Multilayered Clouds Identification and Retrieval for CERES Using MODIS

Science.gov (United States)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Yi, Yuhong; Huang, Jainping; Lin, Bin; Fan, Alice; Gibson, Sharon; Chang, Fu-Lung

2006-01-01

Traditionally, analyses of satellite data have been limited to interpreting the radiances in terms of single layer clouds. Generally, this results in significant errors in the retrieved properties for multilayered cloud systems. Two techniques for detecting overlapped clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. The first technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other method uses microwave (MWR) data. The use of BTD, the 11-12 micrometer brightness temperature difference, in conjunction with tau, the retrieved visible optical depth, was suggested by Kawamoto et al. (2001) and used by Pavlonis et al. (2004) as a means to detect multilayered clouds. Combining visible (VIS; 0.65 micrometer) and infrared (IR) retrievals of cloud properties with microwave (MW) retrievals of cloud water temperature Tw and liquid water path LWP retrieved from satellite microwave imagers appears to be a fruitful approach for detecting and retrieving overlapped clouds (Lin et al., 1998, Ho et al., 2003, Huang et al., 2005). The BTD method is limited to optically thin cirrus over low clouds, while the MWR method is limited to ocean areas only. With the availability of VIS and IR data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and MW data from the Advanced Microwave Scanning Radiometer EOS (AMSR-E), both on Aqua, it is now possible to examine both approaches simultaneously. This paper explores the use of the BTD method as applied to MODIS and AMSR-E data taken from the Aqua satellite over non-polar ocean surfaces.

High-dynamic-range imaging for cloud segmentation

Science.gov (United States)

Dev, Soumyabrata; Savoy, Florian M.; Lee, Yee Hui; Winkler, Stefan

2018-04-01

Sky-cloud images obtained from ground-based sky cameras are usually captured using a fisheye lens with a wide field of view. However, the sky exhibits a large dynamic range in terms of luminance, more than a conventional camera can capture. It is thus difficult to capture the details of an entire scene with a regular camera in a single shot. In most cases, the circumsolar region is overexposed, and the regions near the horizon are underexposed. This renders cloud segmentation for such images difficult. In this paper, we propose HDRCloudSeg - an effective method for cloud segmentation using high-dynamic-range (HDR) imaging based on multi-exposure fusion. We describe the HDR image generation process and release a new database to the community for benchmarking. Our proposed approach is the first using HDR radiance maps for cloud segmentation and achieves very good results.

New Satellite Estimates of Mixed-Phase Cloud Properties: A Synergistic Approach for Application to Global Satellite Imager Data

Science.gov (United States)

Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.

2016-12-01

Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and

Three-dimensional cloud characterization from paired whole-sky imaging cameras

International Nuclear Information System (INIS)

Allmen, M.; Kegelmeyer, W.P. Jr.

1994-01-01

Three-dimensional (3-D) cloud characterization permits the derivation of important cloud geometry properties such as fractional cloudiness, mean cloud and clear length, aspect ratio, and the morphology of cloud cover. These properties are needed as input to the hierarchical diagnosis (HD) and instantaneous radiative transfer (IRF) models, to validate sub-models for cloud occurrence and formation, and to Central Site radiative flux calculations. A full 3-D characterization will eventually require the integration of disparate Cloud and Radiation Testbed (CART) data sources: whole-sky imagers (WSIs), radar, satellites, ceilometers, volume-imaging lidar, and other sensors. In this paper, we demonstrate how an initial 3-D cloud property, cloud base height, can be determined from fusing paired times series of images from two whole-sky imagers

Physically-Retrieving Cloud and Thermodynamic Parameters from Ultraspectral IR Measurements

Science.gov (United States)

Zhou, Daniel K.; Smith, William L., Sr.; Liu, Xu; Larar, Allen M.; Mango, Stephen A.; Huang, Hung-Lung

2007-01-01

A physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error < 1 km). NPOESS Airborne Sounder Testbed Interferometer (NAST-I) retrievals from the Atlantic-THORPEX Regional Campaign are compared with coincident observations obtained from dropsondes and the nadir-pointing Cloud Physics Lidar (CPL). This work was motivated by the need to obtain solutions for atmospheric soundings from infrared radiances observed for every individual field of view, regardless of cloud cover, from future ultraspectral geostationary satellite sounding instruments, such as the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and the Hyperspectral Environmental Suite (HES). However, this retrieval approach can also be applied to the ultraspectral sounding instruments to fly on Polar satellites, such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) on the NPOESS Preparatory Project and the following NPOESS series of satellites.

Cloud Optimized Image Format and Compression

Science.gov (United States)

Becker, P.; Plesea, L.; Maurer, T.

2015-04-01

Cloud based image storage and processing requires revaluation of formats and processing methods. For the true value of the massive volumes of earth observation data to be realized, the image data needs to be accessible from the cloud. Traditional file formats such as TIF and NITF were developed in the hay day of the desktop and assumed fast low latency file access. Other formats such as JPEG2000 provide for streaming protocols for pixel data, but still require a server to have file access. These concepts no longer truly hold in cloud based elastic storage and computation environments. This paper will provide details of a newly evolving image storage format (MRF) and compression that is optimized for cloud environments. Although the cost of storage continues to fall for large data volumes, there is still significant value in compression. For imagery data to be used in analysis and exploit the extended dynamic range of the new sensors, lossless or controlled lossy compression is of high value. Compression decreases the data volumes stored and reduces the data transferred, but the reduced data size must be balanced with the CPU required to decompress. The paper also outlines a new compression algorithm (LERC) for imagery and elevation data that optimizes this balance. Advantages of the compression include its simple to implement algorithm that enables it to be efficiently accessed using JavaScript. Combing this new cloud based image storage format and compression will help resolve some of the challenges of big image data on the internet.

Data fusion of Landsat TM and IRS images in forest classification

Science.gov (United States)

Guangxing Wang; Markus Holopainen; Eero Lukkarinen

2000-01-01

Data fusion of Landsat TM images and Indian Remote Sensing satellite panchromatic image (IRS-1C PAN) was studied and compared to the use of TM or IRS image only. The aim was to combine the high spatial resolution of IRS-1C PAN to the high spectral resolution of Landsat TM images using a data fusion algorithm. The ground truth of the study was based on a sample of 1,020...

IMAGE TO POINT CLOUD METHOD OF 3D-MODELING

Directory of Open Access Journals (Sweden)

A. G. Chibunichev

2012-07-01

Full Text Available This article describes the method of constructing 3D models of objects (buildings, monuments based on digital images and a point cloud obtained by terrestrial laser scanner. The first step is the automated determination of exterior orientation parameters of digital image. We have to find the corresponding points of the image and point cloud to provide this operation. Before the corresponding points searching quasi image of point cloud is generated. After that SIFT algorithm is applied to quasi image and real image. SIFT algorithm allows to find corresponding points. Exterior orientation parameters of image are calculated from corresponding points. The second step is construction of the vector object model. Vectorization is performed by operator of PC in an interactive mode using single image. Spatial coordinates of the model are calculated automatically by cloud points. In addition, there is automatic edge detection with interactive editing available. Edge detection is performed on point cloud and on image with subsequent identification of correct edges. Experimental studies of the method have demonstrated its efficiency in case of building facade modeling.

Cardiovascular imaging environment: will the future be cloud-based?

Science.gov (United States)

Kawel-Boehm, Nadine; Bluemke, David A

2017-07-01

In cardiovascular CT and MR imaging large datasets have to be stored, post-processed, analyzed and distributed. Beside basic assessment of volume and function in cardiac magnetic resonance imaging e.g., more sophisticated quantitative analysis is requested requiring specific software. Several institutions cannot afford various types of software and provide expertise to perform sophisticated analysis. Areas covered: Various cloud services exist related to data storage and analysis specifically for cardiovascular CT and MR imaging. Instead of on-site data storage, cloud providers offer flexible storage services on a pay-per-use basis. To avoid purchase and maintenance of specialized software for cardiovascular image analysis, e.g. to assess myocardial iron overload, MR 4D flow and fractional flow reserve, evaluation can be performed with cloud based software by the consumer or complete analysis is performed by the cloud provider. However, challenges to widespread implementation of cloud services include regulatory issues regarding patient privacy and data security. Expert commentary: If patient privacy and data security is guaranteed cloud imaging is a valuable option to cope with storage of large image datasets and offer sophisticated cardiovascular image analysis for institutions of all sizes.

The algorithm to generate color point-cloud with the registration between panoramic image and laser point-cloud

International Nuclear Information System (INIS)

Zeng, Fanyang; Zhong, Ruofei

2014-01-01

Laser point cloud contains only intensity information and it is necessary for visual interpretation to obtain color information from other sensor. Cameras can provide texture, color, and other information of the corresponding object. Points with color information of corresponding pixels in digital images can be used to generate color point-cloud and is conducive to the visualization, classification and modeling of point-cloud. Different types of digital cameras are used in different Mobile Measurement Systems (MMS).the principles and processes for generating color point-cloud in different systems are not the same. The most prominent feature of the panoramic images is the field of 360 degrees view angle in the horizontal direction, to obtain the image information around the camera as much as possible. In this paper, we introduce a method to generate color point-cloud with panoramic image and laser point-cloud, and deduce the equation of the correspondence between points in panoramic images and laser point-clouds. The fusion of panoramic image and laser point-cloud is according to the collinear principle of three points (the center of the omnidirectional multi-camera system, the image point on the sphere, the object point). The experimental results show that the proposed algorithm and formulae in this paper are correct

Room temperature mid-IR single photon spectral imaging

DEFF Research Database (Denmark)

Dam, Jeppe Seidelin; Tidemand-Lichtenberg, Peter; Pedersen, Christian

2012-01-01

Spectral imaging and detection of mid-infrared (mid-IR) wavelengths are emerging as an enabling technology of great technical and scientific interest; primarily because important chemical compounds display unique and strong mid-IR spectral fingerprints revealing valuable chemical information. Whi...... 20 % for polarized incoherent light at 3 \\mum. The proposed method is relevant for existing and new mid-IR applications like gas analysis and medical diagnostics....

Spatiotemporal High-Resolution Cloud Mapping with a Ground-Based IR Scanner

Directory of Open Access Journals (Sweden)

Benjamin Brede

2017-01-01

Full Text Available The high spatiotemporal variability of clouds requires automated monitoring systems. This study presents a retrieval algorithm that evaluates observations of a hemispherically scanning thermal infrared radiometer, the NubiScope, to produce georeferenced, spatially explicit cloud maps. The algorithm uses atmospheric temperature and moisture profiles and an atmospheric radiative transfer code to differentiate between cloudy and cloudless measurements. In case of a cloud, it estimates its position by using the temperature profile and viewing geometry. The proposed algorithm was tested with 25 cloud maps generated by the Fmask algorithm from Landsat 7 images. The overall cloud detection rate was ranging from 0.607 for zenith angles of 0 to 10° to 0.298 for 50–60° on a pixel basis. The overall detection of cloudless pixels was 0.987 for zenith angles of 30–40° and much more stable over the whole range of zenith angles compared to cloud detection. This proves the algorithm’s capability in detecting clouds, but even better cloudless areas. Cloud-base height was best estimated up to a height of 4000 m compared to ceilometer base heights but showed large deviation above that level. This study shows the potential of the NubiScope system to produce high spatial and temporal resolution cloud maps. Future development is needed for a more accurate determination of cloud height with thermal infrared measurements.

