black holes (BH, contrast enhancing lesions (CEL and T2 lesions were marked and registered to MWI. Additionally, regions of interest (ROI were defined in the frontal, parietal and occipital normal appearing white matter (NAWM/white matter (WM, the corticospinal tract (CST, the splenium (SCC and genu (GCC of the corpus callosum in patients and HCs. Mean values of myelin water fraction (MWF were determined for each ROI.Significant differences (p≤0.05 of the MWF were found in all three different MS-lesion types (BH, CEL, T2 lesions, compared to the WM of HCs. The mean MWF values among the different lesion types were significantly differing from each other. Comparing MS-patients vs. HCs, we found a significant (p≤0.05 difference of the MWF in all measured ROIs except of GCC and SCC. The mean reduction of MWF in the NAWM of MS-patients compared to HCs was 37%. No age, sex, disability score and disease duration dependency was found for the NAWM MWF.MWF measures were in line with previous studies and lesions were clearly visible in MWI. MWI allows for quantitative assessment of NAWM and lesions in MS, which could be used as an additional sensitive imaging endpoint for larger MS studies. Measurements of the MWF also differ between patients and healthy controls.

  18. Magnetic resonance imaging of spinal cord lesions in multiple sclerosis

    Kojima, Shigeyuki; Yagishita, Toshiyuki; Fukutake, Toshio; Hirayama, Keizo; Fukuda, Nobuo.

    1987-01-01

    Magnetic resonance imaging (MRI) was used in three patients with multiple sclerosis (MS) to demonstrate the longitudinal distribution of demyelinating plaques in the spinal cord and to measure their T1 relaxation time values in these disease processes. Neurological examination allowed the detection of the superior limit of the spinal cord lesions in the three patients, but did not permit detection of the inferior limit in two of the patients. With MRI, however, it was possible to demonstrate the longitudinal distribution of demyelinating plaques in all three patients from coronal or sagittal images using spin echo and inversion recovery pulse sequences. In two patients treated with prednisolone, serial T1 relaxation time values of MS spinal cord lesions were measured from T1 calculated images. In one patient with transverse myelopathy, the T1 relaxation time values of MS spinal cord lesions were significantly increased at a stage of acute exacerbation. This is apparently in contrast with the values at the stage of remission. In the patient with localized cervical myelopathy, the increase in T1 relaxation time values of MS spinal cord lesions at the acute stage was small and significantly different from the values at the remission stage. Several recent reports have indicated that MRI is extremely sensitive in the detection of MS plaques, but most efforts to use MRI in the diagnosis of MS have been concentrated on brain lesions in spite of their frequent associations with spinal cord involvements. It is concluded from our case studies that MRI coronal or sagittal image is useful in demonstrating the longitudinal distribution of MS spinal cord lesions. In addition, serial observations of T1 relaxation time values of MS plaques may be important in assessing the activity of MS plaques and evaluation of the steroid therapy in MS processes. (author)

  19. Investigation on the separability of slums by multi-aspect TerraSAR-X dual-co-polarized high resolution spotlight images based on the multi-scale evaluation of local distributions

    Schmitt, Andreas; Sieg, Tobias; Wurm, Michael; Taubenböck, Hannes

    2018-02-01

    Following recent advances in distinguishing settlements vs. non-settlement areas from latest SAR data, the question arises whether a further automatic intra-urban delineation and characterization of different structural types is possible. This paper studies the appearance of the structural type ;slums; in high resolution SAR images. Geocoded Kennaugh elements are used as backscatter information and Schmittlet indices as descriptor of local texture. Three cities with a significant share of slums (Cape Town, Manila, Mumbai) are chosen as test sites. These are imaged by TerraSAR-X in the dual-co-polarized high resolution spotlight mode in any available aspect angle. Representative distributions are estimated and fused by a robust approach. Our observations identify a high similarity of slums throughout all three test sites. The derived similarity maps are validated with reference data sets from visual interpretation and ground truth. The final validation strategy is based on completeness and correctness versus other classes in relation to the similarity. High accuracies (up to 87%) in identifying morphologic slums are reached for Cape Town. For Manila (up to 60%) and Mumbai (up to 54%), the distinction is more difficult due to their complex structural configuration. Concluding, high resolution SAR data can be suitable to automatically trace potential locations of slums. Polarimetric information and the incidence angle seem to have a negligible impact on the results whereas the intensity patterns and the passing direction of the satellite are playing a key role. Hence, the combination of intensity images (brightness) acquired from ascending and descending orbits together with Schmittlet indices (spatial pattern) promises best results. The transfer from the automatically recognized physical similarity to the semantic interpretation remains challenging.

  20. Color correction with blind image restoration based on multiple images using a low-rank model

    Li, Dong; Xie, Xudong; Lam, Kin-Man

    2014-03-01

    We present a method that can handle the color correction of multiple photographs with blind image restoration simultaneously and automatically. We prove that the local colors of a set of images of the same scene exhibit the low-rank property locally both before and after a color-correction operation. This property allows us to correct all kinds of errors in an image under a low-rank matrix model without particular priors or assumptions. The possible errors may be caused by changes of viewpoint, large illumination variations, gross pixel corruptions, partial occlusions, etc. Furthermore, a new iterative soft-segmentation method is proposed for local color transfer using color influence maps. Due to the fact that the correct color information and the spatial information of images can be recovered using the low-rank model, more precise color correction and many other image-restoration tasks-including image denoising, image deblurring, and gray-scale image colorizing-can be performed simultaneously. Experiments have verified that our method can achieve consistent and promising results on uncontrolled real photographs acquired from the Internet and that it outperforms current state-of-the-art methods.

  1. Infrastructure monitoring with spaceborne SAR sensors

    ANGHEL, ANDREI; CACOVEANU, REMUS

    2017-01-01

    This book presents a novel non-intrusive infrastructure monitoring technique based on the detection and tracking of scattering centers in spaceborne SAR images. The methodology essentially consists of refocusing each available SAR image on an imposed 3D point cloud associated to the envisaged infrastructure element and identifying the reliable scatterers to be monitored by means of four dimensional (4D) tomography. The methodology described in this book provides a new perspective on infrastructure monitoring with spaceborne SAR images, is based on a standalone processing chain, and brings innovative technical aspects relative to conventional approaches. The book is intended primarily for professionals and researchers working in the area of critical infrastructure monitoring by radar remote sensing.

  2. Design and realization of an active SAR calibrator for TerraSAR-X

    Dummer, Georg; Lenz, Rainer; Lutz, Benjamin; Kühl, Markus; Müller-Glaser, Klaus D.; Wiesbeck, Werner

    2005-10-01

    TerraSAR-X is a new earth observing satellite which will be launched in spring 2006. It carries a high resolution X-band SAR sensor. For high image data quality, accurate ground calibration targets are necessary. This paper describes a novel system concept for an active and highly integrated, digitally controlled SAR system calibrator. A total of 16 active transponder and receiver systems and 17 receiver only systems will be fabricated for a calibration campaign. The calibration units serve for absolute radiometric calibration of the SAR image data. Additionally, they are equipped with an extra receiver path for two dimensional satellite antenna pattern recognition. The calibrator is controlled by a dedicated digital Electronic Control Unit (ECU). The different voltages needed by the calibrator and the ECU are provided by the third main unit called Power Management Unit (PMU).

  3. Spaceborne Polarimetric SAR Interferometry: Performance Analysis and Mission Concepts

    Shane R. Cloude

    2005-12-01

    Full Text Available We investigate multichannel imaging radar systems employing coherent combinations of polarimetry and interferometry (Pol-InSAR. Such systems are well suited for the extraction of bio- and geophysical parameters by evaluating the combined scattering from surfaces and volumes. This combination leads to several important differences between the design of Pol-InSAR sensors and conventional single polarisation SAR interferometers. We first highlight these differences and then investigate the Pol-InSAR performance of two proposed spaceborne SAR systems (ALOS/PalSAR and TerraSAR-L operating in repeat-pass mode. For this, we introduce the novel concept of a phase tube which enables (1 a quantitative assessment of the Pol-InSAR performance, (2 a comparison between different sensor configurations, and (3 an optimization of the instrument settings for different Pol-InSAR applications. The phase tube may hence serve as an interface between system engineers and application-oriented scientists. The performance analysis reveals major limitations for even moderate levels of temporal decorrelation. Such deteriorations may be avoided in single-pass sensor configurations and we demonstrate the potential benefits from the use of future bi- and multistatic SAR interferometers.

  4. Volume measurement of multiple sclerosis lesions with magnetic resonance images

    Wicks, D.A.G.; Tofts, P.S.; Miller, D.H.; Du Boulay, G.H.; Feinstein, A.; Harvey, I.; Brenner, R.; McDonald, W.I.; Sacares, R.P.

    1992-01-01

    The ability to visualise multiple sclerosis lesions in vivo with magnetic resonance imaging suggests an important role in monitoring the course of the disease. In order to help the long-term assessment of prospective treatments, a semi-automated technique for measuring lesion volume has been developed to provide a quantitative index of disease progression. Results are presented from a preliminary study with a single patient and compared to measurements taken from lesion outlines traced by a neuroradiologist, two neurologists and a technician. The semi-automated technique achieved a precision of 6% compared to a range of 12-33% for the manual tracing method. It also reduced the human interaction time from at least 60 min to 15 min. (orig.)

  5. Imaging by multiple modalities of patients with a carotidynia syndrome

    Kosaka, Nobuyuki; Uematsu, Hidemasa; Kimura, Hirohiko; Itoh, Harumi [University of Fukui, Department of Radiology, Faculty of Medical Sciences, Fukui (Japan); Sagoh, Tadashi; Noguchi, Masato [Fukui Red Cross Hospital, Department of Radiology, Fukui (Japan); Miyayama, Shiro [Fukuiken Saiseikai Hospital, Department of Diagnostic Radiology, Fukui (Japan)

    2007-09-15

    The purpose of this article is to familiarize readers with the clinical syndrome of carotidynia. In the past, the International Headache Society (IHS) described idiopathic carotidynia as a diagnostic entity consisting of a self-limiting neck pain syndrome and tenderness over the carotid bifurcation without structural abnormality and then recently removed it from its classification. Although the clinical criteria of carotidynia in the former classification of the IHS included the absence of structural abnormality, several publications have demonstrated associated radiological findings and have described the usefulness of radiological investigations in diagnosing this syndrome. In this paper, we report four additional cases with a carotidynia clinical syndrome (according to the former classification) and the presence of abnormal soft tissue infiltration surrounding the symptomatic carotid artery as demonstrated by multiple imaging modalities, without any other underlying cause for the carotid pain syndrome. Our findings support the hypothesis that carotidynia could be a distinct disease entity, possibly caused by inflammation. (orig.)

  6. Image reconstruction from multiple fan-beam projections

    Jelinek, J.; Overton, T.R.

    1984-01-01

    Special-purpose third-generation fan-beam CT systems can be greatly simplified by limiting the number of detectors, but this requires a different mode of data collection to provide a set of projections appropriate to the required spatial resolution in the reconstructed image. Repeated rotation of the source-detector fan, combined with shift of the detector array and perhaps offset of the source with respect to the fan's axis after each 360 0 rotation(cycle), provides a fairly general pattern of projection space filling. The authors' investigated the problem of optimal data-collection geometry for a multiple-rotation fan-beam scanner and of corresponding reconstruction algorithm

  7. Imaging by multiple modalities of patients with a carotidynia syndrome

    Kosaka, Nobuyuki; Uematsu, Hidemasa; Kimura, Hirohiko; Itoh, Harumi; Sagoh, Tadashi; Noguchi, Masato; Miyayama, Shiro

    2007-01-01

    The purpose of this article is to familiarize readers with the clinical syndrome of carotidynia. In the past, the International Headache Society (IHS) described idiopathic carotidynia as a diagnostic entity consisting of a self-limiting neck pain syndrome and tenderness over the carotid bifurcation without structural abnormality and then recently removed it from its classification. Although the clinical criteria of carotidynia in the former classification of the IHS included the absence of structural abnormality, several publications have demonstrated associated radiological findings and have described the usefulness of radiological investigations in diagnosing this syndrome. In this paper, we report four additional cases with a carotidynia clinical syndrome (according to the former classification) and the presence of abnormal soft tissue infiltration surrounding the symptomatic carotid artery as demonstrated by multiple imaging modalities, without any other underlying cause for the carotid pain syndrome. Our findings support the hypothesis that carotidynia could be a distinct disease entity, possibly caused by inflammation. (orig.)

  8. Magnetic resonance imaging in optic nerve lesions with multiple sclerosis

    Kojima, Shigeyuki; Hirayama, Keizo; Kakisu, Yonetsugu; Adachi, Emiko

    1990-01-01

    Magnetic resonance imaging (MRI) of the optic nerve was performed in 10 patients with multiple sclerosis (MS) using short inversion time inversion recovery (STIR) pulse sequences, and the results were compared with the visual evoked potentials (VEP). The 10 patients had optic neuritis in the chronic or remitting phase together with additional symptoms or signs allowing a diagnosis of clinically definite or probable MS. Sixteen optic nerves were clinically affected and 4 were unaffected. MRI was performed using a 0.5 tesla supeconducting unit, and multiple continuous 5 mm coronal and axial STIR images were obtained. A lesion was judged to be present if a focal or diffuse area of increased signal intensity was detectd in the optic nerve. In VEP, a delay in peak latency or no P 100 component was judged to be abnormal. With regard to the clinically affected optic nerves, MRI revealed a region of increased signal intensity in 14/16 (88%) and the VEP was abnormal in 16/16 (100%). In the clinically unaffected optic nerves, MRI revealed an increased signal intensity in 2/4 (50%). One of these nerves had an abnormal VEP and the other had a VEP latency at the upper limit of normal. The VEP was abnormal in 1/4 (25%). In the clinically affected optic nerves, the degree of loss of visual acuity was not associated with the longitudinal extent of the lesions shown by MRI. The mean length was 17.5 mm in optic nerves with a slight disturbance of visual acuity and 15.0 mm in nerves with severe visual loss. MRI using STIR pulse sequences was found to be almost as sensitive as VEP in detecting both clinically affected and unaffected optic nerve lesions in patients with MS, and was useful in visualizing the location or size of the lesions. (author)

  9. Magnetic resonance imaging in the diagnosis of multiple sclerosis

    Kato, Hiroyuki; Takase, Sadao; Ichikawa, Nobumichi; Yamada, Kenji; Matsuzawa, Taiju.