Limb darkening in Venus night-side disk as viewed from Akatsuki IR2

Science.gov (United States)

Satoh, Takehiko; Nakakushi, Takashi; Sato, Takao M.; Hashimoto, George L.

2017-10-01

Night-side hemisphere of Venus exhibits dark and bright regions as a result of spatially inhomogeneous cloud opacity which is illuminated by infrared radiation from deeper atmosphere. The 2-μm camera (IR2) onboard Akatsuki, Japan's Venus Climate Orbiter, is equipped with three narrow-band filters (1.735, 2.26, and 2.32 μm) to image Venus night-side disk in well-known transparency windows of CO2 atmosphere (Allen and Crawford 1984). In general, a cloud feature appears brightest when it is in the disk center and becomes darker as the zenith angle of emergent light increases. Such limb darkening was observed with Galileo/NIMS and mathematically approximated (Carlson et al., 1993). Limb-darkening correction helps to identify branches, in a 1.74-μm vs. 2.3-μm radiances scatter plot, each of which corresponds to a group of aerosols with similar properties. We analyzed Akatsuki/IR2 images to characterize the limb darkening for three night-side filters.There is, however, contamination from the intense day-side disk blurred by IR2's point spread function (PSF). It is found that infrared light can be multiplly reflected within the Si substrate of IR2 detector (1024x1024 pixels PtSi array), causing elongated tail in the actual PSF. We treated this in two different ways. One is to mathematically approximate the PSF (with a combination of modified Lorentz functions) and another is to differentiate 2.26-μm image from 2.32-μm image so that the blurred light pattern can directly be obtained. By comparing results from these two methods, we are able to reasonablly clean up the night-side images and limb darkening is extracted. Physical interpretation of limb darkening, as well as "true" time variations of cloud brightness will be presented/discussed.

Analysis of the development of missile-borne IR imaging detecting technologies

Science.gov (United States)

Fan, Jinxiang; Wang, Feng

2017-10-01

Today's infrared imaging guiding missiles are facing many challenges. With the development of targets' stealth, new-style IR countermeasures and penetrating technologies as well as the complexity of the operational environments, infrared imaging guiding missiles must meet the higher requirements of efficient target detection, capability of anti-interference and anti-jamming and the operational adaptability in complex, dynamic operating environments. Missileborne infrared imaging detecting systems are constrained by practical considerations like cost, size, weight and power (SWaP), and lifecycle requirements. Future-generation infrared imaging guiding missiles need to be resilient to changing operating environments and capable of doing more with fewer resources. Advanced IR imaging detecting and information exploring technologies are the key technologies that affect the future direction of IR imaging guidance missiles. Infrared imaging detecting and information exploring technologies research will support the development of more robust and efficient missile-borne infrared imaging detecting systems. Novelty IR imaging technologies, such as Infrared adaptive spectral imaging, are the key to effectively detect, recognize and track target under the complicated operating and countermeasures environments. Innovative information exploring techniques for the information of target, background and countermeasures provided by the detection system is the base for missile to recognize target and counter interference, jamming and countermeasure. Modular hardware and software development is the enabler for implementing multi-purpose, multi-function solutions. Uncooled IRFPA detectors and High-operating temperature IRFPA detectors as well as commercial-off-the-shelf (COTS) technology will support the implementing of low-cost infrared imaging guiding missiles. In this paper, the current status and features of missile-borne IR imaging detecting technologies are summarized. The key

Automatic cloud coverage assessment of Formosat-2 image

Science.gov (United States)

Hsu, Kuo-Hsien

2011-11-01

Formosat-2 satellite equips with the high-spatial-resolution (2m ground sampling distance) remote sensing instrument. It has been being operated on the daily-revisiting mission orbit by National Space organization (NSPO) of Taiwan since May 21 2004. NSPO has also serving as one of the ground receiving stations for daily processing the received Formosat- 2 images. The current cloud coverage assessment of Formosat-2 image for NSPO Image Processing System generally consists of two major steps. Firstly, an un-supervised K-means method is used for automatically estimating the cloud statistic of Formosat-2 image. Secondly, manual estimation of cloud coverage from Formosat-2 image is processed by manual examination. Apparently, a more accurate Automatic Cloud Coverage Assessment (ACCA) method certainly increases the efficiency of processing step 2 with a good prediction of cloud statistic. In this paper, mainly based on the research results from Chang et al, Irish, and Gotoh, we propose a modified Formosat-2 ACCA method which considered pre-processing and post-processing analysis. For pre-processing analysis, cloud statistic is determined by using un-supervised K-means classification, Sobel's method, Otsu's method, non-cloudy pixels reexamination, and cross-band filter method. Box-Counting fractal method is considered as a post-processing tool to double check the results of pre-processing analysis for increasing the efficiency of manual examination.

Remote sensing image segmentation based on Hadoop cloud platform

Science.gov (United States)

Li, Jie; Zhu, Lingling; Cao, Fubin

2018-01-01

To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.

Noninvasive enhanced mid-IR imaging of breast cancer development in vivo

Science.gov (United States)

Case, Jason R.; Young, Madison A.; Dréau, D.; Trammell, Susan R.

2015-11-01

Lumpectomy coupled with radiation therapy and/or chemotherapy is commonly used to treat breast cancer patients. We are developing an enhanced thermal IR imaging technique that has the potential to provide real-time imaging to guide tissue excision during a lumpectomy by delineating tumor margins. This enhanced thermal imaging method is a combination of IR imaging (8 to 10 μm) and selective heating of blood (˜0.5°C) relative to surrounding water-rich tissue using LED sources at low powers. Postacquisition processing of these images highlights temporal changes in temperature and the presence of vascular structures. In this study, fluorescent, standard thermal, and enhanced thermal imaging modalities, as well as physical caliper measurements, were used to monitor breast cancer tumor volumes over a 30-day study period in 19 mice implanted with 4T1-RFP tumor cells. Tumor volumes calculated from fluorescent imaging follow an exponential growth curve for the first 22 days of the study. Cell necrosis affected the tumor volume estimates based on the fluorescent images after day 22. The tumor volumes estimated from enhanced thermal imaging, standard thermal imaging, and caliper measurements all show exponential growth over the entire study period. A strong correlation was found between tumor volumes estimated using fluorescent imaging, standard IR imaging, and caliper measurements with enhanced thermal imaging, indicating that enhanced thermal imaging monitors tumor growth. Further, the enhanced IR images reveal a corona of bright emission along the edges of the tumor masses associated with the tumor margin. In the future, this IR technique might be used to estimate tumor margins in real time during surgical procedures.

Assessment of COTS IR image simulation tools for ATR development

Science.gov (United States)

Seidel, Heiko; Stahl, Christoph; Bjerkeli, Frode; Skaaren-Fystro, Paal

2005-05-01

Following the tendency of increased use of imaging sensors in military aircraft, future fighter pilots will need onboard artificial intelligence e.g. ATR for aiding them in image interpretation and target designation. The European Aeronautic Defence and Space Company (EADS) in Germany has developed an advanced method for automatic target recognition (ATR) which is based on adaptive neural networks. This ATR method can assist the crew of military aircraft like the Eurofighter in sensor image monitoring and thereby reduce the workload in the cockpit and increase the mission efficiency. The EADS ATR approach can be adapted for imagery of visual, infrared and SAR sensors because of the training-based classifiers of the ATR method. For the optimal adaptation of these classifiers they have to be trained with appropriate and sufficient image data. The training images must show the target objects from different aspect angles, ranges, environmental conditions, etc. Incomplete training sets lead to a degradation of classifier performance. Additionally, ground truth information i.e. scenario conditions like class type and position of targets is necessary for the optimal adaptation of the ATR method. In Summer 2003, EADS started a cooperation with Kongsberg Defence & Aerospace (KDA) from Norway. The EADS/KDA approach is to provide additional image data sets for training-based ATR through IR image simulation. The joint study aims to investigate the benefits of enhancing incomplete training sets for classifier adaptation by simulated synthetic imagery. EADS/KDA identified the requirements of a commercial-off-the-shelf IR simulation tool capable of delivering appropriate synthetic imagery for ATR development. A market study of available IR simulation tools and suppliers was performed. After that the most promising tool was benchmarked according to several criteria e.g. thermal emission model, sensor model, targets model, non-radiometric image features etc., resulting in a

Investigation of conspicuous infrared star cluster and star-forming region RCW 38 IR Cluster

International Nuclear Information System (INIS)

Gyulbudaghian, A.L.; May, J.

2008-01-01

An infrared star cluster RCW 38 IR Cluster, which is also a massive star-forming region, is investigated. The results of observations with SEST (Cerro is Silla, Chile) telescope on 2.6-mm 12 CO spectral line and with SIMBA on 1.2-mm continuum are given. The 12 CO observations revealed the existence of several molecular clouds, two of which (clouds I and 2) are connected with the object RCW 38 IR Cluster. Cloud 1 is a massive cloud, which has a depression in which the investigated object is embedded. It is not excluded that the depression was formed by the wind and/or emission from the young bright stars belonging to the star cluster. Rotation of cloud 2, around the axis having SE-NW direction, with an angular velocity ω 4.6 · 10 -14 s -1 is also found. A red-shifted outflow with velocity ∼+5.6 km/s, in the SE direction and perpendicular to the elongation of cloud 2 has been also found. The investigated cluster is associated with an IR point source IRAS 08573-4718, which has IR colours typical for a, non-evolved embedded (in the cloud) stellar object. The cluster is also connected with a water maser. The SIMBA image shoves the existence of a central bright condensation, coinciding with the cluster itself, and two extensions. One of these extensions (the one with SW-NE direction) coincides, both in place and shape, with cloud 2, so that it is not excluded the possibility that this extension might be also rotating like cloud 2. In the vicinity of these extensions there are condensations resembling HH objects

Image quality testing of assembled IR camera modules

Science.gov (United States)

Winters, Daniel; Erichsen, Patrik

2013-10-01

Infrared (IR) camera modules for the LWIR (8-12_m) that combine IR imaging optics with microbolometer focal plane array (FPA) sensors with readout electronics are becoming more and more a mass market product. At the same time, steady improvements in sensor resolution in the higher priced markets raise the requirement for imaging performance of objectives and the proper alignment between objective and FPA. This puts pressure on camera manufacturers and system integrators to assess the image quality of finished camera modules in a cost-efficient and automated way for quality control or during end-of-line testing. In this paper we present recent development work done in the field of image quality testing of IR camera modules. This technology provides a wealth of additional information in contrast to the more traditional test methods like minimum resolvable temperature difference (MRTD) which give only a subjective overall test result. Parameters that can be measured are image quality via the modulation transfer function (MTF) for broadband or with various bandpass filters on- and off-axis and optical parameters like e.g. effective focal length (EFL) and distortion. If the camera module allows for refocusing the optics, additional parameters like best focus plane, image plane tilt, auto-focus quality, chief ray angle etc. can be characterized. Additionally, the homogeneity and response of the sensor with the optics can be characterized in order to calculate the appropriate tables for non-uniformity correction (NUC). The technology can also be used to control active alignment methods during mechanical assembly of optics to high resolution sensors. Other important points that are discussed are the flexibility of the technology to test IR modules with different form factors, electrical interfaces and last but not least the suitability for fully automated measurements in mass production.

Cloud computing in medical imaging.

Science.gov (United States)

Kagadis, George C; Kloukinas, Christos; Moore, Kevin; Philbin, Jim; Papadimitroulas, Panagiotis; Alexakos, Christos; Nagy, Paul G; Visvikis, Dimitris; Hendee, William R

2013-07-01

Over the past century technology has played a decisive role in defining, driving, and reinventing procedures, devices, and pharmaceuticals in healthcare. Cloud computing has been introduced only recently but is already one of the major topics of discussion in research and clinical settings. The provision of extensive, easily accessible, and reconfigurable resources such as virtual systems, platforms, and applications with low service cost has caught the attention of many researchers and clinicians. Healthcare researchers are moving their efforts to the cloud, because they need adequate resources to process, store, exchange, and use large quantities of medical data. This Vision 20/20 paper addresses major questions related to the applicability of advanced cloud computing in medical imaging. The paper also considers security and ethical issues that accompany cloud computing.

Cloud2IR: Infrared thermography and environmental sensors integrated in an autonomoussystem for long term monitoring of structures

Science.gov (United States)

Crinière, Antoine; Dumoulin, Jean; Mevel, Laurent; Andrade-Barroso, Guillermo

2016-04-01

Since late 2014, the project Cloud2SM aims to develop a robust information system able to assess the long term monitoring of civil engineering structures as well as interfacing various sensors and data. Cloud2SM address three main goals, the management of distributed data and sensors network, the asynchronous processing of the data through network and the local management of the sensors themselves [1]. Integrated to this project Cloud2IR is an autonomous sensor system dedicated to the long term monitoring of infrastructures. Past experimentations have shown the need as well as usefulness of such system [2]. Before Cloud2IR an initially laboratory oriented system was used, which implied heavy operating system to be used [3]. Based on such system Cloud2IR has benefited of the experimental knowledge acquired to redefine a lighter architecture based on generics standards, more appropriated to autonomous operations on field and which can be later included in a wide distributed architecture such as Cloud2SM. The sensor system can be divided in two parts. The sensor side, this part is mainly composed by the various sensors drivers themselves as the infrared camera, the weather station or the pyranometers and their different fixed configurations. In our case, as infrared camera are slightly different than other kind of sensors, the system implement in addition an RTSP server which can be used to set up the FOV as well as other measurement parameter considerations. The second part can be seen as the data side, which is common to all sensors. It instantiate through a generic interface all the sensors and control the data access loop (not the requesting). This side of the system is weakly coupled (see data coupling) with the sensor side. It can be seen as a general framework able to aggregate any sensor data, type or size and automatically encapsulate them in various generic data format as HDF5 or cloud data as OGC SWE standard. This whole part is also responsible of the

CLOUD DETECTION OF OPTICAL SATELLITE IMAGES USING SUPPORT VECTOR MACHINE

Directory of Open Access Journals (Sweden)

K.-Y. Lee

2016-06-01

Full Text Available Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012 uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+ and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate

Cloud Detection of Optical Satellite Images Using Support Vector Machine

Science.gov (United States)

Lee, Kuan-Yi; Lin, Chao-Hung

2016-06-01

Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection

Imaging infrared: Scene simulation, modeling, and real image tracking; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

Science.gov (United States)

Triplett, Milton J.; Wolverton, James R.; Hubert, August J.

1989-09-01

Various papers on scene simulation, modeling, and real image tracking using IR imaging are presented. Individual topics addressed include: tactical IR scene generator, dynamic FLIR simulation in flight training research, high-speed dynamic scene simulation in UV to IR spectra, development of an IR sensor calibration facility, IR celestial background scene description, transmission measurement of optical components at cryogenic temperatures, diffraction model for a point-source generator, silhouette-based tracking for tactical IR systems, use of knowledge in electrooptical trackers, detection and classification of target formations in IR image sequences, SMPRAD: simplified three-dimensional cloud radiance model, IR target generator, recent advances in testing of thermal imagers, generic IR system models with dynamic image generation, modeling realistic target acquisition using IR sensors in multiple-observer scenarios, and novel concept of scene generation and comprehensive dynamic sensor test.

Progress towards NASA MODIS and Suomi NPP Cloud Property Data Record Continuity

Science.gov (United States)

Platnick, S.; Meyer, K.; Holz, R.; Ackerman, S. A.; Heidinger, A.; Wind, G.; Platnick, S. E.; Wang, C.; Marchant, B.; Frey, R.

2017-12-01

The Suomi NPP VIIRS imager provides an opportunity to extend the 17+ year EOS MODIS climate data record into the next generation operational era. Similar to MODIS, VIIRS provides visible through IR observations at moderate spatial resolution with a 1330 LT equatorial crossing consistent with the MODIS on the Aqua platform. However, unlike MODIS, VIIRS lacks key water vapor and CO2 absorbing channels used for high cloud detection and cloud-top property retrievals. In addition, there is a significant mismatch in the spectral location of the 2.2 μm shortwave-infrared channels used for cloud optical/microphysical retrievals and cloud thermodynamic phase. Given these instrument differences between MODIS EOS and VIIRS S-NPP/JPSS, a merged MODIS-VIIRS cloud record to serve the science community in the coming decades requires different algorithm approaches than those used for MODIS alone. This new approach includes two parallel efforts: (1) Imager-only algorithms with only spectral channels common to VIIRS and MODIS (i.e., eliminate use of MODIS CO2 and NIR/IR water vapor channels). Since the algorithms are run with similar spectral observations, they provide a basis for establishing a continuous cloud data record across the two imagers. (2) Merged imager and sounder measurements (i.e.., MODIS-AIRS, VIIRS-CrIS) in lieu of higher-spatial resolution MODIS absorption channels absent on VIIRS. The MODIS-VIIRS continuity algorithm for cloud optical property retrievals leverages heritage algorithms that produce the existing MODIS cloud mask (MOD35), optical and microphysical properties product (MOD06), and the NOAA AWG Cloud Height Algorithm (ACHA). We discuss our progress towards merging the MODIS observational record with VIIRS in order to generate cloud optical property climate data record continuity across the observing systems. In addition, we summarize efforts to reconcile apparent radiometric biases between analogous imager channels, a critical consideration for

PERIODIC ACCRETION INSTABILITIES IN THE PROTOSTAR L1634 IRS 7

Energy Technology Data Exchange (ETDEWEB)

Hodapp, Klaus W. [Institute for Astronomy, University of Hawaii, 640 N. Aohoku Place, Hilo, HI 96720 (United States); Chini, Rolf, E-mail: hodapp@ifa.hawaii.edu, E-mail: rolf.chini@astro.ruhr-uni-bochum.de [Astronomisches Institut, Ruhr-Universität Bochum, Universitätsstraße 150, D-44801 Bochum (Germany)

2015-11-10

The small molecular cloud Lynds 1634 contains at least three outflow sources. We found one of these, IRS 7, to be variable with a period of 37.14 ± 0.04 days and an amplitude of approximately 2 mag in the K{sub s} band. The light curve consists of a quiescent phase with little or no variation, and a rapid outburst phase. During the outburst phase, the rapid variation in brightness generates light echoes that propagate into the surrounding molecular cloud, allowing a measurement of the distance to IRS 7 of 404 pc ± 35 pc. We observed only a marginally significant change in the H − K color during the outburst phase. The K-band spectrum of IRS 7 shows CO bandhead emission but its equivalent width does not change significantly with the phase of the light curve. The H{sub 2} 1–0 S(1) line emission does not follow the variability of the continuum flux. We also used the imaging data for a proper motion study of the outflows originating from the IRS 7 and the far-infrared source IRAS 05173-0555, and confirm that these are indeed distinct outflows.

Multi-scale Adaptive Gain Control of IR Images

NARCIS (Netherlands)

Schutte, K.

1997-01-01

IR imagery tends to have a higher dynamic range then typical display devices such as a CRT. Global methods such as stretching and histogram equalization improve the visibility of many images, but some information in the images stays hidden for a human operator. This paper reports about the

Identification of clouds and aurorae in optical data images

CERN Document Server

Seviour, R; Honary, F

2003-01-01

In this paper we present an automatic image recognition technique used to identify clouds and aurorae in digital images, taken with a CCD all-sky imager. The image recognition algorithm uses image segmentation to generate a binary block object image. Object analysis is then performed on the binary block image, the results of which are used to assess whether clouds, aurorae and stars are present in the original image. The need for such an algorithm arises because the optical study of particle precipitation into the Earth's atmosphere by the Ionosphere and Radio Propagation Group at Lancaster generates vast data-sets, over 25 000 images/year, making manual classification of all the images impractical.

Featured Image: A Molecular Cloud Outside Our Galaxy

Science.gov (United States)

Kohler, Susanna

2018-06-01

What do molecular clouds look like outside of our own galaxy? See for yourself in the images above and below of N55, a molecular cloud located in the Large Magellanic Cloud (LMC). In a recent study led by Naslim Neelamkodan (Academia Sinica Institute of Astronomy and Astrophysics, Taiwan), a team of scientists explore N55 to determine how its cloud properties differ from clouds within the Milky Way. The image above reveals the distribution of infrared-emitting gas and dust observed in three bands by the Spitzer Space Telescope. Overplotted in cyan are observations from the Atacama Submillimeter Telescope Experiment tracing the clumpy, warm molecular gas. Below, new observations from the Atacama Large Millimeter/submillimeter Array (ALMA) reveal the sub-parsec-scale molecular clumps in greater detail, showing the correlation of massive clumps with Spitzer-identified young stellar objects (crosses). The study presented here indicates that this cloud in the LMC is the site of massive star formation, with properties similar to equivalent clouds in the Milky Way. To learn more about the authors findings, check out the article linked below.CitationNaslim N. et al 2018 ApJ 853 175. doi:10.3847/1538-4357/aaa5b0

Cloud classification using whole-sky imager data

Energy Technology Data Exchange (ETDEWEB)

Buch, K.A. Jr.; Sun, C.H.; Thorne, L.R. [Sandia National Labs., Livermore, CA (United States)

1996-04-01

Clouds are one of the most important moderators of the earth radiation budget and one of the least understood. The effect that clouds have on the reflection and absorption of solar and terrestrial radiation is strongly influenced by their shape, size, and composition. Physically accurate parameterization of clouds is necessary for any general circulation model (GCM) to yield meaningful results. The work presented here is part of a larger project that is aimed at producing realistic three-dimensional (3D) volume renderings of cloud scenes based on measured data from real cloud scenes. These renderings will provide the important shape information for parameterizing GCMs. The specific goal of the current study is to develop an algorithm that automatically classifies (by cloud type) the clouds observed in the scene. This information will assist the volume rendering program in determining the shape of the cloud. Much work has been done on cloud classification using multispectral satellite images. Most of these references use some kind of texture measure to distinguish the different cloud types and some also use topological features (such as cloud/sky connectivity or total number of clouds). A wide variety of classification methods has been used, including neural networks, various types of clustering, and thresholding. The work presented here uses binary decision trees to distinguish the different cloud types based on cloud features vectors.

High-definition Fourier Transform Infrared (FT-IR) Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology

Science.gov (United States)

Nguyen, Peter L.; Davidson, Bennett; Akkina, Sanjeev; Guzman, Grace; Setty, Suman; Kajdacsy-Balla, Andre; Walsh, Michael J.