    1987-01-01

    Seventeen patients with multiple sclerosis (MS), 11 clinically definite and 6 probable MS, were studied using magnetic resonance imaging (MRI) and other diagnostic techniques including cerebrospinal fluid (CSF) analysis, evoked potentials (EP) and CT. The MRI imager was operated at 0.14 tesla. The Carr-Purcell-Meiboom-Gill pulse sequence was employed and multiple spin echoes were acquired. T 1 and T 2 relaxation times of the MS plaques were calculated. Incidence of MS plaque detection was 82 % in MRI (100 % in definite MS and 50 % in probable MS). Incidence of abnormality was 65 % in CSF analysis (IgG, oligoclonal bands and myelin basic protein), 63 % in EP (auditory evoked brainstem response and somatosensory evoked response), and 24 % in CT. Lesion detection by MRI was more frequent when the patient was diagnosed as clinically definite, when the duration of disease was longer or the exacerbation was more frequent. T 1 and T 2 of the MS plaques were 715 ± 140 msec and 184 ± 42 msec, respectively, and were significantly prolonged compared to normal values (T 1 ; 351 ± 35 msec, T 2 ; 102 ± 12 msec). The relaxation times of the plaques which were detected by CT (T 1 ; 834 ± 106 msec, T 2 ; 216 ± 37 msec) were significantly longer than those which were not detected (T 1 ; 673 ± 128 msec, T 2 ; 165 ± 32 msec). Serial observations of relaxation times showed that they become short as time passes after the onset of symptoms. As a result, MRI was most sensitive among the diagnostic modalities of MS, and the relaxation times can serve as indices of the activity and severity of the disease. (author)

  10. Coseismic displacements from SAR image offsets between different satellite sensors: Application to the 2001 Bhuj (India) earthquake

    Wang, Teng; Wei, Shengji; Jonsson, Sigurjon

    2015-01-01

    preearthquake ERS and postearthquake Envisat images. The rupture model estimated from these cross-sensor offsets and teleseismic waveforms shows a compact fault slip pattern with fairly short rise times (<3 s) and a large stress drop (20 MPa), explaining

  11. Multiple foci of splenic tissue autotransplantation: Splenosis in diagnostic imaging

    Laskowska, K.; Burzynska-Makuch, M.; Drewa, S.; Lasek, W.; Pilecki, S.; Junik, R.

    2005-01-01

    Splenosis is usually defined as an autotransplantation of lienal tissue in the abdomen or cest following trauma to the spleen and/or splenectomy. The authors present the case of patient 15 years after a splenectomy performed because of extensive abdominal trauma. A new computed tomographic (CT) scan of the abdomen revealed multiple homogenous nodules, different in size, spread in the abdomen. Their density was characteristic of spleen. Ultrasound examination revealed only the largest tumors, located close to the liver and apparently isoechogenic to it. Static scintigraphy and SPECT were performed to prove the presence of splenosis. After treating the patient with colloid sulfide, multiple foci of increased radioisotope accumulation were identified in the abdomen, extrahepatic at the same locations as the masses visible on the CT scans, which were comparable to splenic tissue. Nodules revealed during CT or abdominal US in patients previously treated by splenectomy require further imaging with static scintigraphy of the liver and spleen in order to confirm or exclude splenosis. (author)

  12. Modern imaging techniques in patients with multiple myeloma

    Bannas, Peter; Adam, G.; Derlin, T.; Kroeger, N.

    2013-01-01

    Imaging studies are essential for both diagnosis and initial staging of multiple myeloma, as well as for differentiation from other monoclonal plasma cell diseases. Apart from conventional radiography, a variety of newer imaging modalities including whole-body low-dose-CT, whole-body MRI and 18F-FDG PET/CT may be used for detection of osseous and extraosseous myeloma manifestations. Despite of known limitations such as limited sensitivity and specificity and the inability to detect extraosseous lesions, conventional radiography still remains the gold standard for staging newly diagnosed myeloma, partly due to its wide availability and low costs. Whole-body low-dose CT is increasingly used due to its higher sensitivity for the detection of osseous lesions and its ability to diagnose extraosseous lesions, and is replacing conventional radiography at selected centres. The highest sensitivity for both detection of bone marrow disease and extraosseous lesions can be achieved with whole-body MRI or 18F-FDG PET/CT. Diffuse bone marrow infiltration may be visualized by whole-body MRI with high sensitivity. Whole-body MRI is at least recommended in all patients with normal conventional radiography and in all patients with an apparently solitary plasmacytoma of bone. To obtain the most precise readings, optimized examination protocols and dedicated radiologists and nuclear medicine physicians familiar with the complex and variable morphologies of myeloma lesions are required. (orig.)

  13. Multiple endocrine neoplasia detection on I-123 MIBG imaging

    Reinhardt, C.A.; McEwan, L.M.; Wong, J.C.H.

    2000-01-01

    Full text: An 123 I meta-iodobenzylguanidine (MIBG) scan was performed on a 54-year-old lady with familial phaeochromocytoma, to evaluate for bilateral or extra-adrenal disease. She has hypertension with raised catecholamines and CT evidence of a right adrenal phaeochromocytoma, and a female sibling with bilateral phaeochromocytoma. Thyroid blockade using Lugol's Iodine was given orally prior to intravenous administration of 370 MBq 123 I MIBG. Planar and SPECT imaging were acquired at 24 hours. There was intense uptake in the known right phaeochromocytoma. An unexpected finding was focal intense uptake in the region of the right thyroid lobe, which may be either a functioning paraganglioma arising from the cervical sympathetic ganglia or a medullary thyroid carcinoma (MTC). At 48 hours, a further image of the neck showed no changes. This was followed by a standard injection of 150 MBq 99 Tc m pertechnetate for thyroid scanning. Imaging obtained on 99 Tc m energy window setting showed a large hypofunctioning region in the right thyroid lobe, corresponding in location to the focal 123 I MIBG uptake. This is in keeping with a MTC, a neuroendocrine tumour, as other thyroid carcinomas are non-MIBG avid. A subsequent serum calcitonin assay showed elevated levels. The patient underwent surgical removal of the right phaeochromocytoma followed several weeks later by a right hemithyroidectomy. Histological reports confirmed the tumour diagnoses. The patient's familial phaeochromocytoma is therefore part of the multiple endocrine neoplasia syndrome Type 2A (MEN 2A). To date, biochemistry has not shown any evidence of hyperparathyroidism which occurs in 15-20 per cent of patients with MEN 2A. Copyright (2000) The Australian and New Zealand Society of Nuclear Medicine Inc

  14. Spinal cord magnetic resonance imaging in suspected multiple sclerosis

    Lycklama a Nijeholt, G.J.; Bergers, E.; Castelijns, J.A.; Barkhof, F.; Uitdehaag, B.M.J.; Polman, C.H.

    2000-01-01

    We examined the value of spinal cord magnetic resonance imaging (MRI) in the diagnostic work-up of multiple sclerosis (MS). Forty patients suspected of having MS were examined within 24 months after the start of symptoms. Disability was assessed, and symptoms were categorized as either brain or spinal cord. Work-up further included cerebrospinal fluid analysis and standard proton-density, T2-, and T1-weighted gadolinium-enhanced brain and spinal cord MRI. Patients were categorized as either clinically definite MS (n = 13), laboratory-supported definite MS (n = 14), or clinically probable MS (n = 4); four patients had clinically probable MS, and in nine MS was suspected. Spinal cord abnormalities were found in 35 of 40 patients (87.5 %), consisting of focal lesions in 31, only diffuse abnormalities in two, and both in two. Asymptomatic spinal cord lesions occurred in six patients. All patients with diffuse spinal cord abnormality had clear spinal cord symptoms and a primary progressive disease course. In clinically definite MS, the inclusion of spinal imaging increased the sensitivity of MRI to 100 %. Seven patients without a definite diagnosis had clinically isolated syndromes involving the spinal cord. Brain MRI was inconclusive, while all had focal spinal cord lesions which explained symptoms and ruled out other causes. Two other patients had atypical brain abnormalities suggesting ischemic/vascular disease. No spinal cord abnormalities were found, and during follow-up MS was ruled out. Spinal cord abnormalities are common in suspected MS, and may occur asymptomatic. Although diagnostic classification is seldom changed, spinal cord imaging increases diagnostic sensitivity of MRI in patients with suspected MS. In addition, patients with primary progressive MS may possibly be earlier diagnosed. Finally, differentiation with atypical lesions may be improved. (orig.)

  15. An Adaptive Ship Detection Scheme for Spaceborne SAR Imagery

    Xiangguang Leng

    2016-08-01

    Full Text Available With the rapid development of spaceborne synthetic aperture radar (SAR and the increasing need of ship detection, research on adaptive ship detection in spaceborne SAR imagery is of great importance. Focusing on practical problems of ship detection, this paper presents a highly adaptive ship detection scheme for spaceborne SAR imagery. It is able to process a wide range of sensors, imaging modes and resolutions. Two main stages are identified in this paper, namely: ship candidate detection and ship discrimination. Firstly, this paper proposes an adaptive land masking method using ship size and pixel size. Secondly, taking into account the imaging mode, incidence angle, and polarization channel of SAR imagery, it implements adaptive ship candidate detection in spaceborne SAR imagery by applying different strategies to different resolution SAR images. Finally, aiming at different types of typical false alarms, this paper proposes a comprehensive ship discrimination method in spaceborne SAR imagery based on confidence level and complexity analysis. Experimental results based on RADARSAT-1, RADARSAT-2, TerraSAR-X, RS-1, and RS-3 images demonstrate that the adaptive scheme proposed in this paper is able to detect ship targets in a fast, efficient and robust way.

  16. SAR: Stroke Authorship Recognition

    Shaheen, Sara

    2015-10-15

    Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR\\'s ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools. © 2015 The Eurographics Association and John Wiley & Sons Ltd.

  17. Multiple myoma: current recommendations for imaging; Multiples Myelom: Aktuelle Empfehlungen fuer die Bildgebung

    Hillengass, J. [Medizinische Universitaetsklinik, Abteilung fuer Haematologie, Onkologie und Rheumatologie, Heidelberg (Germany); Deutsches Krebsforschungszentrum, Abteilung Radiologie E010, Heidelberg (Germany); Delorme, S. [Deutsches Krebsforschungszentrum, Abteilung Radiologie E010, Heidelberg (Germany)

    2012-04-15

    Imaging in monoclonal plasma cell disease serves to detect end organ damage, i.e., osteoporosis or bone destruction. Diffuse or circumscribed bone marrow infiltration without damage to mineralized bone is so far not regarded as end organ damage. Skeletal plain x-ray film survey to detect bone destruction, osteoporosis or fractures. Whole body low-dose computed tomography (CT) and whole body magnetic resonance imaging (MRI) allow a more sensitive assessment of both mineralized bone and bone marrow, with greater patient comfort and in the case of MRI without ionizing radiation. According to the literature, cross-sectional imaging is clearly superior to skeletal surveys and MRI is more sensitive than CT. Every locally destructive lesion will be detectable with MRI but for assessing the damage to mineralized bone CT is indispensible. The sensitivities of positron emission tomography (PET)/CT and MRI are comparable. If available whole body MRI and whole body low dose CT should replace conventional skeletal surveys. This has already been implemented in several centers in Germany. For the initial diagnosis of monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma or symptomatic multiple myeloma, a whole-body MRI and a whole body low-dose CT should be performed. For MGUS and asymptomatic myeloma, whole body MRI only should be performed for follow-up until detection of first bone destruction. Patients with symptomatic multiple myeloma and known bone destruction will usually have whole body low-dose CT, supplemented by MRI studies where clinically required. (orig.) [German] Aufgabe der bildgebenden Diagnostik monoklonaler Plasmazellerkrankungen ist der Nachweis der Endorganschaedigung, d. h. der Osteoporose oder der Destruktion des mineralisierten Knochens. Die alleinige umschriebene oder diffuse Markrauminfiltration ohne knoecherne Destruktion gilt nach heutiger Konvention nicht als Endorganschaedigung. Konventioneller Roentgenskelettstatus

  18. Integrating interferometric SAR data with levelling measurements of land subsidence using geostatistics

    Zhou, Y.; Stein, A.; Molenaar, M.