2015-01-01

High-definition Fourier Transform Infrared (FT-IR) spectroscopic imaging is an emerging approach to obtain detailed images that have associated biochemical information. FT-IR imaging of tissue is based on the principle that different regions of the mid-infrared are absorbed by different chemical bonds (e.g., C=O, C-H, N-H) within cells or tissue that can then be related to the presence and composition of biomolecules (e.g., lipids, DNA, glycogen, protein, collagen). In an FT-IR image, every pixel within the image comprises an entire Infrared (IR) spectrum that can give information on the biochemical status of the cells that can then be exploited for cell-type or disease-type classification. In this paper, we show: how to obtain IR images from human tissues using an FT-IR system, how to modify existing instrumentation to allow for high-definition imaging capabilities, and how to visualize FT-IR images. We then present some applications of FT-IR for pathology using the liver and kidney as examples. FT-IR imaging holds exciting applications in providing a novel route to obtain biochemical information from cells and tissue in an entirely label-free non-perturbing route towards giving new insight into biomolecular changes as part of disease processes. Additionally, this biochemical information can potentially allow for objective and automated analysis of certain aspects of disease diagnosis. PMID:25650759

Image registration of naval IR images

Science.gov (United States)

Rodland, Arne J.

1996-06-01

In a real world application an image from a stabilized sensor on a moving platform will not be 100 percent stabilized. There will always be a small unknown error in the stabilization due to factors such as dynamic deformations in the structure between sensor and reference Inertial Navigation Unit, servo inaccuracies, etc. For a high resolution imaging sensor this stabilization error causes the image to move several pixels in unknown direction between frames. TO be able to detect and track small moving objects from such a sensor, this unknown movement of the sensor image must be estimated. An algorithm that searches for land contours in the image has been evaluated. The algorithm searches for high contrast points distributed over the whole image. As long as moving objects in the scene only cover a small area of the scene, most of the points are located on solid ground. By matching the list of points from frame to frame, the movement of the image due to stabilization errors can be estimated and compensated. The point list is searched for points with diverging movement from the estimated stabilization error. These points are then assumed to be located on moving objects. Points assumed to be located on moving objects are gradually exchanged with new points located in the same area. Most of the processing is performed on the list of points and not on the complete image. The algorithm is therefore very fast and well suited for real time implementation. The algorithm has been tested on images from an experimental IR scanner. Stabilization errors were added artificially to the image such that the output from the algorithm could be compared with the artificially added stabilization errors.

Simultaneous monitoring of ice accretion and thermography of an airfoil: an IR imaging methodology

International Nuclear Information System (INIS)

Mohseni, M; Frioult, M; Amirfazli, A

2012-01-01

A novel image analysis methodology based on infrared (IR) imaging was developed for simultaneous monitoring of ice accretion and thermography of airfoils. In this study, an IR camera was calibrated and used to measure the surface temperature of the energized airfoils, and monitor the ice accretion and growth pattern on the airfoils’ surfaces. The methodology comprises the automatic processing of a series of IR video frames with the purpose of detecting ice pattern evolution during the icing test period. A specially developed MATLAB code was used to detect the iced areas in the IR images, and simultaneously monitor surface temperature evolution of the airfoil during an icing test. Knowing the correlation between the icing pattern and surface temperature changes during an icing test is essential for energy efficient design of thermal icing mitigation systems. Processed IR images were also used to determine the ice accumulation rate on the airfoil's surface in a given icing test. The proposed methodology has been demonstrated to work successfully, since the optical images taken at the end of icing tests from the airfoils’ surfaces compared well with the processed IR images detecting the ice grown outward from the airfoils’ leading edge area. (paper)

IR imaging of blood circulation of patients with vascular disease

Science.gov (United States)

Wang, Hsin; Wade, Dwight R., Jr.; Kam, Jack

2004-04-01

We conducted a preliminary IR imaging study of blood circulation in patients with peripheral vascular diseases. Abnormal blood flow is common in older adults, especially those with elevated blood lipids, diabetes, hypertension, and a history of smoking. All of these conditions have a high prevalence in our population, often with more than one condition in the same individual. The differences in blood flow is revealed by temperature differences in areas of the extremities as well as other regions of the body. However, what is needed is an imaging technique that is relatively inexpensive and can reveal the blood flow in real time. The IR imaging can show detailed venous system and small tempearture changes associated with blood flow. Six patients with vascular diseases were tested in a clinic set up. Their legs and feet were imaged. We observed large temperature differences (cooling of more than 10° C) at the foot, especially toes. More valuable information were obtained from the temperature distribution maps. IR thermography is potentially a very valuable tool for medical application, especially for vascular diseases.

A holistic image segmentation framework for cloud detection and extraction

Science.gov (United States)

Shen, Dan; Xu, Haotian; Blasch, Erik; Horvath, Gregory; Pham, Khanh; Zheng, Yufeng; Ling, Haibin; Chen, Genshe

2013-05-01

Atmospheric clouds are commonly encountered phenomena affecting visual tracking from air-borne or space-borne sensors. Generally clouds are difficult to detect and extract because they are complex in shape and interact with sunlight in a complex fashion. In this paper, we propose a clustering game theoretic image segmentation based approach to identify, extract, and patch clouds. In our framework, the first step is to decompose a given image containing clouds. The problem of image segmentation is considered as a "clustering game". Within this context, the notion of a cluster is equivalent to a classical equilibrium concept from game theory, as the game equilibrium reflects both the internal and external (e.g., two-player) cluster conditions. To obtain the evolutionary stable strategies, we explore three evolutionary dynamics: fictitious play, replicator dynamics, and infection and immunization dynamics (InImDyn). Secondly, we use the boundary and shape features to refine the cloud segments. This step can lower the false alarm rate. In the third step, we remove the detected clouds and patch the empty spots by performing background recovery. We demonstrate our cloud detection framework on a video clip provides supportive results.

The Application of the Technology of 3D Satellite Cloud Imaging in Virtual Reality Simulation

Directory of Open Access Journals (Sweden)

Xiao-fang Xie

2007-05-01

Full Text Available Using satellite cloud images to simulate clouds is one of the new visual simulation technologies in Virtual Reality (VR. Taking the original data of satellite cloud images as the source, this paper depicts specifically the technology of 3D satellite cloud imaging through the transforming of coordinates and projection, creating a DEM (Digital Elevation Model of cloud imaging and 3D simulation. A Mercator projection was introduced to create a cloud image DEM, while solutions for geodetic problems were introduced to calculate distances, and the outer-trajectory science of rockets was introduced to obtain the elevation of clouds. For demonstration, we report on a computer program to simulate the 3D satellite cloud images.

Cloud Overlapping Detection Algorithm Using Solar and IR Wavelengths With GOSE Data Over ARM/SGP Site

Science.gov (United States)

Kawamoto, Kazuaki; Minnis, Patrick; Smith, William L., Jr.

2001-01-01

One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a 1-layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum el al. (1995) used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow (1997) also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. (1999) used a combination infrared, visible, and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne (2000) proposed 1.6 and 11 microns. bispectral threshold method. While all of these methods have made progress in solving this stubborn problem, none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the ARM domains (e.g., Minnis et al 1998) and hence should identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the NOAA Advanced Very High Resolution Radiometer (AVHRR) used over the ARM SGP and NSA sites to study the

Image selection as a service for cloud computing environments

KAUST Repository

Filepp, Robert

2010-12-01

Customers of Cloud Services are expected to choose specific machine images to instantiate in order to host their workloads. Unfortunately very little information is provided to the users to enable them to make intelligent choices. We believe that as the number of images proliferates it will become increasingly difficult for users to decide effectively. Cloud service providers often allow their customers to instantiate standard system images, to modify their instances, and to store images of these customized instances for public or private future use. Storing modified instances as images enables customers to avoid re-provisioning and re-configuration of required resources thereby reducing their future costs. However Cloud service providers generally do not expose details regarding the configurations of the images in a rigorous canonical fashion nor offer services that assist clients in the best target image selection to support client transformation objectives. Rather, they allow customers to enter a free-form description of an image based on client\\'s best effort. This means in order to find a "best fit" image to instantiate, a human user must review potentially thousands of image descriptions, reading each description to evaluate its suitability as a platform to host their source application. Furthermore, the actual content of the selected image may differ greatly from its description. Finally, even images that have been customized and retained for future use may need additional provisioning and customization to accommodate specific needs. In this paper we propose a service that accumulates image configuration details in a canonical fashion and a further service that employs an algorithm to order images per best fit /least cost in conformance to user-specified policies. These services collectively facilitate workload transformation into enterprise cloud environments.

Research into the usage of integrated jamming of IR weakening and smoke-screen resisting the IR imaging guided missiles

Science.gov (United States)

Wang, Long-tao; Jiang, Ning; Lv, Ming-shan

2015-10-01

With the emergence of the anti-ship missle with the capability of infrared imaging guidance, the traditional single jamming measures, because of the jamming mechanism and technical flaws or unsuitable use, greatly reduced the survival probability of the war-ship in the future naval battle. Intergrated jamming of IR weakening + smoke-screen Can not only make jamming to the search and tracking of IR imaging guidance system , but also has feasibility in conjunction, besides , which also make the best jamming effect. The research conclusion has important realistic meaning for raising the antimissile ability of surface ships. With the development of guidance technology, infrared guidance system has expanded by ir point-source homing guidance to infrared imaging guidance, Infrared imaging guidance has made breakthrough progress, Infrared imaging guidance system can use two-dimensional infrared image information of the target, achieve the precise tracking. Which has Higher guidance precision, better concealment, stronger anti-interference ability and could Target the key parts. The traditional single infrared smoke screen jamming or infrared decoy flare interference cannot be imposed effective interference. So, Research how to effectively fight against infrared imaging guided weapons threat measures and means, improving the surface ship antimissile ability is an urgent need to solve.

Self-Similar Spin Images for Point Cloud Matching

Science.gov (United States)

Pulido, Daniel

based on the concept of self-similarity to aid in the scale and feature matching steps. An open problem in fusion is how best to extract features from two point clouds and then perform feature-based matching. The proposed approach for this matching step is the use of local self-similarity as an invariant measure to match features. In particular, the proposed approach is to combine the concept of local self-similarity with a well-known feature descriptor, Spin Images, and thereby define "Self-Similar Spin Images". This approach is then extended to the case of matching two points clouds in very different coordinate systems (e.g., a geo-referenced Lidar point cloud and stereo-image derived point cloud without geo-referencing). The use of Self-Similar Spin Images is again applied to address this problem by introducing a "Self-Similar Keyscale" that matches the spatial scales of two point clouds. Another open problem is how best to detect changes in content between two point clouds. A method is proposed to find changes between two point clouds by analyzing the order statistics of the nearest neighbors between the two clouds, and thereby define the "Nearest Neighbor Order Statistic" method. Note that the well-known Hausdorff distance is a special case as being just the maximum order statistic. Therefore, by studying the entire histogram of these nearest neighbors it is expected to yield a more robust method to detect points that are present in one cloud but not the other. This approach is applied at multiple resolutions. Therefore, changes detected at the coarsest level will yield large missing targets and at finer levels will yield smaller targets.

Real-Time Estimation of Volcanic ASH/SO2 Cloud Height from Combined Uv/ir Satellite Observations and Numerical Modeling

Science.gov (United States)

Vicente, Gilberto A.

An efficient iterative method has been developed to estimate the vertical profile of SO2 and ash clouds from volcanic eruptions by comparing near real-time satellite observations with numerical modeling outputs. The approach uses UV based SO2 concentration and IR based ash cloud images, the volcanic ash transport model PUFF and wind speed, height and directional information to find the best match between the simulated and the observed displays. The method is computationally fast and is being implemented for operational use at the NOAA Volcanic Ash Advisory Centers (VAACs) in Washington, DC, USA, to support the Federal Aviation Administration (FAA) effort to detect, track and measure volcanic ash cloud heights for air traffic safety and management. The presentation will show the methodology, results, statistical analysis and SO2 and Aerosol Index input products derived from the Ozone Monitoring Instrument (OMI) onboard the NASA EOS/Aura research satellite and from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument in the MetOp-A. The volcanic ash products are derived from AVHRR instruments in the NOAA POES-16, 17, 18, 19 as well as MetOp-A. The presentation will also show how a VAAC volcanic ash analyst interacts with the system providing initial condition inputs such as location and time of the volcanic eruption, followed by the automatic real-time tracking of all the satellite data available, subsequent activation of the iterative approach and the data/product delivery process in numerical and graphical format for operational applications.

Upconversion applied for mid-IR hyperspectral image acquisition

DEFF Research Database (Denmark)

Tidemand-Lichtenberg, Peter; Kehlet, Louis Martinus; Sanders, Nicolai Højer

2015-01-01

Different schemes for upconversion mid-IR hyperspectral imaging is implemented and compared in terms of spectral coverage, spectral resolution, speed and noise. Phasematch scanning and scanning of the object within the field of view is considered....

RESEARCH OF REGISTRATION APPROACHES OF THERMAL INFRARED IMAGES AND INTENSITY IMAGES OF POINT CLOUD

Directory of Open Access Journals (Sweden)

L. Liu

2017-09-01

Full Text Available In order to realize the analysis of thermal energy of the objects in 3D vision, the registration approach of thermal infrared images and TLS (Terrestrial Laser Scanner point cloud was studied. The original data was pre-processed. For the sake of making the scale and brightness contrast of the two kinds of data meet the needs of basic matching, the intensity image of point cloud was produced and projected to spherical coordinate system, histogram equalization processing was done for thermal infrared image.This paper focused on the research of registration approaches of thermal infrared images and intensity images of point cloud based on SIFT，EOH-SIFT and PIIFD operators. The latter of which is usually used for medical image matching with different spectral character. The comparison results of the experiments showed that PIIFD operator got much more accurate feature point correspondences compared to SIFT and EOH-SIFT operators. The thermal infrared image and intensity image also have ideal overlap results by quadratic polynomial transformation. Therefore, PIIFD can be used as the basic operator for the registration of thermal infrared images and intensity images, and the operator can also be further improved by incorporating the iteration method.

Contribution To The Data Warehouse And Prospects Of The IRS Program

Science.gov (United States)

Barner, Frithjof; Haydn, Rupert; Parmar, Manish; Makiola, Jens

2013-12-01

Over the past two years, the IRS program has again significantly contributed to the GSC-DA Data Warehouse. From its suite of optical EO satellites which operate in the visible, near IR and shortwave IR domain, multispectral data from the HR LISS-III and MR AWiFS sensors have been provided. Both cameras are implemented on board of Resourcesat-1 and Resourcesat-2 respectively. Despite reduced capacities, the Resourcesat constellation of satellites so far acquired cloud-free images of a vast majority of the first HR coverage of CORE_001 and several monthly MR coverages for CORE_008 over the EEA-39. The results regarding the above mentioned data sets will be discussed including an appraisal of the possible future role of upcoming IRS EO satellites for European data requirements.

A spatial study of the mid-IR emission features in four Herbig Ae/Be stars

NARCIS (Netherlands)

Boersma, C.; Peeters, E.; Martin-Hernandez, N. L.; van der Wolk, G.; Verhoeff, A. P.; Tielens, A. G. G. M.; Waters, L. B. F. M.; Pel, J. W.

Context. Infrared (IR) spectroscopy and imaging provide a prime tool to study the characteristics of polycyclic aromatic hydrocarbon (PAH) molecules and the mineralogy in regions of star formation. Herbig Ae/Be stars are known to have varying amounts of natal cloud material present in their

Estimating nocturnal opaque ice cloud optical depth from MODIS multispectral infrared radiances using a neural network method

Science.gov (United States)

Minnis, Patrick; Hong, Gang; Sun-Mack, Szedung; Smith, William L.; Chen, Yan; Miller, Steven D.

2016-05-01

Retrieval of ice cloud properties using IR measurements has a distinct advantage over the visible and near-IR techniques by providing consistent monitoring regardless of solar illumination conditions. Historically, the IR bands at 3.7, 6.7, 11.0, and 12.0 µm have been used to infer ice cloud parameters by various methods, but the reliable retrieval of ice cloud optical depth τ is limited to nonopaque cirrus with τ < 8. The Ice Cloud Optical Depth from Infrared using a Neural network (ICODIN) method is developed in this paper by training Moderate Resolution Imaging Spectroradiometer (MODIS) radiances at 3.7, 6.7, 11.0, and 12.0 µm against CloudSat-estimated τ during the nighttime using 2 months of matched global data from 2007. An independent data set comprising observations from the same 2 months of 2008 was used to validate the ICODIN. One 4-channel and three 3-channel versions of the ICODIN were tested. The training and validation results show that IR channels can be used to estimate ice cloud τ up to 150 with correlations above 78% and 69% for all clouds and only opaque ice clouds, respectively. However, τ for the deepest clouds is still underestimated in many instances. The corresponding RMS differences relative to CloudSat are ~100 and ~72%. If the opaque clouds are properly identified with the IR methods, the RMS differences in the retrieved optical depths are ~62%. The 3.7 µm channel appears to be most sensitive to optical depth changes but is constrained by poor precision at low temperatures. A method for estimating total optical depth is explored for estimation of cloud water path in the future. Factors affecting the uncertainties and potential improvements are discussed. With improved techniques for discriminating between opaque and semitransparent ice clouds, the method can ultimately improve cloud property monitoring over the entire diurnal cycle.

An Uneven Illumination Correction Algorithm for Optical Remote Sensing Images Covered with Thin Clouds

Directory of Open Access Journals (Sweden)

Xiaole Shen

2015-09-01

Full Text Available The uneven illumination phenomenon caused by thin clouds will reduce the quality of remote sensing images, and bring adverse effects to the image interpretation. To remove the effect of thin clouds on images, an uneven illumination correction can be applied. In this paper, an effective uneven illumination correction algorithm is proposed to remove the effect of thin clouds and to restore the ground information of the optical remote sensing image. The imaging model of remote sensing images covered by thin clouds is analyzed. Due to the transmission attenuation, reflection, and scattering, the thin cloud cover usually increases region brightness and reduces saturation and contrast of the image. As a result, a wavelet domain enhancement is performed for the image in Hue-Saturation-Value (HSV color space. We use images with thin clouds in Wuhan area captured by QuickBird and ZiYuan-3 (ZY-3 satellites for experiments. Three traditional uneven illumination correction algorithms, i.e., multi-scale Retinex (MSR algorithm, homomorphic filtering (HF-based algorithm, and wavelet transform-based MASK (WT-MASK algorithm are performed for comparison. Five indicators, i.e., mean value, standard deviation, information entropy, average gradient, and hue deviation index (HDI are used to analyze the effect of the algorithms. The experimental results show that the proposed algorithm can effectively eliminate the influences of thin clouds and restore the real color of ground objects under thin clouds.

3D Point Cloud Reconstruction from Single Plenoptic Image

Directory of Open Access Journals (Sweden)

F. Murgia

2016-06-01

Full Text Available Novel plenoptic cameras sample the light field crossing the main camera lens. The information available in a plenoptic image must be processed, in order to create the depth map of the scene from a single camera shot. In this paper a novel algorithm, for the reconstruction of 3D point cloud of the scene from a single plenoptic image, taken with a consumer plenoptic camera, is proposed. Experimental analysis is conducted on several test images, and results are compared with state of the art methodologies. The results are very promising, as the quality of the 3D point cloud from plenoptic image, is comparable with the quality obtained with current non-plenoptic methodologies, that necessitate more than one image.

Synergistic multi-sensor and multi-frequency retrieval of cloud ice water path constrained by CloudSat collocations

International Nuclear Information System (INIS)

Islam, Tanvir; Srivastava, Prashant K.

2015-01-01

The cloud ice water path (IWP) is one of the major parameters that have a strong influence on earth's radiation budget. Onboard satellite sensors are recognized as valuable tools to measure the IWP in a global scale. Albeit, active sensors such as the Cloud Profiling Radar (CPR) onboard the CloudSat satellite has better capability to measure the ice water content profile, thus, its vertical integral, IWP, than any passive microwave (MW) or infrared (IR) sensors. In this study, we investigate the retrieval of IWP from MW and IR sensors, including AMSU-A, MHS, and HIRS instruments on-board the N19 satellite, such that the retrieval is consistent with the CloudSat IWP estimates. This is achieved through the collocations between the passive satellite measurements and CloudSat scenes. Potential benefit of synergistic multi-sensor multi-frequency retrieval is investigated. Two modeling approaches are explored for the IWP retrieval – generalized linear model (GLM) and neural network (NN). The investigation has been carried out over both ocean and land surface types. The MW/IR synergy is found to be retrieved more accurate IWP than the individual AMSU-A, MHS, or HIRS measurements. Both GLM and NN approaches have been able to exploit the synergistic retrievals. - Highlights: • MW/IR synergy is investigated for IWP retrieval. • The IWP retrieval is modeled using CloudSat collocations. • Two modeling approaches are explored – GLM and ANN. • MW/IR synergy performs better than the MW or IR only retrieval

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations. Part I: Forward Model, Error Analysis, and Information Content

Science.gov (United States)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (tau), effective radius (r(sub eff)), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations. Part I: Forward model, error analysis, and information content

Science.gov (United States)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2018-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud-top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available. PMID:29707470

Cloud cover over the equatorial eastern Pacific derived from July 1983 International Satellite Cloud Climatology Project data using a hybrid bispectral threshold method

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Minnis, Patrick; Harrison, Edwin F.; Gibson, Gary G.

1987-01-01

A set of visible and IR data obtained with GOES from July 17-31, 1983 is analyzed using a modified version of the hybrid bispectral threshold method developed by Minnis and Harrison (1984). This methodology can be divided into a set of procedures or optional techniques to determine the proper contaminate clear-sky temperature or IR threshold. The various optional techniques are described; the options are: standard, low-temperature limit, high-reflectance limit, low-reflectance limit, coldest pixel and thermal adjustment limit, IR-only low-cloud temperature limit, IR clear-sky limit, and IR overcast limit. Variations in the cloud parameters and the characteristics and diurnal cycles of trade cumulus and stratocumulus clouds over the eastern equatorial Pacific are examined. It is noted that the new method produces substantial changes in about one third of the cloud amount retrieval; and low cloud retrievals are affected most by the new constraints.

Images from Galileo of the Venus cloud deck

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Belton, M.J.S.; Gierasch, P.J.; Smith, M.D.; Helfenstein, P.; Schinder, P.J.; Pollack, James B.; Rages, K.A.; Ingersoll, A.P.; Klaasen, K.P.; Veverka, J.; Anger, C.D.; Carr, M.H.; Chapman, C.R.; Davies, M.E.; Fanale, F.P.; Greeley, R.; Greenberg, R.; Head, J. W.; Morrison, D.; Neukum, G.; Pilcher, C.B.