    2003-01-01

    Differential Synthetic Aperture Radar (SAR) interferometric (D-InSAR) data of ground surface deformation are affected by several error sources associated with image acquisitions and data processing. In this paper, we study the use of D-InSAR for quantifying land subsidence due to groundwater

  19. On the Design of Radar Corner Reflectors for Deformation Monitoring in Multi-Frequency InSAR

    Matthew C. Garthwaite

    2017-06-01

    Full Text Available Trihedral corner reflectors are being increasingly used as point targets in deformation monitoring studies using interferometric synthetic aperture radar (InSAR techniques. The frequency and size dependence of the corner reflector Radar Cross Section (RCS means that no single design can perform equally in all the possible imaging modes and radar frequencies available on the currently orbiting Synthetic Aperture Radar (SAR satellites. Therefore, either a corner reflector design tailored to a specific data type or a compromise design for multiple data types is required. In this paper, I outline the practical and theoretical considerations that need to be made when designing appropriate radar targets, with a focus on supporting multi-frequency SAR data. These considerations are tested by performing field experiments on targets of different size using SAR images from TerraSAR-X, COSMO-SkyMed and RADARSAT-2. Phase noise behaviour in SAR images can be estimated by measuring the Signal-to-Clutter ratio (SCR in individual SAR images. The measured SCR of a point target is dependent on its RCS performance and the influence of clutter near to the deployed target. The SCR is used as a metric to estimate the expected InSAR displacement error incurred by the design of each target and to validate these observations against theoretical expectations. I find that triangular trihedral corner reflectors as small as 1 m in dimension can achieve a displacement error magnitude of a tenth of a millimetre or less in medium-resolution X-band data. Much larger corner reflectors (2.5 m or greater are required to achieve the same displacement error magnitude in medium-resolution C-band data. Compromise designs should aim to satisfy the requirements of the lowest SAR frequency to be used, providing that these targets will not saturate the sensor of the highest frequency to be used. Finally, accurate boresight alignment of the corner reflector can be critical to the overall

  20. Feature learning and change feature classification based on deep learning for ternary change detection in SAR images

    Gong, Maoguo; Yang, Hailun; Zhang, Puzhao

    2017-07-01

    Ternary change detection aims to detect changes and group the changes into positive change and negative change. It is of great significance in the joint interpretation of spatial-temporal synthetic aperture radar images. In this study, sparse autoencoder, convolutional neural networks (CNN) and unsupervised clustering are combined to solve ternary change detection problem without any supervison. Firstly, sparse autoencoder is used to transform log-ratio difference image into a suitable feature space for extracting key changes and suppressing outliers and noise. And then the learned features are clustered into three classes, which are taken as the pseudo labels for training a CNN model as change feature classifier. The reliable training samples for CNN are selected from the feature maps learned by sparse autoencoder with certain selection rules. Having training samples and the corresponding pseudo labels, the CNN model can be trained by using back propagation with stochastic gradient descent. During its training procedure, CNN is driven to learn the concept of change, and more powerful model is established to distinguish different types of changes. Unlike the traditional methods, the proposed framework integrates the merits of sparse autoencoder and CNN to learn more robust difference representations and the concept of change for ternary change detection. Experimental results on real datasets validate the effectiveness and superiority of the proposed framework.

  1. Probabilistic images (PBIS): A concise image representation technique for multiple parameters

    Wu, L.C.; Yeh, S.H.; Chen, Z.; Liu, R.S.

    1984-01-01

    Based on m parametric images (PIs) derived from a dynamic series (DS), each pixel of DS is regarded as an m-dimensional vector. Given one set of normal samples (pixels) N and another of abnormal samples A, probability density functions (pdfs) of both sets are estimated. Any unknown sample is classified into N or A by calculating the probability of its being in the abnormal set using the Bayes' theorem. Instead of estimating the multivariate pdfs, a distance ratio transformation is introduced to map the m-dimensional sample space to one dimensional Euclidean space. Consequently, the image that localizes the regional abnormalities is characterized by the probability of being abnormal. This leads to the new representation scheme of PBIs. Tc-99m HIDA study for detecting intrahepatic lithiasis (IL) was chosen as an example of constructing PBI from 3 parameters derived from DS and such a PBI was compared with those 3 PIs, namely, retention ratio image (RRI), peak time image (TNMAX) and excretion mean transit time image (EMTT). 32 normal subjects and 20 patients with proved IL were collected and analyzed. The resultant sensitivity and specificity of PBI were 97% and 98% respectively. They were superior to those of any of the 3 PIs: RRI (94/97), TMAX (86/88) and EMTT (94/97). Furthermore, the contrast of PBI was much better than that of any other image. This new image formation technique, based on multiple parameters, shows the functional abnormalities in a structural way. Its good contrast makes the interpretation easy. This technique is powerful compared to the existing parametric image method

  2. Segmentation of multiple sclerosis lesions in MR images: a review

    Mortazavi, Daryoush; Kouzani, Abbas Z. [Deakin University, School of Engineering, Geelong, Victoria (Australia); Soltanian-Zadeh, Hamid [Henry Ford Health System, Image Analysis Laboratory, Radiology Department, Detroit, MI (United States); University of Tehran, Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, Tehran (Iran, Islamic Republic of); School of Cognitive Sciences, Institute for Studies in Theoretical Physics and Mathematics (IPM), Tehran (Iran, Islamic Republic of)

    2012-04-15

    Multiple sclerosis (MS) is an inflammatory demyelinating disease that the parts of the nervous system through the lesions generated in the white matter of the brain. It brings about disabilities in different organs of the body such as eyes and muscles. Early detection of MS and estimation of its progression are critical for optimal treatment of the disease. For diagnosis and treatment evaluation of MS lesions, they may be detected and segmented in Magnetic Resonance Imaging (MRI) scans of the brain. However, due to the large amount of MRI data to be analyzed, manual segmentation of the lesions by clinical experts translates into a very cumbersome and time consuming task. In addition, manual segmentation is subjective and prone to human errors. Several groups have developed computerized methods to detect and segment MS lesions. These methods are not categorized and compared in the past. This paper reviews and compares various MS lesion segmentation methods proposed in recent years. It covers conventional methods like multilevel thresholding and region growing, as well as more recent Bayesian methods that require parameter estimation algorithms. It also covers parameter estimation methods like expectation maximization and adaptive mixture model which are among unsupervised techniques as well as kNN and Parzen window methods that are among supervised techniques. Integration of knowledge-based methods such as atlas-based approaches with Bayesian methods increases segmentation accuracy. In addition, employing intelligent classifiers like Fuzzy C-Means, Fuzzy Inference Systems, and Artificial Neural Networks reduces misclassified voxels. (orig.)

  3. Segmentation of multiple sclerosis lesions in MR images: a review

    Mortazavi, Daryoush; Kouzani, Abbas Z.; Soltanian-Zadeh, Hamid

    2012-01-01

    Multiple sclerosis (MS) is an inflammatory demyelinating disease that the parts of the nervous system through the lesions generated in the white matter of the brain. It brings about disabilities in different organs of the body such as eyes and muscles. Early detection of MS and estimation of its progression are critical for optimal treatment of the disease. For diagnosis and treatment evaluation of MS lesions, they may be detected and segmented in Magnetic Resonance Imaging (MRI) scans of the brain. However, due to the large amount of MRI data to be analyzed, manual segmentation of the lesions by clinical experts translates into a very cumbersome and time consuming task. In addition, manual segmentation is subjective and prone to human errors. Several groups have developed computerized methods to detect and segment MS lesions. These methods are not categorized and compared in the past. This paper reviews and compares various MS lesion segmentation methods proposed in recent years. It covers conventional methods like multilevel thresholding and region growing, as well as more recent Bayesian methods that require parameter estimation algorithms. It also covers parameter estimation methods like expectation maximization and adaptive mixture model which are among unsupervised techniques as well as kNN and Parzen window methods that are among supervised techniques. Integration of knowledge-based methods such as atlas-based approaches with Bayesian methods increases segmentation accuracy. In addition, employing intelligent classifiers like Fuzzy C-Means, Fuzzy Inference Systems, and Artificial Neural Networks reduces misclassified voxels. (orig.)

  4. High intensity region segmentation in MR imaging of multiple sclerosis

    Rodrigo, F; Filipuzzi, M; Graffigna, J P; Isoardi, R; Noceti, M

    2013-01-01

    Numerous pathologies are often manifest in Magnetic Resonance Imaging (MRI) as hyperintense or bright regions as compared to normal tissue. It is of particular interest to develop an algorithm to detect, identify and define those Regions of Interest (ROI) when analyzing MRI studies, particularly for lesions of Multiple Sclerosis (MS). The objective of this study is to analyze those parameters which optimize segmentation of the areas of interest. To establish which areas should be considered as hyperintense regions, we developed a database (DB), with studies of patients diagnosed with MS. This disease causes axonal demyelination and it is expressed as bright regions in PD, T2 and FLAIR MRI sequences. Thus, with more than 4300 hyperintense regions validated by an expert physician, an algorithm was developed to detect such spots, approximating the results the expert obtained. Alongside these hyperintense lesion regions, it also detected bone regions with high intensity levels, similar to the intensity of the lesions, but with other features that allow a good differentiation.The algorithm will then detect ROIs with similar intensity levels and performs classification through data mining techniques

  5. Monitoring Building Deformation with InSAR: Experiments and Validation

    Yang, Kui; Yan, Li; Huang, Guoman; Chen, Chu; Wu, Zhengpeng

    2016-01-01

    Synthetic Aperture Radar Interferometry (InSAR) techniques are increasingly applied for monitoring land subsidence. The advantages of InSAR include high accuracy and the ability to cover large areas; nevertheless, research validating the use of InSAR on building deformation is limited. In this paper, we test the monitoring capability of the InSAR in experiments using two landmark buildings; the Bohai Building and the China Theater, located in Tianjin, China. They were selected as real examples to compare InSAR and leveling approaches for building deformation. Ten TerraSAR-X images spanning half a year were used in Permanent Scatterer InSAR processing. These extracted InSAR results were processed considering the diversity in both direction and spatial distribution, and were compared with true leveling values in both Ordinary Least Squares (OLS) regression and measurement of error analyses. The detailed experimental results for the Bohai Building and the China Theater showed a high correlation between InSAR results and the leveling values. At the same time, the two Root Mean Square Error (RMSE) indexes had values of approximately 1 mm. These analyses show that a millimeter level of accuracy can be achieved by means of InSAR technique when measuring building deformation. We discuss the differences in accuracy between OLS regression and measurement of error analyses, and compare the accuracy index of leveling in order to propose InSAR accuracy levels appropriate for monitoring buildings deformation. After assessing the advantages and limitations of InSAR techniques in monitoring buildings, further applications are evaluated. PMID:27999403

  6. Monitoring Building Deformation with InSAR: Experiments and Validation

    Kui Yang

    2016-12-01

    Full Text Available Synthetic Aperture Radar Interferometry (InSAR techniques are increasingly applied for monitoring land subsidence. The advantages of InSAR include high accuracy and the ability to cover large areas; nevertheless, research validating the use of InSAR on building deformation is limited. In this paper, we test the monitoring capability of the InSAR in experiments using two landmark buildings; the Bohai Building and the China Theater, located in Tianjin, China. They were selected as real examples to compare InSAR and leveling approaches for building deformation. Ten TerraSAR-X images spanning half a year were used in Permanent Scatterer InSAR processing. These extracted InSAR results were processed considering the diversity in both direction and spatial distribution, and were compared with true leveling values in both Ordinary Least Squares (OLS regression and measurement of error analyses. The detailed experimental results for the Bohai Building and the China Theater showed a high correlation between InSAR results and the leveling values. At the same time, the two Root Mean Square Error (RMSE indexes had values of approximately 1 mm. These analyses show that a millimeter level of accuracy can be achieved by means of InSAR technique when measuring building deformation. We discuss the differences in accuracy between OLS regression and measurement of error analyses, and compare the accuracy index of leveling in order to propose InSAR accuracy levels appropriate for monitoring buildings deformation. After assessing the advantages and limitations of InSAR techniques in monitoring buildings, further applications are evaluated.

  7. Use of time series of optical and SAR images in the estimation of snow cover for the optimization of water use in the Andes of Argentina and Chile

    Salinas de Salmuni, Graciela; Cabezas Cartes, Ricardo; Menicocci, Felix

    2014-05-01

    operational application because it is simple and easy to implement. From the analysis of multitemporal study in the region using COSMO SkyMed images, it is observed that the values of wet snow coverage, obtained along the 2012 hydrological cycle, are consistent with the dynamics of the same: The study area has a high rise and steep relief (up to 6400m), therefore the shadows loom large, processing optical and SAR images improve the results. The behavior of the accumulation process (winter) and snowmelt (summer), is influenced by the elevation of the different study areas. A high percentage (49%) of surface snow at higher elevations to 3000 m. This is due to the accumulation of snow increases with elevation, by the combined effect of low temperatures and increased precipitation snowy orographic effect. In studies of wet meadows with optical images, a high correspondence between the spectral classes and vigor of vegetation and soil moisture (seen in the field) so are considered as indicators of degradation of these ecosystems was observed

  8. Development of an image intensifier-TV digital imaging system with a multiple-slit scanning x-ray beam

    Kume, Y.; Doi, K.

    1986-01-01

    The authors are developing a new digital x-ray imaging system employing a multiple-slit assembly (MSA) and an image intensifier (II)-TV digital system. The final image consisting of primary radiation is digitally reconstructed from multiple slit images obtained with the MSA. This system can significantly reduce the scattered radiation from an object and the veiling glare from II-TV system. The quality of the reconstructed image is related to many parameters, such as slit width, the number of image frames, and the image reconstruction algorithm. They present the effect of these various parameters on basic imaging properties and the practicability of the method in comparison with conventional wide beam imaging

  9. SAR: Stroke Authorship Recognition

    Shaheen, Sara; Rockwood, Alyn; Ghanem, Bernard

    2015-01-01

    Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR's ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools. © 2015 The Eurographics Association and John Wiley & Sons Ltd.