1991-01-01

Images of Venus taken at 418 (violet) and 986 [near-infrared (NIR)] nanometers show that the morphology and motions of large-scale features change with depth in the cloud deck. Poleward meridional velocities, seen in both spectral regions, are much reduced in the NIR. In the south polar region the markings in the two wavelength bands are strongly anticorrelated. The images follow the changing state of the upper cloud layer downwind of the subsolar point, and the zonal flow field shows a longitudinal periodicity that may be coupled to the formation of large-scale planetary waves. No optical lightning was detected.

Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

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Su, X.

2017-12-01

A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

Long-term Behaviour Of Venus Winds At Cloud Level From Virtis/vex Observations

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Hueso, Ricardo; Peralta, J.; Sánchez-Lavega, A.; Pérez-Hoyos, S.; Piccioni, G.; Drossart, P.

2009-09-01

The Venus Express (VEX) mission has been in orbit to Venus for more than three years now. The VIRTIS instrument onboard VEX observes Venus in two channels (visible and infrared) obtaining spectra and multi-wavelength images of the planet. Images in the ultraviolet range are used to study the upper cloud at 66 km while images in the infrared (1.74 μm) map the opacity of the lower cloud deck at 48 km. Here we present an analysis of the overall dynamics of Venus’ atmosphere at both levels using observations that cover a large fraction of the VIRTIS dataset. We will present our latest results concerning the zonal winds, the overall stability in the lower cloud deck motions and the variability in the upper cloud. Meridional winds are also observed in the upper and lower cloud in the UV and IR images obtained with VIRTIS. While the upper clouds present a net meridional motion consistent with the upper branch of a Hadley cell the lower cloud present more irregular, variable and less intense motions in the meridional direction. Acknowledgements This work has been funded by Spanish MEC AYA2006-07735 with FEDER support and Grupos Gobierno Vasco IT-464-07. RH acknowledges a "Ramón y Cajal” contract from MEC.

Reflective all-sky thermal infrared cloud imager.

Science.gov (United States)

Redman, Brian J; Shaw, Joseph A; Nugent, Paul W; Clark, R Trevor; Piazzolla, Sabino

2018-04-30

A reflective all-sky imaging system has been built using a long-wave infrared microbolometer camera and a reflective metal sphere. This compact system was developed for measuring spatial and temporal patterns of clouds and their optical depth in support of applications including Earth-space optical communications. The camera is mounted to the side of the reflective sphere to leave the zenith sky unobstructed. The resulting geometric distortion is removed through an angular map derived from a combination of checkerboard-target imaging, geometric ray tracing, and sun-location-based alignment. A tape of high-emissivity material on the side of the reflector acts as a reference that is used to estimate and remove thermal emission from the metal sphere. Once a bias that is under continuing study was removed, sky radiance measurements from the all-sky imager in the 8-14 μm wavelength range agreed to within 0.91 W/(m 2 sr) of measurements from a previously calibrated, lens-based infrared cloud imager over its 110° field of view.

Toward Confirming a Framework for Securing the Virtual Machine Image in Cloud Computing

Directory of Open Access Journals (Sweden)

Raid Khalid Hussein

2017-04-01

Full Text Available The concept of cloud computing has arisen thanks to academic work in the fields of utility computing, distributed computing, virtualisation, and web services. By using cloud computing, which can be accessed from anywhere, newly-launched businesses can minimise their start-up costs. Among the most important notions when it comes to the construction of cloud computing is virtualisation. While this concept brings its own security risks, these risks are not necessarily related to the cloud. The main disadvantage of using cloud computing is linked to safety and security. This is because anybody which chooses to employ cloud computing will use someone else’s hard disk and CPU in order to sort and store data. In cloud environments, a great deal of importance is placed on guaranteeing that the virtual machine image is safe and secure. Indeed, a previous study has put forth a framework with which to protect the virtual machine image in cloud computing. As such, the present study is primarily concerned with confirming this theoretical framework so as to ultimately secure the virtual machine image in cloud computing. This will be achieved by carrying out interviews with experts in the field of cloud security.

Coupled Retrieval of Liquid Water Cloud and Above-Cloud Aerosol Properties Using the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)

Science.gov (United States)

Xu, Feng; van Harten, Gerard; Diner, David J.; Davis, Anthony B.; Seidel, Felix C.; Rheingans, Brian; Tosca, Mika; Alexandrov, Mikhail D.; Cairns, Brian; Ferrare, Richard A.; Burton, Sharon P.; Fenn, Marta A.; Hostetler, Chris A.; Wood, Robert; Redemann, Jens

2018-03-01

An optimization algorithm is developed to retrieve liquid water cloud properties including cloud optical depth (COD), droplet size distribution and cloud top height (CTH), and above-cloud aerosol properties including aerosol optical depth (AOD), single-scattering albedo, and microphysical properties from sweep-mode observations by Jet Propulsion Laboratory's Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) instrument. The retrieval is composed of three major steps: (1) initial estimate of the mean droplet size distribution across the entire image of 80-100 km along track by 10-25 km across track from polarimetric cloudbow observations, (2) coupled retrieval of image-scale cloud and above-cloud aerosol properties by fitting the polarimetric data at all observation angles, and (3) iterative retrieval of 1-D radiative transfer-based COD and droplet size distribution at pixel scale (25 m) by establishing relationships between COD and droplet size and fitting the total radiance measurements. Our retrieval is tested using 134 AirMSPI data sets acquired during the National Aeronautics and Space Administration (NASA) field campaign ObseRvations of Aerosols above CLouds and their intEractionS. The retrieved above-cloud AOD and CTH are compared to coincident HSRL-2 (HSRL-2, NASA Langley Research Center) data, and COD and droplet size distribution parameters (effective radius reff and effective variance veff) are compared to coincident Research Scanning Polarimeter (RSP) (NASA Goddard Institute for Space Studies) data. Mean absolute differences between AirMSPI and HSRL-2 retrievals of above-cloud AOD at 532 nm and CTH are 0.03 and mean absolute differences between RSP and AirMSPI retrievals of COD, reff, and veff in the cloudbow area are 2.33, 0.69 μm, and 0.020, respectively. Neglect of smoke aerosols above cloud leads to an underestimate of image-averaged COD by 15%.

GIFT-Cloud: A data sharing and collaboration platform for medical imaging research.

Science.gov (United States)

Doel, Tom; Shakir, Dzhoshkun I; Pratt, Rosalind; Aertsen, Michael; Moggridge, James; Bellon, Erwin; David, Anna L; Deprest, Jan; Vercauteren, Tom; Ourselin, Sébastien

2017-02-01

Clinical imaging data are essential for developing research software for computer-aided diagnosis, treatment planning and image-guided surgery, yet existing systems are poorly suited for data sharing between healthcare and academia: research systems rarely provide an integrated approach for data exchange with clinicians; hospital systems are focused towards clinical patient care with limited access for external researchers; and safe haven environments are not well suited to algorithm development. We have established GIFT-Cloud, a data and medical image sharing platform, to meet the needs of GIFT-Surg, an international research collaboration that is developing novel imaging methods for fetal surgery. GIFT-Cloud also has general applicability to other areas of imaging research. GIFT-Cloud builds upon well-established cross-platform technologies. The Server provides secure anonymised data storage, direct web-based data access and a REST API for integrating external software. The Uploader provides automated on-site anonymisation, encryption and data upload. Gateways provide a seamless process for uploading medical data from clinical systems to the research server. GIFT-Cloud has been implemented in a multi-centre study for fetal medicine research. We present a case study of placental segmentation for pre-operative surgical planning, showing how GIFT-Cloud underpins the research and integrates with the clinical workflow. GIFT-Cloud simplifies the transfer of imaging data from clinical to research institutions, facilitating the development and validation of medical research software and the sharing of results back to the clinical partners. GIFT-Cloud supports collaboration between multiple healthcare and research institutions while satisfying the demands of patient confidentiality, data security and data ownership. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

GEWEX cloud assessment: A review

Science.gov (United States)

Stubenrauch, Claudia; Rossow, William B.; Kinne, Stefan; Ackerman, Steve; Cesana, Gregory; Chepfer, Hélène; Di Girolamo, Larry; Getzewich, Brian; Guignard, Anthony; Heidinger, Andy; Maddux, Brent; Menzel, Paul; Minnis, Patrick; Pearl, Cindy; Platnick, Steven; Poulsen, Caroline; Riedi, Jérôme; Sayer, Andrew; Sun-Mack, Sunny; Walther, Andi; Winker, Dave; Zeng, Shen; Zhao, Guangyu

2013-05-01

Clouds cover about 70% of the Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the entire globe and across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite cloud data records now exceed more than 25 years; however, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors. The Global Energy and Water cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel, provides the first coordinated intercomparison of publicly available, global cloud products (gridded, monthly statistics) retrieved from measurements of multi-spectral imagers (some with multi-angle view and polarization capabilities), IR sounders and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature or altitude), cloud radiative properties (optical depth or emissivity), cloud thermodynamic phase and bulk microphysical properties (effective particle size and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. The monthly, gridded database presented here facilitates further assessments, climate studies, and the evaluation of climate models.

Registration of vehicle based panoramic image and LiDAR point cloud

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Chen, Changjun; Cao, Liang; Xie, Hong; Zhuo, Xiangyu

2013-10-01

Higher quality surface information would be got when data from optical images and LiDAR were integrated, owing to the fact that optical images and LiDAR point cloud have unique characteristics that make them preferable in many applications. While most previous works focus on registration of pinhole perspective cameras to 2D or 3D LiDAR data. In this paper, a method for the registration of vehicle based panoramic image and LiDAR point cloud is proposed. Using the translation among panoramic image, single CCD image, laser scanner and Position and Orientation System (POS) along with the GPS/IMU data, precise co-registration between the panoramic image and the LiDAR point cloud in the world system is achieved. Results are presented under a real world data set collected by a new developed Mobile Mapping System (MMS) integrated with a high resolution panoramic camera, two laser scanners and a POS.

Temporal co-registration for TROPOMI cloud clearing

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I. Genkova

2012-03-01

Full Text Available The TROPOspheric Monitoring Instrument (TROPOMI is anticipated to provide high-quality and timely global atmospheric composition information through observations of atmospheric constituents such as ozone, nitrogen dioxide, sulfur dioxide, carbon monoxide, methane, formaldehyde and aerosol properties. The methane and the aerosol retrievals require very precise cloud clearing, which is difficult to achieve at the TROPOMI spatial resolution (7 by 7 km and without thermal IR measurements. The TROPOMI carrier – the Sentinel 5 Precursor (S5P, does not include a cloud imager, thus it is planned to fly the S5P mission in a constellation with an instrument yielding an accurate cloud mask. The cloud imagery data will be provided by the US NPOESS Preparatory Project (NPP mission, which will have the Visible Infrared Imager Radiometer Suite (VIIRS on board (Scalione, 2004. This paper investigates the temporal co-registration requirements for suitable time differences between the VIIRS measurements of clouds and the TROPOMI methane and aerosol measurements, so that the former could be used for cloud clearing. The temporal co-registration is studied using Meteosat Second Generation (MSG Spinning Enhanced Visible and Infrared Imager (SEVIRI data with 15 min temporal resolution (Veefkind, 2008b, and with data from the Geostationary Operational Environmental Satellite – 10 (GOES-10 having 1 min temporal resolution. The aim is to understand and assess the relation between the amount of allowed cloud contamination and the required time difference between the two satellites' overflights. Quantitative analysis shows that a time difference of approximately 5 min is sufficient (in most conditions to use the cloud information from the first instrument for cloud clearing in the retrievals using data from the second instrument. In recent years the A-train constellation demonstrated the benefit of flying satellites in formation. Therefore this study's findings will be

Secure public cloud platform for medical images sharing.

Science.gov (United States)

Pan, Wei; Coatrieux, Gouenou; Bouslimi, Dalel; Prigent, Nicolas

2015-01-01

Cloud computing promises medical imaging services offering large storage and computing capabilities for limited costs. In this data outsourcing framework, one of the greatest issues to deal with is data security. To do so, we propose to secure a public cloud platform devoted to medical image sharing by defining and deploying a security policy so as to control various security mechanisms. This policy stands on a risk assessment we conducted so as to identify security objectives with a special interest for digital content protection. These objectives are addressed by means of different security mechanisms like access and usage control policy, partial-encryption and watermarking.

Preliminary Results from the First Deployment of a Tethered-Balloon Cloud Particle Imager Instrument Package in Arctic Stratus Clouds at Ny-Alesund

Science.gov (United States)

Lawson, P.; Stamnes, K.; Stamnes, J.; Zmarzly, P.; O'Connor, D.; Koskulics, J.; Hamre, B.

2008-12-01

A tethered balloon system specifically designed to collect microphysical data in mixed-phase clouds was deployed in Arctic stratus clouds during May 2008 near Ny-Alesund, Svalbard, at 79 degrees North Latitude. This is the first time a tethered balloon system with a cloud particle imager (CPI) that records high-resolution digital images of cloud drops and ice particles has been operated in cloud. The custom tether supplies electrical power to the instrument package, which in addition to the CPI houses a 4-pi short-wavelength radiometer and a met package that measures temperature, humidity, pressure, GPS position, wind speed and direction. The instrument package was profiled vertically through cloud up to altitudes of 1.6 km. Since power was supplied to the instrument package from the ground, it was possible to keep the balloon package aloft for extended periods of time, up to 9 hours at Ny- Ålesund, which was limited only by crew fatigue. CPI images of cloud drops and the sizes, shapes and degree of riming of ice particles are shown throughout vertical profiles of Arctic stratus clouds. The images show large regions of mixed-phase cloud from -8 to -2 C. The predominant ice crystal habits in these regions are needles and aggregates of needles. The amount of ice in the mixed-phase clouds varied considerably and did not appear to be a function of temperature. On some occasions, ice was observed near cloud base at -2 C with supercooled cloud above to - 8 C that was devoid of ice. Measurements of shortwave radiation are also presented. Correlations between particle distributions and radiative measurements will be analyzed to determine the effect of these Arctic stratus clouds on radiative forcing.

Influence of Ice Cloud Microphysics on Imager-Based Estimates of Earth's Radiation Budget

Science.gov (United States)

Loeb, N. G.; Kato, S.; Minnis, P.; Yang, P.; Sun-Mack, S.; Rose, F. G.; Hong, G.; Ham, S. H.

2016-12-01

A central objective of the Clouds and the Earth's Radiant Energy System (CERES) is to produce a long-term global climate data record of Earth's radiation budget from the TOA down to the surface along with the associated atmospheric and surface properties that influence it. CERES relies on a number of data sources, including broadband radiometers measuring incoming and reflected solar radiation and OLR, high-resolution spectral imagers, meteorological, aerosol and ozone assimilation data, and snow/sea-ice maps based on microwave radiometer data. While the TOA radiation budget is largely determined directly from accurate broadband radiometer measurements, the surface radiation budget is derived indirectly through radiative transfer model calculations initialized using imager-based cloud and aerosol retrievals and meteorological assimilation data. Because ice cloud particles exhibit a wide range of shapes, sizes and habits that cannot be independently retrieved a priori from passive visible/infrared imager measurements, assumptions about the scattering properties of ice clouds are necessary in order to retrieve ice cloud optical properties (e.g., optical depth) from imager radiances and to compute broadband radiative fluxes. This presentation will examine how the choice of an ice cloud particle model impacts computed shortwave (SW) radiative fluxes at the top-of-atmosphere (TOA) and surface. The ice cloud particle models considered correspond to those from prior, current and future CERES data product versions. During the CERES Edition2 (and Edition3) processing, ice cloud particles were assumed to be smooth hexagonal columns. In the Edition4, roughened hexagonal columns are assumed. The CERES team is now working on implementing in a future version an ice cloud particle model comprised of a two-habit ice cloud model consisting of roughened hexagonal columns and aggregates of roughened columnar elements. In each case, we use the same ice particle model in both the

Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series

Science.gov (United States)

Champion, Nicolas

2016-06-01

Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pl

AUTOMATIC DETECTION OF CLOUDS AND SHADOWS USING HIGH RESOLUTION SATELLITE IMAGE TIME SERIES

Directory of Open Access Journals (Sweden)

N. Champion

2016-06-01

Full Text Available Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8

OpenID connect as a security service in Cloud-based diagnostic imaging systems

Science.gov (United States)

Ma, Weina; Sartipi, Kamran; Sharghi, Hassan; Koff, David; Bak, Peter

2015-03-01

The evolution of cloud computing is driving the next generation of diagnostic imaging (DI) systems. Cloud-based DI systems are able to deliver better services to patients without constraining to their own physical facilities. However, privacy and security concerns have been consistently regarded as the major obstacle for adoption of cloud computing by healthcare domains. Furthermore, traditional computing models and interfaces employed by DI systems are not ready for accessing diagnostic images through mobile devices. RESTful is an ideal technology for provisioning both mobile services and cloud computing. OpenID Connect, combining OpenID and OAuth together, is an emerging REST-based federated identity solution. It is one of the most perspective open standards to potentially become the de-facto standard for securing cloud computing and mobile applications, which has ever been regarded as "Kerberos of Cloud". We introduce OpenID Connect as an identity and authentication service in cloud-based DI systems and propose enhancements that allow for incorporating this technology within distributed enterprise environment. The objective of this study is to offer solutions for secure radiology image sharing among DI-r (Diagnostic Imaging Repository) and heterogeneous PACS (Picture Archiving and Communication Systems) as well as mobile clients in the cloud ecosystem. Through using OpenID Connect as an open-source identity and authentication service, deploying DI-r and PACS to private or community clouds should obtain equivalent security level to traditional computing model.

OpenID Connect as a security service in cloud-based medical imaging systems.

Science.gov (United States)

Ma, Weina; Sartipi, Kamran; Sharghigoorabi, Hassan; Koff, David; Bak, Peter

2016-04-01

The evolution of cloud computing is driving the next generation of medical imaging systems. However, privacy and security concerns have been consistently regarded as the major obstacles for adoption of cloud computing by healthcare domains. OpenID Connect, combining OpenID and OAuth together, is an emerging representational state transfer-based federated identity solution. It is one of the most adopted open standards to potentially become the de facto standard for securing cloud computing and mobile applications, which is also regarded as "Kerberos of cloud." We introduce OpenID Connect as an authentication and authorization service in cloud-based diagnostic imaging (DI) systems, and propose enhancements that allow for incorporating this technology within distributed enterprise environments. The objective of this study is to offer solutions for secure sharing of medical images among diagnostic imaging repository (DI-r) and heterogeneous picture archiving and communication systems (PACS) as well as Web-based and mobile clients in the cloud ecosystem. The main objective is to use OpenID Connect open-source single sign-on and authorization service and in a user-centric manner, while deploying DI-r and PACS to private or community clouds should provide equivalent security levels to traditional computing model.

A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors

Science.gov (United States)

Sedano, Fernando; Kempeneers, Pieter; Strobl, Peter; Kucera, Jan; Vogt, Peter; Seebach, Lucia; San-Miguel-Ayanz, Jesús

2011-09-01

This study presents a novel cloud masking approach for high resolution remote sensing images in the context of land cover mapping. As an advantage to traditional methods, the approach does not rely on thermal bands and it is applicable to images from most high resolution earth observation remote sensing sensors. The methodology couples pixel-based seed identification and object-based region growing. The seed identification stage relies on pixel value comparison between high resolution images and cloud free composites at lower spatial resolution from almost simultaneously acquired dates. The methodology was tested taking SPOT4-HRVIR, SPOT5-HRG and IRS-LISS III as high resolution images and cloud free MODIS composites as reference images. The selected scenes included a wide range of cloud types and surface features. The resulting cloud masks were evaluated through visual comparison. They were also compared with ad-hoc independently generated cloud masks and with the automatic cloud cover assessment algorithm (ACCA). In general the results showed an agreement in detected clouds higher than 95% for clouds larger than 50 ha. The approach produced consistent results identifying and mapping clouds of different type and size over various land surfaces including natural vegetation, agriculture land, built-up areas, water bodies and snow.

Auto-Scaling of Geo-Based Image Processing in an OpenStack Cloud Computing Environment

Directory of Open Access Journals (Sweden)

Sanggoo Kang

2016-08-01

Full Text Available Cloud computing is a base platform for the distribution of large volumes of data and high-performance image processing on the Web. Despite wide applications in Web-based services and their many benefits, geo-spatial applications based on cloud computing technology are still developing. Auto-scaling realizes automatic scalability, i.e., the scale-out and scale-in processing of virtual servers in a cloud computing environment. This study investigates the applicability of auto-scaling to geo-based image processing algorithms by comparing the performance of a single virtual server and multiple auto-scaled virtual servers under identical experimental conditions. In this study, the cloud computing environment is built with OpenStack, and four algorithms from the Orfeo toolbox are used for practical geo-based image processing experiments. The auto-scaling results from all experimental performance tests demonstrate applicable significance with respect to cloud utilization concerning response time. Auto-scaling contributes to the development of web-based satellite image application services using cloud-based technologies.

Leveraging the Cloud for Robust and Efficient Lunar Image Processing

Science.gov (United States)

Chang, George; Malhotra, Shan; Wolgast, Paul

2011-01-01

The Lunar Mapping and Modeling Project (LMMP) is tasked to aggregate lunar data, from the Apollo era to the latest instruments on the LRO spacecraft, into a central repository accessible by scientists and the general public. A critical function of this task is to provide users with the best solution for browsing the vast amounts of imagery available. The image files LMMP manages range from a few gigabytes to hundreds of gigabytes in size with new data arriving every day. Despite this ever-increasing amount of data, LMMP must make the data readily available in a timely manner for users to view and analyze. This is accomplished by tiling large images into smaller images using Hadoop, a distributed computing software platform implementation of the MapReduce framework, running on a small cluster of machines locally. Additionally, the software is implemented to use Amazon's Elastic Compute Cloud (EC2) facility. We also developed a hybrid solution to serve images to users by leveraging cloud storage using Amazon's Simple Storage Service (S3) for public data while keeping private information on our own data servers. By using Cloud Computing, we improve upon our local solution by reducing the need to manage our own hardware and computing infrastructure, thereby reducing costs. Further, by using a hybrid of local and cloud storage, we are able to provide data to our users more efficiently and securely. 12 This paper examines the use of a distributed approach with Hadoop to tile images, an approach that provides significant improvements in image processing time, from hours to minutes. This paper describes the constraints imposed on the solution and the resulting techniques developed for the hybrid solution of a customized Hadoop infrastructure over local and cloud resources in managing this ever-growing data set. It examines the performance trade-offs of using the more plentiful resources of the cloud, such as those provided by S3, against the bandwidth limitations such use

Cloud-based processing of multi-spectral imaging data

Science.gov (United States)

Bernat, Amir S.; Bolton, Frank J.; Weiser, Reuven; Levitz, David

2017-03-01

Multispectral imaging holds great promise as a non-contact tool for the assessment of tissue composition. Performing multi - spectral imaging on a hand held mobile device would allow to bring this technology and with it knowledge to low resource settings to provide a state of the art classification of tissue health. This modality however produces considerably larger data sets than white light imaging and requires preliminary image analysis for it to be used. The data then needs to be analyzed and logged, while not requiring too much of the system resource or a long computation time and battery use by the end point device. Cloud environments were designed to allow offloading of those problems by allowing end point devices (smartphones) to offload computationally hard tasks. For this end we present a method where the a hand held device based around a smartphone captures a multi - spectral dataset in a movie file format (mp4) and compare it to other image format in size, noise and correctness. We present the cloud configuration used for segmenting images to frames where they can later be used for further analysis.