  10. NOAA high resolution sea surface winds data from Synthetic Aperture Radar (SAR) on the RADARSAT-2 satellite

    National Oceanic and Atmospheric Administration, Department of Commerce — Synthetic Aperture Radar (SAR)-derived high resolution wind products are calculated from high resolution SAR images of normalized radar cross section (NRCS) of the...

  11. Mapping mountain meadow with high resolution and polarimetric SAR data

    Tian, Bangsen; Li, Zhen; Xu, Juan; Fu, Sitao; Liu, Jiuli

    2014-01-01

    This paper presents a method to map the large grassland in the eastern margin of the Tibetan Plateau with the high resolution polarimetric SAR (PolSAR) imagery. When PolSAR imagery is used for land cover classification, the brightness of a SAR image is affected by topography due to varying projection between ground and image coordinates. The objective of this paper is twofold: (1) we first extend the theory of SAR terrain correction to the polarimetric case, to utilize the entire available polarimetric signature, where correction is performed explicitly based on a matrix format like covariance matrix. (2) Next, the orthoectified PolSAR is applied to classify mountain meadow and investigate the potential of PolSAR in mapping grassland. In this paper, the gamma naught radiometric correction estimates the local illuminated area at each grid point in the radar geometry. Then, each element of the coherency matrix is divided by the local area to produce a polarimetric product. Secondly, the impact of radiometric correction upon classification accuracy is investigated. A supervised classification is performed on the orthorectified Radarsat-2 PolSAR to map the spatial distribution of meadow and evaluate monitoring capabilities of mountain meadow

  12. Satellite sar detection of hurricane helene (2006)

    Ju, Lian; Cheng, Yongcun; Xu, Qing

    2013-01-01

    In this paper, the wind structure of hurricane Helene (2006) over the Atlantic Ocean is investigated from a C-band RADARSAT-1 synthetic aperture radar (SAR) image acquired on 20 September 2006. First, the characteristics, e.g., the center, scale and area of the hurricane eye (HE) are determined. ...... observations from the stepped frequency microwave radiometer (SFMR) on NOAA P3 aircraft. All the results show the capability of hurricane monitoring by satellite SAR. Copyright © 2013 by the International Society of Offshore and Polar Engineers (ISOPE)....

  13. Stellwagen Bank National Marine Sanctuary - Synthetic Aperture Radar (SAR) Imagery

    National Oceanic and Atmospheric Administration, Department of Commerce — This geodatabase contains Synthetic Aperture Radar images (SAR), which consist of a fine resolution (12.5-50m), two-dimensional radar backscatter map of the...

  14. Evaluation of RISAT-1 SAR data for tropical forestry applications

    Padalia, Hitendra; Yadav, Sadhana

    2017-01-01

    India launched C band (5.35 GHz) RISAT-1 (Radar Imaging Satellite-1) on 26th April, 2012, equipped with the capability to image the Earth at multiple-resolutions and -polarizations. In this study the potential of Fine Resolution Strip (FRS) modes of RISAT-1 was evaluated for characterization and classification forests and estimation of biomass of early growth stages. The study was carried out at the two sites located in the foothills of western Himalaya, India. The pre-processing and classification of FRS-1 SAR data was performed using PolSAR Pro ver. 5.0 software. The scattering mechanisms derived from m-chi decomposition of FRS-1 RH/RV data were found physically meaningful for the characterization of various surface features types. The forest and land use type classification of the study area was developed applying Support Vector Machine (SVM) algorithm on FRS-1 derived appropriate polarimetric features. The biomass of early growth stages of Eucalyptus (up to 60 ton/ha) was estimated developing a multi-linear regression model using C band σ0 HV and σ0 HH backscatter information. The study outcomes has promise for wider application of RISAT-1 data for forest cover monitoring, especially for the tropical regions.

  15. Inversion Algorithms and PS Detection in SAR Tomography, Case Study of Bucharest City

    C. Dănişor

    2016-06-01

    Full Text Available Synthetic Aperture Radar (SAR tomography can reconstruct the elevation profile of each pixel based on a set of co-registered complex images of a scene. Its main advantage over classical interferometric methods consists in the capability to improve the detection of single persistent scatterers as well as to enable the detection of multiple scatterers interfering within the same pixel. In this paper, three tomographic algorithms are compared and applied to a dataset of 32 images to generate the elevation map of dominant scatterers from a scene. Targets which present stable proprieties over time - Persistent Scatterers (PS are then detected based on reflectivity functions reconstructed with Capon filtering.

  16. Context and Quasi-Invariants in Automatic Target Recognition (ATR) with Synthetic Aperture Radar (SAR) Imagery

    Binford, Thomas

    2000-01-01

    .... Experiments based on conventional recognition techniques were conducted for comparisons. Study of persistent scattering confirms the feasibility of implementing a SAR ATR system using physical image features...

  17. New challenges for a SAR toolbox

    Loreaux, P.; Quin, G.

    2013-01-01

    High resolution multi-frequency synthetic aperture radar (SAR) imagery, available since early 2008, brings all weather capability and day/night operability in support of safeguards verification. Today, a combined approach of high resolution optical and radar imagery in monitoring exercise would enable looking at any area of interest on daily basis. One of the challenges is the co-registration of SAR images acquired with different acquisition mode and also with different optical images. We show in this paper the on-going research work to find a general co-register method and an automatic tool to detect changes. Before having an operational co-register tool, a method to find automatically tie points between SAR images acquired with different acquisition mode and with optical images has to be developed. Concerning an automatic change detection method we can conclude that the study of the Harmonic mean, Geometric mean and Arithmetic mean, enables several applications like change detection for SAR imagery. Thus, we developed the MAGMA (Method for Arithmetic and Geometric Means Analysis) change detection method. As shown in this paper, the MAGMA method improves the Maximum Likelihood techniques like GLRT, using Information-Theory concepts to detect changes between SAR amplitude images. The major improvement consists in a lower false detection rate, especially in low amplitude areas. The second improvement consists in a better location of the changes in clearly delimited areas, which enables precise interpretations. Results presented here reveal the potential of high resolution radar imagery for a baseline description of some sites, change detection based on repeat pass imagery acquisitions and site specific constraints in coherent change detection due to cover conditions. (A.C.)

  18. Multiple Voices, Multiple Realities: Self-Defined Images of Self among Adolescent Hispanic English Language Learners

    Ajayi, Lasisi J.

    2006-01-01

    Acquisition of multiple identities to negotiate new forms of social participation and the concomitant attendant multiple languages and multiple cultures is "sine qua non" to success in English language learning classrooms. This study therefore, investigates how middle school Hispanic students reconceptualize their identities to negotiate…

  19. Ground Subsidence over Beijing-Tianjin-Hebei Region during Three Periods of 1992 to 2014 Monitored by Interferometric SAR

    ZHANG Yonghong

    2016-09-01

    Full Text Available The Beijing-Tianjin-Hebei region suffers the most serious ground subsidence in China, which has caused huge economic losses every year. Therefore, ground subsidence was listed as an important mission in the project of geographic conditions monitoring over Beijing-Tianjin-Hebei launched by the National Administration of Surveying, Mapping and Geoinformation in 2013. In this paper, we propose a methodology of ground subsidence monitoring over wide area, which is entitled "multiple master-image coherent target small-baseline interferometric SAR (MCTSB-InSAR". MCTSB-InSAR is an improved time series InSAR technique with some unique features. SAR datasets used for ground subsidence monitoring over the Beijing-Tianjin-Hebei region include ERS-1/2 SAR images acquired between 1992 to 2000, ENVISAT ASAR images acquired between 2003 to 2010 and RADARSAT-2 images acquired between 2012 to 2014. This research represents a first ever effort on mapping ground subsidence over Beijing-Tianjin-Hebei region and over such as a long time span in China. In comparison with more than 120 leveling measurements collected in Beijing and Tianjin, the derived subsidence velocity has the accuracy of 8.7mm/year (1992—2000, 4.7mm/year (2003—2010, and 5.4mm/year (2012—2014 respectively. The spatial-temporal characteristics of the development of ground subsidence in Beijing and Tianjin are analyzed. In general, ground subsidence in Beijing kept continuously expanding in the period of 1992 to 2014. While, ground subsidence in Tianjin had already been serious in 1990s, had dramatically expanded during 2000s, and started to alleviate in recent years. The monitoring result is of high significance for prevention and mitigation of ground subsidence disaster, for making development plan, for efficient and effective utilization of water resource, and for adjustment of economic framework of this region. The result also indicates the effectiveness and reliability of the MCTSB-InSAR

  20. Assessing ScanSAR Interferometry for Deformation Studies

    Buckley, S. M.; Gudipati, K.

    2007-12-01

    There is a trend in civil satellite SAR mission design to implement an imaging strategy that incorporates both stripmap mode and ScanSAR imaging. This represents a compromise between high resolution data collection and a desire for greater spatial coverage and more frequent revisit times. However, mixed mode imaging can greatly reduce the number of stripmap images available for measuring subtle ground deformation. Although ScanSAR-ScanSAR and ScanSAR-stripmap repeat-pass interferometry have been demonstrated, these approaches are infrequently used for single interferogram formation and nonexistent for InSAR time series analysis. For future mission design, e.g., a dedicated US InSAR mission, the effect of various ScanSAR system parameter choices on InSAR time series analysis also remains unexplored. Our objective is to determine the utility of ScanSAR differential interferometry. We will demonstrate the use of ScanSAR interferograms for several previous deformation studies: localized and broad-scale urban land subsidence, tunneling, volcanic surface movements and several examples associated with the seismic cycle. We also investigate the effect of various ScanSAR burst synchronization levels on our ability to detect and make quality measurements of deformation. To avoid the issues associated with Envisat ScanSAR burst alignment and to exploit a decade of InSAR measurements, we simulate ScanSAR data by bursting (throwing away range lines of) ERS-1/2 data. All the burst mode datasets are processed using a Modified SPECAN algorithm. To investigate the effects of burst misalignment, a number of cases with varying degrees of burst overlap are considered. In particular, we look at phase decorrelation as a function of percentage of burst overlap. Coherence clearly reduces as the percentage of overlap decreases and we find a useful threshold of 40-70% burst overlap depending on the study site. In order to get a more generalized understanding for different surface conditions

  1. Monitoring of Oil Exploitation Infrastructure by Combining Unsupervised Pixel-Based Classification of Polarimetric SAR and Object-Based Image Analysis

    Simon Plank

    2014-12-01

    Full Text Available In developing countries, there is a high correlation between the dependence of oil exports and violent conflicts. Furthermore, even in countries which experienced a peaceful development of their oil industry, land use and environmental issues occur. Therefore, independent monitoring of oil field infrastructure may support problem solving. Earth observation data enables fast monitoring of large areas which allows comparing the real amount of land used by the oil exploitation and the companies’ contractual obligations. The target feature of this monitoring is the infrastructure of the oil exploitation, oil well pads—rectangular features of bare land covering an area of approximately 50–60 m × 100 m. This article presents an automated feature extraction procedure based on the combination of a pixel-based unsupervised classification of polarimetric synthetic aperture radar data (PolSAR and an object-based post-classification. The method is developed and tested using dual-polarimetric TerraSAR-X imagery acquired over the Doba basin in south Chad. The advantages of PolSAR are independence of the cloud coverage (vs. optical imagery and the possibility of detailed land use classification (vs. single-pol SAR. The PolSAR classification uses the polarimetric Wishart probability density function based on the anisotropy/entropy/alpha decomposition. The object-based post-classification refinement, based on properties of the feature targets such as shape and area, increases the user’s accuracy of the methodology by an order of a magnitude. The final achieved user’s and producer’s accuracy is 59%–71% in each case (area based accuracy assessment. Considering only the numbers of correctly/falsely detected oil well pads, the user’s and producer’s accuracies increase to even 74%–89%. In an iterative training procedure the best suited polarimetric speckle filter and processing parameters of the developed feature extraction procedure are

  2. MRI screening on bone ischemia of hip and knee in recovered SARS patients

    Cheng Xiaoguang; Qu Hui; Liu Wei; Sun Jing; Cheng Kebin; Feng Suchen; Li Xiaosong

    2004-01-01

    Objective: To screen ischemia in the hip and knee joints of recovered SARS patients with MRI, and to investigate the prevalence rate of bone ischemia in those patients and its relationship with the use of steroid. Methods: Hip and knee MRI examinations were performed in 76 recovered SARS patients. There were 17 males and 59 females. Eight patients were treated without steroid, while 68 patients with steroid. Dose and duration of steroid usage were available in 30 out of 68 patients. The MRI images were read by senior radiologists to determine whether bone ischemia and/or osteonecrosis was present. Appropriate statistic analysis was performed to determine the significance of difference between groups. Results: (1) The MRI appearance of osteonecrosis in femoral head and condyle and bone infarct in bone marrow found in SARS patients was identical to those caused by other conditions (including steroid usage in other diseases). (2) No one of 8 SARS without steroid developed osteonecrosis, while 25 out of 68 steroid users had osteonecrosis found by MRI screening, and the difference in prevalence of osteonecrosis between these 2 groups was significant. In 25 patients with osteonecrosis, 20 of them involved more than one joints. Osteonecrosis involved 32 femoral heads, 26 femoral condyles, and 6 in femoral and tibial shafts. Thirteen patients with osteonecrosis had greater total steroid dose, greater daily dose, and longer duration than those (17 patients) without osteonecrosis, however, the differences between the two groups were not statistically significant. Sixty-four patients out of 76 complained pain in joints, 50 of them had multiple joint pains. The pain was reported in hips in 40 cases, followed by knees in 36, low backs in 10, shoulders in 7, and wrists in 4, respectively. The differences in frequency of pain between steroid users and non-steroid users, as well as between osteonecrosis and non-osteonecrosis were not significant. Conclusion: MRI is recommended for

  3. Positron annihilation imaging device using multiple offset rings of detectors

    Thompson, C.J.

    1981-01-01

    This patent application relates to a positron annihilation imaging device comprising two or more coaxial circular arrays of detectors (2,2'), with the detectors in one array angularly offset with respect to the detectors in the adjacent array to detect more than one tomographic image simultaneously through different cross-sections of a patient. (author)

  4. Multiple-image encryption via lifting wavelet transform and XOR operation based on compressive ghost imaging scheme

    Li, Xianye; Meng, Xiangfeng; Yang, Xiulun; Wang, Yurong; Yin, Yongkai; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

    2018-03-01

    A multiple-image encryption method via lifting wavelet transform (LWT) and XOR operation is proposed, which is based on a row scanning compressive ghost imaging scheme. In the encryption process, the scrambling operation is implemented for the sparse images transformed by LWT, then the XOR operation is performed on the scrambled images, and the resulting XOR images are compressed in the row scanning compressive ghost imaging, through which the ciphertext images can be detected by bucket detector arrays. During decryption, the participant who possesses his/her correct key-group, can successfully reconstruct the corresponding plaintext image by measurement key regeneration, compression algorithm reconstruction, XOR operation, sparse images recovery, and inverse LWT (iLWT). Theoretical analysis and numerical simulations validate the feasibility of the proposed method.

  5. Simultaneous ECG-gated PET imaging of multiple mice

    Seidel, Jurgen; Bernardo, Marcelino L.; Wong, Karen J.; Xu, Biying; Williams, Mark R.; Kuo, Frank; Jagoda, Elaine M.; Basuli, Falguni; Li, Changhui; Griffiths, Gary L.

    2014-01-01

    Introduction: We describe and illustrate a method for creating ECG-gated PET images of the heart for each of several mice imaged at the same time. The method is intended to increase “throughput” in PET research studies of cardiac dynamics or to obtain information derived from such studies, e.g. tracer concentration in end-diastolic left ventricular blood. Methods: An imaging bed with provisions for warming, anesthetic delivery, etc., was fabricated by 3D printing to allow simultaneous PET imaging of two side-by-side mice. After electrode attachment, tracer injection and placement of the animals in the scanner field of view, ECG signals from each animal were continuously analyzed and independent trigger markers generated whenever an R-wave was detected in each signal. PET image data were acquired in “list” mode and these trigger markers were inserted into this list along with the image data. Since each mouse is in a different spatial location in the FOV, sorting of these data using trigger markers first from one animal and then the other yields two independent and correctly formed ECG-gated image sequences that reflect the dynamical properties of the heart during an “average” cardiac cycle. Results: The described method yields two independent ECG-gated image sequences that exhibit the expected properties in each animal, e.g. variation of the ventricular cavity volumes from maximum to minimum and back during the cardiac cycle in the processed animal with little or no variation in these volumes during the cardiac cycle in the unprocessed animal. Conclusion: ECG-gated image sequences for each of several animals can be created from a single list mode data collection using the described method. In principle, this method can be extended to more than two mice (or other animals) and to other forms of physiological gating, e.g. respiratory gating, when several subjects are imaged at the same time

  6. Land cover in the Guayas Basin using SAR images from low resolution ASAR Global mode to high resolution Sentinel-1 images

    Bourrel, Luc; Brodu, Nicolas; Frappart, Frédéric

    2016-04-01

    Remotely sensed images allow a frequent monitoring of land cover variations at regional and global scale. Recently launched Sentinel-1 satellite offers a global cover of land areas at an unprecedented spatial (20 m) and temporal (6 days at the Equator). We propose here to compare the performances of commonly used supervised classification techniques (i.e., k-nearest neighbors, linear and Gaussian support vector machines, naive Bayes, linear and quadratic discriminant analyzes, adaptative boosting, loggit regression, ridge regression with one-vs-one voting, random forest, extremely randomized trees) for land cover applications in the Guayas Basin, the largest river basin of the Pacific coast of Ecuator (area ~32,000 km²). The reason of this choice is the importance of this region in Ecuatorian economy as its watershed represents 13% of the total area of Ecuador where 40% of the Ecuadorian population lives. It also corresponds to the most productive region of Ecuador for agriculture and aquaculture. Fifty percents of the country shrimp farming production comes from this watershed, and represents with agriculture the largest source of revenue of the country. Similar comparisons are also performed using ENVISAT ASAR images acquired in global mode (1 km of spatial resolution). Accuracy of the results will be achieved using land cover map derived from multi-spectral images.

  7. Magnetic resonance imaging correlates of bee sting induced multiple organ dysfunction syndrome: A case report.

    Das, Sushant K; Zeng, Li-Chuan; Li, Bing; Niu, Xiang-Ke; Wang, Jing-Liang; Bhetuwal, Anup; Yang, Han-Feng

    2014-09-28

    Occasionally systemic complications with high risk of death, such as multiple organ dysfunction syndrome (MODS), can occur following multiple bee stings. This case study reports a patient who presented with MODS, i.e., acute kidney injury, hepatic and cardiac dysfunction, after multiple bee stings. The standard clinical findings were then correlated with magnetic resonance imaging (MRI) findings, which demonstrates that MRI may be utilized as a simpler tool to use than other multiple diagnostics.

  8. Crop Classification by Polarimetric SAR

    Skriver, Henning; Svendsen, Morten Thougaard; Nielsen, Flemming

    1999-01-01

    Polarimetric SAR-data of agricultural fields have been acquired by the Danish polarimetric L- and C-band SAR (EMISAR) during a number of missions at the Danish agricultural test site Foulum during 1995. The data are used to study the classification potential of polarimetric SAR data using...

  9. MR imaging of multiple fibroadenoma in breast: comparison with color doppler images and histologic findings

    Chung, Soo Young; Yang, Ik; Park, Hai Jung; Lee, Yul; Chung, Bong Wha; Ahn, Hye Kyung [Hallym Univ. College of Medicine, Seoul (Korea, Republic of)

    1997-10-01

    To understand the different signal intensities seen on contrast enhanced magnetic resonance imaging (MRI) in multiple fibroadenoma of the breast, and to compare these with color Doppler ultrasonographic (CDUS) and histologic findings. MRI (1.0 Tesla, TIWI, T2WI, 3D-gradient echo dynamic contrast enhancement study) findings of 24 histologically proven cases of fibroadenoma in five patients were evaluated and compared with the histologic components (myxoid, adenomatous, fibrous). In addition, vascular flow, as seen on CDUS and histologic section, was compared. The observed degree of signal intensity waw classified into three groups, as follows: negative, 8.3%, mild to moderate, 54.2%; marked, 37.5%. On histologic section, the greater the fibrotic component, the higher the intensity of MRI enhancement, the greater the glandular component, and the intensity. CDUS showed vascular flow in only one tumor larger than 3cm in diameter. Vascular patterns of tumors on CDUS were dots in mass and detouring pattern, but in this case and in strongly enhanced cases, tumor vascularity-as seen on histologic section-showed no significant increase. Different signal intensities seen on contrast enhanced MRI in multiple fibroadenoma of the breast may be related more to the amount of glandular and fibrotic component than to increased tumor vascularity.

  10. MR imaging of multiple fibroadenoma in breast: comparison with color doppler images and histologic findings

    Chung, Soo Young; Yang, Ik; Park, Hai Jung; Lee, Yul; Chung, Bong Wha; Ahn, Hye Kyung

    1997-01-01

    To understand the different signal intensities seen on contrast enhanced magnetic resonance imaging (MRI) in multiple fibroadenoma of the breast, and to compare these with color Doppler ultrasonographic (CDUS) and histologic findings. MRI (1.0 Tesla, TIWI, T2WI, 3D-gradient echo dynamic contrast enhancement study) findings of 24 histologically proven cases of fibroadenoma in five patients were evaluated and compared with the histologic components (myxoid, adenomatous, fibrous). In addition, vascular flow, as seen on CDUS and histologic section, was compared. The observed degree of signal intensity waw classified into three groups, as follows: negative, 8.3%, mild to moderate, 54.2%; marked, 37.5%. On histologic section, the greater the fibrotic component, the higher the intensity of MRI enhancement, the greater the glandular component, and the intensity. CDUS showed vascular flow in only one tumor larger than 3cm in diameter. Vascular patterns of tumors on CDUS were dots in mass and detouring pattern, but in this case and in strongly enhanced cases, tumor vascularity-as seen on histologic section-showed no significant increase. Different signal intensities seen on contrast enhanced MRI in multiple fibroadenoma of the breast may be related more to the amount of glandular and fibrotic component than to increased tumor vascularity

  11. Multiple-image hiding using super resolution reconstruction in high-frequency domains

    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.

  12. Image analysis of multiple moving wood pieces in real time

    Wang, Weixing

    2006-02-01

    This paper presents algorithms for image processing and image analysis of wood piece materials. The algorithms were designed for auto-detection of wood piece materials on a moving conveyor belt or a truck. When wood objects on moving, the hard task is to trace the contours of the objects in n optimal way. To make the algorithms work efficiently in the plant, a flexible online system was designed and developed, which mainly consists of image acquisition, image processing, object delineation and analysis. A number of newly-developed algorithms can delineate wood objects with high accuracy and high speed, and in the wood piece analysis part, each wood piece can be characterized by a number of visual parameters which can also be used for constructing experimental models directly in the system.

  13. Examination of cognitive fatigue in multiple sclerosis using functional magnetic resonance imaging and diffusion tensor imaging.

    Genova, Helen M; Rajagopalan, Venkateswaran; Deluca, John; Das, Abhijit; Binder, Allison; Arjunan, Aparna; Chiaravalloti, Nancy; Wylie, Glenn

    2013-01-01

    The present study investigated the neural correlates of cognitive fatigue in Multiple Sclerosis (MS), looking specifically at the relationship between self-reported fatigue and objective measures of cognitive fatigue. In Experiment 1, functional magnetic resonance imaging (fMRI) was used to examine where in the brain BOLD activity covaried with "state" fatigue, assessed during performance of a task designed to induce cognitive fatigue while in the scanner. In Experiment 2, diffusion tensor imaging (DTI) was used to examine where in the brain white matter damage correlated with increased "trait" fatigue in individuals with MS, assessed by the Fatigue Severity Scale (FSS) completed outside the scanning session. During the cognitively fatiguing task, the MS group had increased brain activity associated with fatigue in the caudate as compared with HCs. DTI findings revealed that reduced fractional anisotropy in the anterior internal capsule was associated with increased self-reported fatigue on the FSS. Results are discussed in terms of identifying a "fatigue-network" in MS.

  14. Examination of cognitive fatigue in multiple sclerosis using functional magnetic resonance imaging and diffusion tensor imaging.

    Helen M Genova

    Full Text Available The present study investigated the neural correlates of cognitive fatigue in Multiple Sclerosis (MS, looking specifically at the relationship between self-reported fatigue and objective measures of cognitive fatigue. In Experiment 1, functional magnetic resonance imaging (fMRI was used to examine where in the brain BOLD activity covaried with "state" fatigue, assessed during performance of a task designed to induce cognitive fatigue while in the scanner. In Experiment 2, diffusion tensor imaging (DTI was used to examine where in the brain white matter damage correlated with increased "trait" fatigue in individuals with MS, assessed by the Fatigue Severity Scale (FSS completed outside the scanning session. During the cognitively fatiguing task, the MS group had increased brain activity associated with fatigue in the caudate as compared with HCs. DTI findings revealed that reduced fractional anisotropy in the anterior internal capsule was associated with increased self-reported fatigue on the FSS. Results are discussed in terms of identifying a "fatigue-network" in MS.

  15. Program Merges SAR Data on Terrain and Vegetation Heights

    Siqueira, Paul; Hensley, Scott; Rodriguez, Ernesto; Simard, Marc

    2007-01-01

    X/P Merge is a computer program that estimates ground-surface elevations and vegetation heights from multiple sets of data acquired by the GeoSAR instrument [a terrain-mapping synthetic-aperture radar (SAR) system that operates in the X and bands]. X/P Merge software combines data from X- and P-band digital elevation models, SAR backscatter magnitudes, and interferometric correlation magnitudes into a simplified set of output topographical maps of ground-surface elevation and tree height.

  16. Sentinel-3 SAR Altimetry Toolbox

    Benveniste, Jerome; Lucas, Bruno; DInardo, Salvatore

    2015-04-01

    ) and raster images (JPEG, PNG, etc.). Several kinds of computations can be done within BRAT involving combinations of data fields that the user can save for posterior reuse or using the already embedded formulas that include the standard oceanographic altimetry formulas. The Radar Altimeter Tutorial, that contains a strong introduction to altimetry, showing its applications in different fields such as Oceanography, Cryosphere, Geodesy, Hydrology among others. Included are also "use cases", with step-by-step examples, on how to use the toolbox in the different contexts. The Sentinel-3 SAR Altimetry Toolbox shall benefit from the current BRAT version. While developing the Sentinel-3 SAR Altimetry Toolbox we will revamp of the Graphical User Interface and provide, among other enhancements, support for reading the upcoming S3 datasets and specific "use-cases" for SAR altimetry in order to train the users and make them aware of the great potential of SAR altimetry for coastal and inland applications. As for any open source framework, contributions from users having developed their own functions are welcome. The Kick Off is expected to be happen in Q1 2015 and have the 1st version available before the launch of Sentinel-3.

  17. Optical multiple-image encryption based on multiplane phase retrieval and interference

    Chen, Wen; Chen, Xudong

    2011-01-01

    In this paper, we propose a new method for optical multiple-image encryption based on multiplane phase retrieval and interference. An optical encoding system is developed in the Fresnel domain. A phase-only map is iteratively extracted based on a multiplane phase retrieval algorithm, and multiple plaintexts are simultaneously encrypted. Subsequently, the extracted phase-only map is further encrypted into two phase-only masks based on a non-iterative interference algorithm. During image decryption, the advantages and security of the proposed optical cryptosystem are analyzed. Numerical results are presented to demonstrate the validity of the proposed optical multiple-image encryption method

  18. Alaska Synthetic Aperture Radar (SAR) Facility science data processing architecture

    Hilland, Jeffrey E.; Bicknell, Thomas; Miller, Carol L.

    1991-01-01

    The paper describes the architecture of the Alaska SAR Facility (ASF) at Fairbanks, being developed to generate science data products for supporting research in sea ice motion, ice classification, sea-ice-ocean interaction, glacier behavior, ocean waves, and hydrological and geological study areas. Special attention is given to the individual substructures of the ASF: the Receiving Ground Station (RGS), the SAR Processor System, and the Interactive Image Analysis System. The SAR data will be linked to the RGS by the ESA ERS-1 and ERS-2, the Japanese ERS-1, and the Canadian Radarsat.

  19. Mapping and monitoring renewable resources with space SAR

    Ulaby, F. T.; Brisco, B.; Dobson, M. C.; Moezzi, S.

    1983-01-01

    The SEASAT-A SAR and SIR-A imagery was examined to evaluate the quality and type of information that can be extracted and used to monitor renewable resources on Earth. Two tasks were carried out: (1) a land cover classification study which utilized two sets of imagery acquired by the SEASAT-A SAR, one set by SIR-A, and one LANDSAT set (4 bands); and (2) a change detection to examine differences between pairs of SEASAT-A SAR images and relates them to hydrologic and/or agronomic variations in the scene.

  20. Segment-based change detection for polarimetric SAR data

    Skriver, Henning; Nielsen, Allan Aasbjerg; Conradsen, Knut

    2006-01-01

    that is needed compared to single polarisation SAR to provide reliable and robust detection of changes. Polarimetric SAR data will be available from satellites in the near future, e.g. the Japanese ALOS, the Canadian Radarsat-2 and the German TerraSAR-X. An appropriate way of representing multi-look fully...... be split into a number of smaller fields, a building may be removed from or added to some area, hedgerows may be removed/added or other type of vegetated areas may be partly removed or added. In this case, ambiguities may arise when segments have changed shape and extent from one image to another...

  1. InSAR deformation monitoring of high risk landslides

    Singhroy, V.; Li, J.

    2013-05-01

    During the past year there were at least twenty five media reports of landslides and seismic activities some fatal, occurring in various areas in Canada. These high risk geohazards sites requires high resolution monitoring both spatially and temporally for mitigation purposes, since they are near populated areas and energy, transportation and communication corridors. High resolution air photos, lidar and satellite images are quite common in areas where the landslides can be fatal. Radar interferometry (InSAR) techniques using images from several radar satellites are increasingly being used in slope stability assessment. This presentation provides examples of using high-resolution (1-3m) frequent revisits InSAR techniques from RADARSAT 2 and TerraSAR X to monitor several types of high-risk landslides affecting transportation and energy corridors and populated areas. We have analyses over 200 high resolution InSAR images over a three year period on geologically different landslides. The high-resolution InSAR images are effective in characterizing differential motion within these low velocity landslides. The low velocity landslides become high risk during the active wet spring periods. The wet soils are poor coherent targets and corner reflectors provide an effective means of InSAR monitoring the slope activities.

  2. Automated inundation monitoring using TerraSAR-X multitemporal imagery

    Gebhardt, S.; Huth, J.; Wehrmann, T.; Schettler, I.; Künzer, C.; Schmidt, M.; Dech, S.

    2009-04-01

    The Mekong Delta in Vietnam offers natural resources for several million inhabitants. However, a strong population increase, changing climatic conditions and regulatory measures at the upper reaches of the Mekong lead to severe changes in the Delta. Extreme flood events occur more frequently, drinking water availability is increasingly limited, soils show signs of salinization or acidification, species and complete habitats diminish. During the Monsoon season the river regularly overflows its banks in the lower Mekong area, usually with beneficial effects. However, extreme flood events occur more frequently causing extensive damage, on the average once every 6 to 10 years river flood levels exceed the critical beneficial level X-band SAR data are well suited for deriving inundated surface areas. The TerraSAR-X sensor with its different scanning modi allows for the derivation of spatial and temporal high resolved inundation masks. The paper presents an automated procedure for deriving inundated areas from TerraSAR-X Scansar and Stripmap image data. Within the framework of the German-Vietnamese WISDOM project, focussing the Mekong Delta region in Vietnam, images have been acquired covering the flood season from June 2008 to November 2008. Based on these images a time series of the so called watermask showing inundated areas have been derived. The product is required as intermediate to (i) calibrate 2d inundation model scenarios, (ii) estimate the extent of affected areas, and (iii) analyze the scope of prior crisis. The image processing approach is based on the assumption that water surfaces are forward scattering the radar signal resulting in low backscatter signals to the sensor. It uses multiple grey level thresholds and image morphological operations. The approach is robust in terms of automation, accuracy, robustness, and processing time. The resulting watermasks show the seasonal flooding pattern with inundations starting in July, having their peak at the end

  3. Automatic Detection and Positioning of Ground Control Points Using TerraSAR-X Multiaspect Acquisitions

    Montazeri, Sina; Gisinger, Christoph; Eineder, Michael; Zhu, Xiao xiang

    2018-05-01

    Geodetic stereo Synthetic Aperture Radar (SAR) is capable of absolute three-dimensional localization of natural Persistent Scatterer (PS)s which allows for Ground Control Point (GCP) generation using only SAR data. The prerequisite for the method to achieve high precision results is the correct detection of common scatterers in SAR images acquired from different viewing geometries. In this contribution, we describe three strategies for automatic detection of identical targets in SAR images of urban areas taken from different orbit tracks. Moreover, a complete work-flow for automatic generation of large number of GCPs using SAR data is presented and its applicability is shown by exploiting TerraSAR-X (TS-X) high resolution spotlight images over the city of Oulu, Finland and a test site in Berlin, Germany.

  4. Simultaneous reconstruction of multiple depth images without off-focus points in integral imaging using a graphics processing unit.

    Yi, Faliu; Lee, Jieun; Moon, Inkyu

    2014-05-01

    The reconstruction of multiple depth images with a ray back-propagation algorithm in three-dimensional (3D) computational integral imaging is computationally burdensome. Further, a reconstructed depth image consists of a focus and an off-focus area. Focus areas are 3D points on the surface of an object that are located at the reconstructed depth, while off-focus areas include 3D points in free-space that do not belong to any object surface in 3D space. Generally, without being removed, the presence of an off-focus area would adversely affect the high-level analysis of a 3D object, including its classification, recognition, and tracking. Here, we use a graphics processing unit (GPU) that supports parallel processing with multiple processors to simultaneously reconstruct multiple depth images using a lookup table containing the shifted values along the x and y directions for each elemental image in a given depth range. Moreover, each 3D point on a depth image can be measured by analyzing its statistical variance with its corresponding samples, which are captured by the two-dimensional (2D) elemental images. These statistical variances can be used to classify depth image pixels as either focus or off-focus points. At this stage, the measurement of focus and off-focus points in multiple depth images is also implemented in parallel on a GPU. Our proposed method is conducted based on the assumption that there is no occlusion of the 3D object during the capture stage of the integral imaging process. Experimental results have demonstrated that this method is capable of removing off-focus points in the reconstructed depth image. The results also showed that using a GPU to remove the off-focus points could greatly improve the overall computational speed compared with using a CPU.

  5. Bats and SARS

    Bats are a natural reservoir for emerging viruses, among them henipaviruses and rabies virus variants. Dr. Nina Marano, Chief, Geographic Medicine and Health Promotion Branch, Division of Global Migration and Quarantine, CDC, explains connection between horseshoe bats and SARS coronavirus transmission.

  6. Bats and SARS

    2006-11-08

    Bats are a natural reservoir for emerging viruses, among them henipaviruses and rabies virus variants. Dr. Nina Marano, Chief, Geographic Medicine and Health Promotion Branch, Division of Global Migration and Quarantine, CDC, explains connection between horseshoe bats and SARS coronavirus transmission.  Created: 11/8/2006 by Emerging Infectious Diseases.   Date Released: 11/17/2006.

  7. Data Analytics for SAR

    Murphy, David Patrick [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Calef, Matthew Thomas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-10-02

    We assess the ability of variants of anomalous change detection (ACD) to identify human activity associated with large outdoor music festivals as they are seen from synthetic aperture radar (SAR) imagery collected by the Sentinel-1 satellite constellation. We found that, with appropriate feature vectors, ACD using random-forest machine learning was most effective at identifying changes associated with the human activity.

  8. Imaging Finding of Multiple Endocrine Neoplasia Type 1: Case Report

    Yum, Tae Jun; Cho, Hee Woo

    2012-01-01

    Multiple endocrine neoplasia type 1 (MEN1) is an autosomal dominant inherited syndrome with characteristic clinical and radiological manifestations. Many reports on MEN1 have been published; however, no cases of radiologically diagnosed MEN1 have been reported. Therefore, we report on a radiologically diagnosed case of MEN1 with clinical symptoms of gastroduodenal ulcer.

  9. MR-based conductivity imaging using multiple receiver coils.

    Lee, Joonsung; Shin, Jaewook; Kim, Dong-Hyun

    2016-08-01

    To propose a signal combination method for MR-based tissue conductivity mapping using a standard clinical scanner with multiple receiver coils. The theory of the proposed method is presented with two practical approaches, a coil-specific approach and a subject-specific approach. Conductivity maps were reconstructed using the transceive phase of the combined signal. The sensitivities of the coefficients used for signal combination were analyzed and the method was compared with other signal combination methods. For validation, multiple receiver brain coils and multiple receiver breast coils were used in phantom, in vivo brain, and in vivo breast studies. The variation among the conductivity estimates was conductivity estimates. MR-based tissue conductivity mapping is feasible when using a standard clinical MR scanner with multiple receiver coils. The proposed method reduces systematic errors in phase-based conductivity mapping that can occur due to the inhomogeneous magnitude of the combined receive profile. Magn Reson Med 76:530-539, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  10. Multiple interpretations of a pair of images of a surface

    Longuet-Higgins, H. C.

    1988-07-01

    It is known that, if two optical images of a visually textured surface, projected from finitely separated viewpoints, allow more than one three-dimensional interpretation, then the surface must be part of a quadric passing through the two viewpoints. It is here shown that this quadric is either a plane or a ruled surface of a type first considered by Maybank (1985) in a study of ambiguous optic flow fields. In the latter case, three is the maximum number of distinct interpretations that the two images can sustain.

  11. Positron annihilation imaging device using multiple offset rings of detectors

    Thompson, C.J.

    1982-01-01

    A means is provided for recording more than one tomographic image simultaneously through different cross-sections of a patient, using positron emission tomography. Separate rings of detectors are used to construct every odd-numbered slice, and coincident events that occur between adjacent rings of detectors provide a center or even-numbered slice. Detector rings are offset with respect to one another by half the angular separation of the detectors, allowing an image to be reconstructed from the central slice without the necessity of physically rotating the detector array while accumulating data

  12. Designing Websites for Displaying Large Data Sets and Images on Multiple Platforms

    Anderson, A.; Wolf, V. G.; Garron, J.; Kirschner, M.

    2012-12-01

    The desire to build websites to analyze and display ever increasing amounts of scientific data and images pushes for web site designs which utilize large displays, and to use the display area as efficiently as possible. Yet, scientists and users of their data are increasingly wishing to access these websites in the field and on mobile devices. This results in the need to develop websites that can support a wide range of devices and screen sizes, and to optimally use whatever display area is available. Historically, designers have addressed this issue by building two websites; one for mobile devices, and one for desktop environments, resulting in increased cost, duplicity of work, and longer development times. Recent advancements in web design technology and techniques have evolved which allow for the development of a single website that dynamically adjusts to the type of device being used to browse the website (smartphone, tablet, desktop). In addition they provide the opportunity to truly optimize whatever display area is available. HTML5 and CSS3 give web designers media query statements which allow design style sheets to be aware of the size of the display being used, and to format web content differently based upon the queried response. Web elements can be rendered in a different size, position, or even removed from the display entirely, based upon the size of the display area. Using HTML5/CSS3 media queries in this manner is referred to as "Responsive Web Design" (RWD). RWD in combination with technologies such as LESS and Twitter Bootstrap allow the web designer to build web sites which not only dynamically respond to the browser display size being used, but to do so in very controlled and intelligent ways, ensuring that good layout and graphic design principles are followed while doing so. At the University of Alaska Fairbanks, the Alaska Satellite Facility SAR Data Center (ASF) recently redesigned their popular Vertex application and converted it from a

  13. Full wavefield migration: Seismic imaging using multiple scattering effects

    Davydenko, M.

    2016-01-01

    Seismic imaging aims at revealing the structural information of the subsurface using the reflected wavefields captured by sensors usually located at the surface. Wave propagation is a complex phenomenon and the measured data contain a set of backscattered events including not only primary

  14. Accounting for free-surface multiples in Marchenko imaging

    Singh, S.; Snieder, R; van der Neut, J.R.; Thorbecke, J.W.; Slob, E.C.; Wapenaar, C.P.A.

    2017-01-01

    Imagine placing a receiver at any location in the earth and recording the response at that location to sources on the surface. In such a world, we could place receivers around our reservoir to better image the reservoir and understand its properties. Realistically, this is not a feasible approach

  15. Light chain deposition disease in multiple myeloma: MR imaging features correlated with histopathological findings

    Baur, A.; Staebler, A.; Reiser, M.; Lamerz, R.; Bartl, R.

    1998-01-01

    The clinical, histopathological, and imaging findings on MRI of a 56-year-old woman with light chain deposition disease occurring in multiple myeloma are presented. Light chain deposition disease is a variant of multiple myeloma with distinct clinical and histological characteristics. MRI of this patient also revealed an infiltration pattern in the bone marrow distinct from that of typical multiple myeloma. Multiple small foci of low signal intensity were present on T1- and T2-weighted spin echo and STIR images, corresponding to conglomerates of light chains in bone marrow biopsy. Contrast-enhanced T1-weighted spin echo images show diffuse enhancement of 51% over all vertebral bodies, with a minor enhancement of the focal conglomerates of light chains. Light chain deposition disease in multiple myeloma should be added to the list of those few entities with normal radiographs and discrete low-signal marrow lesions on T1- and T2-weighted spin echo pulse sequences. (orig.)

  16. Resolution Enhancement Algorithm for Spaceborn SAR Based on Hanning Function Weighted Sidelobe Suppression

    Li, C.; Zhou, X.; Tang, D.; Zhu, Z.

    2018-04-01

    Resolution and sidelobe are mutual restrict for SAR image. Usually sidelobe suppression is based on resolution reduction. This paper provide a method for resolution enchancement using sidelobe opposition speciality of hanning window and SAR image. The method can keep high resolution on the condition of sidelobe suppression. Compare to traditional method, this method can enchance 50 % resolution when sidelobe is -30dB.

  17. SAR Imagery Segmentation by Statistical Region Growing and Hierarchical Merging

    Ushizima, Daniela Mayumi; Carvalho, E.A.; Medeiros, F.N.S.; Martins, C.I.O.; Marques, R.C.P.; Oliveira, I.N.S.

    2010-05-22

    This paper presents an approach to accomplish synthetic aperture radar (SAR) image segmentation, which are corrupted by speckle noise. Some ordinary segmentation techniques may require speckle filtering previously. Our approach performs radar image segmentation using the original noisy pixels as input data, eliminating preprocessing steps, an advantage over most of the current methods. The algorithm comprises a statistical region growing procedure combined with hierarchical region merging to extract regions of interest from SAR images. The region growing step over-segments the input image to enable region aggregation by employing a combination of the Kolmogorov-Smirnov (KS) test with a hierarchical stepwise optimization (HSWO) algorithm for the process coordination. We have tested and assessed the proposed technique on artificially speckled image and real SAR data containing different types of targets.

  18. Imaging a Large Sample with Selective Plane Illumination Microscopy Based on Multiple Fluorescent Microsphere Tracking

    Ryu, Inkeon; Kim, Daekeun

    2018-04-01

    A typical selective plane illumination microscopy (SPIM) image size is basically limited by the field of view, which is a characteristic of the objective lens. If an image larger than the imaging area of the sample is to be obtained, image stitching, which combines step-scanned images into a single panoramic image, is required. However, accurately registering the step-scanned images is very difficult because the SPIM system uses a customized sample mount where uncertainties for the translational and the rotational motions exist. In this paper, an image registration technique based on multiple fluorescent microsphere tracking is proposed in the view of quantifying the constellations and measuring the distances between at least two fluorescent microspheres embedded in the sample. Image stitching results are demonstrated for optically cleared large tissue with various staining methods. Compensation for the effect of the sample rotation that occurs during the translational motion in the sample mount is also discussed.

  19. Diffusion tensor imaging using multiple coils for mouse brain connectomics.

    Nouls, John C; Badea, Alexandra; Anderson, Robert B J; Cofer, Gary P; Allan Johnson, G

    2018-04-19

    The correlation between brain connectivity and psychiatric or neurological diseases has intensified efforts to develop brain connectivity mapping techniques on mouse models of human disease. The neural architecture of mouse brain specimens can be shown non-destructively and three-dimensionally by diffusion tensor imaging, which enables tractography, the establishment of a connectivity matrix and connectomics. However, experiments on cohorts of animals can be prohibitively long. To improve throughput in a 7-T preclinical scanner, we present a novel two-coil system in which each coil is shielded, placed off-isocenter along the axis of the magnet and connected to a receiver circuit of the scanner. Preservation of the quality factor of each coil is essential to signal-to-noise ratio (SNR) performance and throughput, because mouse brain specimen imaging at 7 T takes place in the coil-dominated noise regime. In that regime, we show a shielding configuration causing no SNR degradation in the two-coil system. To acquire data from several coils simultaneously, the coils are placed in the magnet bore, around the isocenter, in which gradient field distortions can bias diffusion tensor imaging metrics, affect tractography and contaminate measurements of the connectivity matrix. We quantified the experimental alterations in fractional anisotropy and eigenvector direction occurring in each coil. We showed that, when the coils were placed 12 mm away from the isocenter, measurements of the brain connectivity matrix appeared to be minimally altered by gradient field distortions. Simultaneous measurements on two mouse brain specimens demonstrated a full doubling of the diffusion tensor imaging throughput in practice. Each coil produced images devoid of shading or artifact. To further improve the throughput of mouse brain connectomics, we suggested a future expansion of the system to four coils. To better understand acceptable trade-offs between imaging throughput and connectivity

  20. Correction of over and under exposure images using multiple lighting system

    Im, Jonghoon; Fujii, Hiromitsu; Yamashita, Atsushi; Asama, Hajime

    2015-01-01

    When images are acquired in bright condition, it can cause a loss of highlight details (over exposure) in bright area and a loss of shadow details (under exposure) in dark area. Over and under exposure causes a big problem when people investigate dangerous place like Fukushima nuclear power plant through the camera attached remote control robot. In this paper, we propose a method to correct the over and under exposure image to solve the problem. The image processing consists of four steps. Firstly, multiple images are acquired by alternately turning on and off each illumination which set in different positions. Then the image obtained first is defined as input image 1, the image obtained second is defined as input image 2 and the image obtained N-th is defined as input image N. Secondly, luminance of the images is corrected. Thirdly, over and under exposure regions in the image are extracted from the input image 1. Finally, the over and under exposure regions in the input image 1 are compensated by other images. The results show that the over and under exposure regions in the input image are recovered by our proposed method. (author)

  1. Spinal focal lesion detection in multiple myeloma using multimodal image features

    Fränzle, Andrea; Hillengass, Jens; Bendl, Rolf

    2015-03-01

    Multiple myeloma is a tumor disease in the bone marrow that affects the skeleton systemically, i.e. multiple lesions can occur in different sites in the skeleton. To quantify overall tumor mass for determining degree of disease and for analysis of therapy response, volumetry of all lesions is needed. Since the large amount of lesions in one patient impedes manual segmentation of all lesions, quantification of overall tumor volume is not possible until now. Therefore development of automatic lesion detection and segmentation methods is necessary. Since focal tumors in multiple myeloma show different characteristics in different modalities (changes in bone structure in CT images, hypointensity in T1 weighted MR images and hyperintensity in T2 weighted MR images), multimodal image analysis is necessary for the detection of focal tumors. In this paper a pattern recognition approach is presented that identifies focal lesions in lumbar vertebrae based on features from T1 and T2 weighted MR images. Image voxels within bone are classified using random forests based on plain intensities and intensity value derived features (maximum, minimum, mean, median) in a 5 x 5 neighborhood around a voxel from both T1 and T2 weighted MR images. A test data sample of lesions in 8 lumbar vertebrae from 4 multiple myeloma patients can be classified at an accuracy of 95% (using a leave-one-patient-out test). The approach provides a reasonable delineation of the example lesions. This is an important step towards automatic tumor volume quantification in multiple myeloma.

  2. Evaluation of Polarimetric SAR Decomposition for Classifying Wetland Vegetation Types

    Sang-Hoon Hong

    2015-07-01

    Full Text Available The Florida Everglades is the largest subtropical wetland system in the United States and, as with subtropical and tropical wetlands elsewhere, has been threatened by severe environmental stresses. It is very important to monitor such wetlands to inform management on the status of these fragile ecosystems. This study aims to examine the applicability of TerraSAR-X quadruple polarimetric (quad-pol synthetic aperture radar (PolSAR data for classifying wetland vegetation in the Everglades. We processed quad-pol data using the Hong & Wdowinski four-component decomposition, which accounts for double bounce scattering in the cross-polarization signal. The calculated decomposition images consist of four scattering mechanisms (single, co- and cross-pol double, and volume scattering. We applied an object-oriented image analysis approach to classify vegetation types with the decomposition results. We also used a high-resolution multispectral optical RapidEye image to compare statistics and classification results with Synthetic Aperture Radar (SAR observations. The calculated classification accuracy was higher than 85%, suggesting that the TerraSAR-X quad-pol SAR signal had a high potential for distinguishing different vegetation types. Scattering components from SAR acquisition were particularly advantageous for classifying mangroves along tidal channels. We conclude that the typical scattering behaviors from model-based decomposition are useful for discriminating among different wetland vegetation types.

  3. Playback system designed for X-Band SAR

    Yuquan, Liu; Changyong, Dou

    2014-01-01

    SAR(Synthetic Aperture Radar) has extensive application because it is daylight and weather independent. In particular, X-Band SAR strip map, designed by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, provides high ground resolution images, at the same time it has a large spatial coverage and a short acquisition time, so it is promising in multi-applications. When sudden disaster comes, the emergency situation acquires radar signal data and image as soon as possible, in order to take action to reduce loss and save lives in the first time. This paper summarizes a type of X-Band SAR playback processing system designed for disaster response and scientific needs. It describes SAR data workflow includes the payload data transmission and reception process. Playback processing system completes signal analysis on the original data, providing SAR level 0 products and quick image. Gigabit network promises radar signal transmission efficiency from recorder to calculation unit. Multi-thread parallel computing and ping pong operation can ensure computation speed. Through gigabit network, multi-thread parallel computing and ping pong operation, high speed data transmission and processing meet the SAR radar data playback real time requirement

  4. Playback system designed for X-Band SAR

    Yuquan, Liu; Changyong, Dou

    2014-03-01

    SAR(Synthetic Aperture Radar) has extensive application because it is daylight and weather independent. In particular, X-Band SAR strip map, designed by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, provides high ground resolution images, at the same time it has a large spatial coverage and a short acquisition time, so it is promising in multi-applications. When sudden disaster comes, the emergency situation acquires radar signal data and image as soon as possible, in order to take action to reduce loss and save lives in the first time. This paper summarizes a type of X-Band SAR playback processing system designed for disaster response and scientific needs. It describes SAR data workflow includes the payload data transmission and reception process. Playback processing system completes signal analysis on the original data, providing SAR level 0 products and quick image. Gigabit network promises radar signal transmission efficiency from recorder to calculation unit. Multi-thread parallel computing and ping pong operation can ensure computation speed. Through gigabit network, multi-thread parallel computing and ping pong operation, high speed data transmission and processing meet the SAR radar data playback real time requirement.

  5. Accommodating multiple illumination sources in an imaging colorimetry environment

    Tobin, Kenneth W., Jr.; Goddard, James S., Jr.; Hunt, Martin A.; Hylton, Kathy W.; Karnowski, Thomas P.; Simpson, Marc L.; Richards, Roger K.; Treece, Dale A.

    2000-03-01

    Researchers at the Oak Ridge National Laboratory have been developing a method for measuring color quality in textile products using a tri-stimulus color camera system. Initial results of the Imaging Tristimulus Colorimeter (ITC) were reported during 1999. These results showed that the projection onto convex sets (POCS) approach to color estimation could be applied to complex printed patterns on textile products with high accuracy and repeatability. Image-based color sensors used for on-line measurement are not colorimetric by nature and require a non-linear transformation of the component colors based on the spectral properties of the incident illumination, imaging sensor, and the actual textile color. Our earlier work reports these results for a broad-band, smoothly varying D65 standard illuminant. To move the measurement to the on-line environment with continuously manufactured textile webs, the illumination source becomes problematic. The spectral content of these light sources varies substantially from the D65 standard illuminant and can greatly impact the measurement performance of the POCS system. Although absolute color measurements are difficult to make under different illumination, referential measurements to monitor color drift provide a useful indication of product quality. Modifications to the ITC system have been implemented to enable the study of different light sources. These results and the subsequent analysis of relative color measurements will be reported for textile products.

  6. 3D Power Line Extraction from Multiple Aerial Images

    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.

  7. Influences of multiple memory systems on auditory mental image acuity.

    Navarro Cebrian, Ana; Janata, Petr

    2010-05-01

    The influence of different memory systems and associated attentional processes on the acuity of auditory images, formed for the purpose of making intonation judgments, was examined across three experiments using three different task types (cued-attention, imagery, and two-tone discrimination). In experiment 1 the influence of implicit long-term memory for musical scale structure was manipulated by varying the scale degree (leading tone versus tonic) of the probe note about which a judgment had to be made. In experiments 2 and 3 the ability of short-term absolute pitch knowledge to develop was manipulated by presenting blocks of trials in the same key or in seven different keys. The acuity of auditory images depended on all of these manipulations. Within individual listeners, thresholds in the two-tone discrimination and cued-attention conditions were closely related. In many listeners, cued-attention thresholds were similar to thresholds in the imagery condition, and depended on the amount of training individual listeners had in playing a musical instrument. The results indicate that mental images formed at a sensory/cognitive interface for the purpose of making perceptual decisions are highly malleable.

  8. Conventional MRI and magnetisation transfer imaging of tumour-like multiple sclerosis in a child

    Metafratzi, Z.; Argyropoulou, M.I.; Efremidis, S.C.; Tzoufi, M.; Papadopoulou, Z.

    2002-01-01

    Tumefactive multiple sclerosis is a rare entity in children. Differential diagnosis includes other mass lesions such as neoplasm and abscess. A case of tumefactive multiple sclerosis in a child is presented. The open-ring pattern of enhancement on conventional MRI and magnetisation transfer imaging was important for the initial diagnosis and the evaluation of the course of the disease. (orig.)

  9. New Hybrid Variational Recovery Model for Blurred Images with Multiplicative Noise

    Dong, Yiqiu; Zeng, Tieyong

    2013-01-01

    A new hybrid variational model for recovering blurred images in the presence of multiplicative noise is proposed. Inspired by previous work on multiplicative noise removal, an I-divergence technique is used to build a strictly convex model under a condition that ensures the uniqueness...

  10. Robust image registration for multiple exposure high dynamic range image synthesis

    Yao, Susu

    2011-03-01

    Image registration is an important preprocessing technique in high dynamic range (HDR) image synthesis. This paper proposed a robust image registration method for aligning a group of low dynamic range images (LDR) that are captured with different exposure times. Illumination change and photometric distortion between two images would result in inaccurate registration. We propose to transform intensity image data into phase congruency to eliminate the effect of the changes in image brightness and use phase cross correlation in the Fourier transform domain to perform image registration. Considering the presence of non-overlapped regions due to photometric distortion, evolutionary programming is applied to search for the accurate translation parameters so that the accuracy of registration is able to be achieved at a hundredth of a pixel level. The proposed algorithm works well for under and over-exposed image registration. It has been applied to align LDR images for synthesizing high quality HDR images..

  11. High Dynamic Velocity Range Particle Image Velocimetry Using Multiple Pulse Separation Imaging

    Tadhg S. O’Donovan

    2010-12-01

    Full Text Available The dynamic velocity range of particle image velocimetry (PIV is determined by the maximum and minimum resolvable particle displacement. Various techniques have extended the dynamic range, however flows with a wide velocity range (e.g., impinging jets still challenge PIV algorithms. A new technique is presented to increase the dynamic velocity range by over an order of magnitude. The multiple pulse separation (MPS technique (i records series of double-frame exposures with different pulse separations, (ii processes the fields using conventional multi-grid algorithms, and (iii yields a composite velocity field with a locally optimized pulse separation. A robust criterion determines the local optimum pulse separation, accounting for correlation strength and measurement uncertainty. Validation experiments are performed in an impinging jet flow, using laser-Doppler velocimetry as reference measurement. The precision of mean flow and turbulence quantities is significantly improved compared to conventional PIV, due to the increase in dynamic range. In a wide range of applications, MPS PIV is a robust approach to increase the dynamic velocity range without restricting the vector evaluation methods.

  12. High dynamic velocity range particle image velocimetry using multiple pulse separation imaging.

    Persoons, Tim; O'Donovan, Tadhg S

    2011-01-01

    The dynamic velocity range of particle image velocimetry (PIV) is determined by the maximum and minimum resolvable particle displacement. Various techniques have extended the dynamic range, however flows with a wide velocity range (e.g., impinging jets) still challenge PIV algorithms. A new technique is presented to increase the dynamic velocity range by over an order of magnitude. The multiple pulse separation (MPS) technique (i) records series of double-frame exposures with different pulse separations, (ii) processes the fields using conventional multi-grid algorithms, and (iii) yields a composite velocity field with a locally optimized pulse separation. A robust criterion determines the local optimum pulse separation, accounting for correlation strength and measurement uncertainty. Validation experiments are performed in an impinging jet flow, using laser-Doppler velocimetry as reference measurement. The precision of mean flow and turbulence quantities is significantly improved compared to conventional PIV, due to the increase in dynamic range. In a wide range of applications, MPS PIV is a robust approach to increase the dynamic velocity range without restricting the vector evaluation methods.

  13. Clinical diagnostic criteria of multiple sclerosis: the role of magnetic resonance imaging

    Belair, M.; Girard, M.

    2004-01-01

    The objective of this article is to summarize the diagnostic criteria recommended by the International Panel on the Diagnosis of Multiple Sclerosis in 2001. The recommendations of another working group, the Consortium of Multiple Sclerosis Centers Consensus Meeting, which met in Vancouver in 2001, concerning the diagnosis and follow-up of patients with multiple sclerosis are also presented in an effort to standardize the protocols for magnetic resonance imaging of these patients. (author)

  14. Enriching Student Concept Images: Teaching and Learning Fractions through a Multiple-Embodiment Approach

    Zhang, Xiaofen; Clements, M. A.; Ellerton, Nerida F.

    2015-01-01

    This study investigated how fifth-grade children's concept images of the unit fractions represented by the symbols 1/2, 1/3/ and 1/4 changed as a result of their participation in an instructional intervention based on multiple embodiments of fraction concepts. The participants' concept images were examined through pre- and post-teaching written…

  15. Polarimetric SAR interferometry-based decomposition modelling for reliable scattering retrieval

    Agrawal, Neeraj; Kumar, Shashi; Tolpekin, Valentyn

    2016-05-01

    Fully Polarimetric SAR (PolSAR) data is used for scattering information retrieval from single SAR resolution cell. Single SAR resolution cell may contain contribution from more than one scattering objects. Hence, single or dual polarized data does not provide all the possible scattering information. So, to overcome this problem fully Polarimetric data is used. It was observed in previous study that fully Polarimetric data of different dates provide different scattering values for same object and coefficient of determination obtained from linear regression between volume scattering and aboveground biomass (AGB) shows different values for the SAR dataset of different dates. Scattering values are important input elements for modelling of forest aboveground biomass. In this research work an approach is proposed to get reliable scattering from interferometric pair of fully Polarimetric RADARSAT-2 data. The field survey for data collection was carried out for Barkot forest during November 10th to December 5th, 2014. Stratified random sampling was used to collect field data for circumference at breast height (CBH) and tree height measurement. Field-measured AGB was compared with the volume scattering elements obtained from decomposition modelling of individual PolSAR images and PolInSAR coherency matrix. Yamaguchi 4-component decomposition was implemented to retrieve scattering elements from SAR data. PolInSAR based decomposition was the great challenge in this work and it was implemented with certain assumptions to create Hermitian coherency matrix with co-registered polarimetric interferometric pair of SAR data. Regression analysis between field-measured AGB and volume scattering element obtained from PolInSAR data showed highest (0.589) coefficient of determination. The same regression with volume scattering elements of individual SAR images showed 0.49 and 0.50 coefficients of determination for master and slave images respectively. This study recommends use of

  16. A NEW SAR CLASSIFICATION SCHEME FOR SEDIMENTS ON INTERTIDAL FLATS BASED ON MULTI-FREQUENCY POLARIMETRIC SAR IMAGERY

    W. Wang

    2017-11-01

    Full Text Available We present a new classification scheme for muddy and sandy sediments on exposed intertidal flats, which is based on synthetic aperture radar (SAR data, and use ALOS-2 (L-band, Radarsat-2 (C-band and TerraSAR-X (X-band fully polarimetric SAR imagery to demonstrate its effectiveness. Four test sites on the German North Sea coast were chosen, which represent typical surface compositions of different sediments, vegetation, and habitats, and of which a large amount of SAR is used for our analyses. Both Freeman-Durden and Cloude-Pottier polarimetric decomposition are utilized, and an additional descriptor called Double-Bounce Eigenvalue Relative Difference (DERD is introduced into the feature sets instead of the original polarimetric intensity channels. The classification is conducted following Random Forest theory, and the results are verified using ground truth data from field campaigns and an existing classification based on optical imagery. In addition, the use of Kennaugh elements for classification purposes is demonstrated using both fully and dual-polarization multi-frequency and multi-temporal SAR data. Our results show that the proposed classification scheme can be applied for the discrimination of muddy and sandy sediments using L-, C-, and X-band SAR images, while SAR imagery acquired at short wavelengths (C- and X-band can also be used to detect more detailed features such as bivalve beds on intertidal flats.

  17. Effect of multiple circular holes Fraunhofer diffraction for the infrared optical imaging

    Lu, Chunlian; Lv, He; Cao, Yang; Cai, Zhisong; Tan, Xiaojun

    2014-11-01

    With the development of infrared optics, infrared optical imaging systems play an increasingly important role in modern optical imaging systems. Infrared optical imaging is used in industry, agriculture, medical, military and transportation. But in terms of infrared optical imaging systems which are exposed for a long time, some contaminations will affect the infrared optical imaging. When the contamination contaminate on the lens surface of the optical system, it would affect diffraction. The lens can be seen as complementary multiple circular holes screen happen Fraunhofer diffraction. According to Babinet principle, you can get the diffraction of the imaging system. Therefore, by studying the multiple circular holes Fraunhofer diffraction, conclusions can be drawn about the effect of infrared imaging. This paper mainly studies the effect of multiple circular holes Fraunhofer diffraction for the optical imaging. Firstly, we introduce the theory of Fraunhofer diffraction and Point Spread Function. Point Spread Function is a basic tool to evaluate the image quality of the optical system. Fraunhofer diffraction will affect Point Spread Function. Then, the results of multiple circular holes Fraunhofer diffraction are given for different hole size and hole spacing. We choose the hole size from 0.1mm to 1mm and hole spacing from 0.3mm to 0.8mm. The infrared wavebands of optical imaging are chosen from 1μm to 5μm. We use the MATLAB to simulate light intensity distribution of multiple circular holes Fraunhofer diffraction. Finally, three-dimensional diffraction maps of light intensity are given to contrast.

  18. Radionuclide bone scintigraphy in early detection of avascular osteonecrosis occurred in recovered SARS patients after hormone therapy

    Wang Qian; Huang Lili; Qin Shuling; Wang Yu; Nie Yuxin; Liang Tiejun; Zhang Caiqun; Zhao Yamei

    2005-01-01

    Objective: To analyze the characteristics of bone scintigraphy in patients who recovered from the severe acute respiratory syndrome (SARS), and to evaluate the clinical value of bone scintigraphy in the early diagnosis of avascular osteonecrosis (AVN) after hormone therapy. Methods: Bone scintigraphy was performed in 66 SARS patients. Among them 54 underwent MRI in bilateral hips and knees. Both images were compared and followed up clinically. Results: Abnormal scintigraphy was found in 30 (45.5%) of the 66 recovered SARS patients. Total 82 foci were found in hip, knee, ankle, elbow, shoulder, wrist and the middle of the tibia. Hip and knee joints were the most involved sites. 25 patients with 71 lesions were symptomatic, whereas 11 in 5 patients were asymptomatic, lesions in 8 patients were multifocal. The lesions found in scintigraphy and MRI were concordant in 92.6% of the joints. But more lesions could be detected by bone scintigraphy. Conclusions: SARS patients have a high occurrence of AVN, usually involved in multiple sites. Bone scintigraphy should be the first choice method used for early detection of AVN. (authors)

  19. Magnetic resonance imaging in monitoring of treatment of multiple sclerosis

    Bekiesinska-Figatowska, M.; Walecki, J.; Stelmasiak, Z.

    1996-01-01

    The purpose of the study was to establish the value of MR in monitoring of treatment of multiple sclerosis with new drug 2-CDA and placebo. 83 patients (51 women, 32 men) were examined - 81 of them twice, 66 - three times: before and after 6 and 12 courses of treatment. Toshiba MRT50A machine was used. After the first 6 courses of treatment the number of new plaques was twice as big in placebo group than in 2-CDA group. After 12 courses it turned out that a certain inhibitory influence of 2-CDA on new plaques' appearance was more evident after 15 than 3 months after the end of its administration. This may indicate the delayed action of 2-CDA but requires further investigation. (author)

  20. Autosomal recessive osteopetrosis with a unique imaging finding: multiple encephaloceles

    Saglam, Dilek; Bilgici, Meltem Ceyhan; Bekci, Tuemay; Albayrak, Canan; Albayrak, Davut

    2017-01-01

    Osteopetrosis is a hereditary form of sclerosing bone dysplasia with various radiological and clinical presentations. The autosomal recessive type, also known as malignant osteopetrosis, is the most severe type, with the early onset of manifestations. A 5-month-old infant was admitted to our hospital with recurrent respiratory tract infections. Chest X-ray and skeletal survey revealed the classic findings of osteopetrosis, including diffuse osteosclerosis and bone within a bone appearance. At follow-up, the patient presented with, thickened calvarium, multiple prominent encephaloceles, and dural calcifications leading to the intracranial clinical manifestations with bilateral hearing and sight loss. Autosomal recessive osteopetrosis is one of the causes of encephaloceles and this finding may become dramatic if untreated. (orig.)