Results from the Two-Year Infrared Cloud Imager Deployment at ARM's NSA Observatory in Barrow, Alaska

Science.gov (United States)

Shaw, J. A.; Nugent, P. W.

2016-12-01

Ground-based longwave-infrared (LWIR) cloud imaging can provide continuous cloud measurements in the Arctic. This is of particular importance during the Arctic winter when visible wavelength cloud imaging systems cannot operate. This method uses a thermal infrared camera to observe clouds and produce measurements of cloud amount and cloud optical depth. The Montana State University Optical Remote Sensor Laboratory deployed an infrared cloud imager (ICI) at the Atmospheric Radiation Monitoring North Slope of Alaska site at Barrow, AK from July 2012 through July 2014. This study was used to both understand the long-term operation of an ICI in the Arctic and to study the consistency of the ICI data products in relation to co-located active and passive sensors. The ICI was found to have a high correlation (> 0.92) with collocated cloud instruments and to produce an unbiased data product. However, the ICI also detects thin clouds that are not detected by most operational cloud sensors. Comparisons with high-sensitivity actively sensed cloud products confirm the existence of these thin clouds. Infrared cloud imaging systems can serve a critical role in developing our understanding of cloud cover in the Arctic by provided a continuous annual measurement of clouds at sites of interest.

Automatic registration of terrestrial point cloud using panoramic reflectance images

NARCIS (Netherlands)

Kang, Z.

2008-01-01

Much attention is paid to registration of terrestrial point clouds nowadays. Research is carried out towards improved efficiency and automation of the registration process. This paper reports a new approach for point clouds registration utilizing reflectance panoramic images. The approach follows a

Low level cloud motion vectors from Kalpana-1 visible images

Indian Academy of Sciences (India)

. In this paper, an attempt has been made to retrieve low-level cloud motion vectors using Kalpana-1 visible (VIS) images at every half an hour. The VIS channel provides better detection of low level clouds, which remain obscure in thermal IR ...

Atmospheric Profiles, Clouds and the Evolution of Sea Ice Cover in the Beaufort and Chukchi Seas

Science.gov (United States)

2014-09-30

developed by incorporating the proposed IR sensors and ground-sky temperature difference algorithm into a tethered balloon borne payload (Figure 3...into the cloud base. RESULTS FROM FY 2014 • A second flight of the tethered balloon -borne IR cloud margin sensor was conducted in Colorado on...Figure 3: Tethered balloon -borne IR sensing payload IR Cloud Margin Sensor Figure 4: First successful flight validation of the IR cloud

Cloud Image Data Center for Healthcare Network in Taiwan.

Science.gov (United States)

Weng, Shao-Jen; Lai, Lai-Shiun; Gotcher, Donald; Wu, Hsin-Hung; Xu, Yeong-Yuh; Yang, Ching-Wen

2016-04-01

This paper investigates how a healthcare network in Taiwan uses a practical cloud image data center (CIDC) to communicate with its constituent hospital branches. A case study approach was used. The study was carried out in the central region of Taiwan, with four hospitals belonging to the Veterans Hospital healthcare network. The CIDC provides synchronous and asynchronous consultation among these branches. It provides storage, platforms, and services on demand to the hospitals. Any branch-client can pull up the patient's medical images from any hospital off this cloud. Patients can be examined at the branches, and the images and reports can be further evaluated by physicians in the main Taichung Veterans General Hospital (TVGH) to enhance the usage and efficiency of equipment in the various branches, thereby shortening the waiting time of patients. The performance of the CIDC over 5 years shows: (1) the total number of cross-hospital images accessed with CDC in the branches was 132,712; and (2) TVGH assisted the branches in keying in image reports using the CIDC 4,424 times; and (3) Implementation of the system has improved management, efficiency, speed and quality of care. Therefore, the results lead to the recommendation of continuing and expanding the cloud computing architecture to improve information sharing among branches in the healthcare network.

Small Galactic H II regions. II. The molecular clouds and star formation

International Nuclear Information System (INIS)

Hunter, D.A.; Thronson, H.A. Jr.; Wilton, C.

1990-01-01

CO maps of molecular clouds associated with 11 small Galactic H II regions are presented and compared with IR images obtained by IRAS. The molecular masses of the clouds are computed and compared with the masses of the stellar content. The mapped clouds have masses of 1000-60,000 solar and are typical of the more numerous, smaller Galactic molecular clouds. All of the clouds have recently made massive OB stars, and many have complex spatial and kinematic structures. The coincidence of IRAS sources and CO peaks suggests that many of the clouds have sites of star formation other than the optically visible H II region. Star-formation efficiencies are uncertain, with values for the clouds ranging from 0.02 to 0.6 with an average value of 0.2. There is no trend of the upper stellar mass limit with Galactic radius and with molecular cloud mass. 53 refs

The Use of the Deep Convective Cloud Technique (DCCT) to Monitor On-Orbit Performance of the Geostationary Lightning Mapper (GLM): Use of Lightning Imaging Sensor (LIS) Data as Proxy

Science.gov (United States)

Buechler, Dennis E.; Christian, H. J.; Koshak, William J.; Goodman, Steve J.

2013-01-01

The Geostationary Lightning Mapper (GLM) on the next generation Geostationary Operational Environmental Satellite-R (GOES-R) will not have onboard calibration capability to monitor its performance. The Lightning Imaging Sensor (LIS) onboard the Tropical Rainfall Measuring Mission (TRMM) satellite has been providing observations of total lightning over the Earth's Tropics since 1997. The GLM design is based on LIS heritage, making it a good proxy dataset. This study examines the performance of LIS throughout its time in orbit. This was accomplished through application of the Deep Convective Cloud Technique (DCCT) (Doelling et al., 2004) to LIS background pixel radiance data. The DCCT identifies deep convective clouds by their cold Infrared (IR) brightness temperatures and using them as invariant targets in the solar reflective portion of the solar spectrum. The GLM and LIS operate in the near-IR at a wavelength of 777.4 nm. In the present study the IR data is obtained from the Visible Infrared Sensor (VIRS) which is collocated with LIS onboard the Tropical Rainfall Measuring Mission (TRMM) satellite. The DCCT is applied to LIS observations for July and August of each year from 1998-2010. The resulting distributions of LIS background DCC pixel radiance for each July August are very similar, indicating stable performance. The mean radiance of the DCCT analysis does not show a long term trend and the maximum deviation of the July August mean radiance for each year is within 0.7% of the overall mean. These results demonstrate that there has been no discernible change in LIS performance throughout its lifetime. A similar approach will used for monitoring the performance of GLM, with cold clouds identified using IR data from the Advanced Baseline Imager (ABI) which will also be located on GOES-R. Since GLM is based on LIS design heritage, the LIS results indicate that GLM should also experience stable performance over its lifetime.

Virtual Machine Images Management in Cloud Environments

CERN Multimedia

CERN. Geneva

2017-01-01

Nowadays, the demand for scalability in distributed systems has led a design philosophy in which virtual resources need to be configured in a flexible way to provide services to a large number of users. The configuration and management of such an architecture is challenging (e.g.: 100,000 compute cores on the private cloud together with thousands of cores on external cloud resources). There is the need to process CPU intensive work whilst ensuring that the resources are shared fairly between different users of the system, and guarantee that all nodes are up to date with new images containing the latest software configurations. Different types of automated systems can be used to facilitate the orchestration. CERN’s current system, composed of different technologies such as OpenStack, Packer, Puppet, Rundeck and Docker will be introduced and explained, together with the process used to create new Virtual Machines images at CERN.

12MAP: Cloud Disaster Recovery Based on Image-Instance Mapping

OpenAIRE

Nadgowda , Shripad; Jayachandran , Praveen; Verma , Akshat

2013-01-01

Part 2: Cloud Computing; International audience; Virtual machines (VMs) in a cloud use standardized ‘golden master’ images, standard software catalog and management tools. This facilitates quick provisioning of VMs and helps reduce the cost of managing the cloud by reducing the need for specialized software skills. However, knowledge of this similarity is lost post-provisioning, as VMs could experience different changes and may drift away from one another. In this work, we propose the 12MAP s...

Monitoring combat wound healing by IR hyperspectral imaging

Science.gov (United States)

Howle, Chris R.; Spear, Abigail M.; Gazi, Ehsan; Crane, Nicole J.

2016-03-01

In recent conflicts, battlefield injuries consist largely of extensive soft injuries from blasts and high energy projectiles, including gunshot wounds. Repair of these large, traumatic wounds requires aggressive surgical treatment, including multiple surgical debridements to remove devitalised tissue and to reduce bacterial load. Identifying those patients with wound complications, such as infection and impaired healing, could greatly assist health care teams in providing the most appropriate and personalised care for combat casualties. Candidate technologies to enable this benefit include the fusion of imaging and optical spectroscopy to enable rapid identification of key markers. Hence, a novel system based on IR negative contrast imaging (NCI) is presented that employs an optical parametric oscillator (OPO) source comprising a periodically-poled LiNbO3 (PPLN) crystal. The crystal operates in the shortwave and midwave IR spectral regions (ca. 1.5 - 1.9 μm and 2.4 - 3.8 μm, respectively). Wavelength tuning is achieved by translating the crystal within the pump beam. System size and complexity are minimised by the use of single element detectors and the intracavity OPO design. Images are composed by raster scanning the monochromatic beam over the scene of interest; the reflection and/or absorption of the incident radiation by target materials and their surrounding environment provide a method for spatial location. Initial results using the NCI system to characterise wound biopsies are presented here.

Cloud solution for histopathological image analysis using region of interest based compression.

Science.gov (United States)

Kanakatte, Aparna; Subramanya, Rakshith; Delampady, Ashik; Nayak, Rajarama; Purushothaman, Balamuralidhar; Gubbi, Jayavardhana

2017-07-01

Recent technological gains have led to the adoption of innovative cloud based solutions in medical imaging field. Once the medical image is acquired, it can be viewed, modified, annotated and shared on many devices. This advancement is mainly due to the introduction of Cloud computing in medical domain. Tissue pathology images are complex and are normally collected at different focal lengths using a microscope. The single whole slide image contains many multi resolution images stored in a pyramidal structure with the highest resolution image at the base and the smallest thumbnail image at the top of the pyramid. Highest resolution image will be used for tissue pathology diagnosis and analysis. Transferring and storing such huge images is a big challenge. Compression is a very useful and effective technique to reduce the size of these images. As pathology images are used for diagnosis, no information can be lost during compression (lossless compression). A novel method of extracting the tissue region and applying lossless compression on this region and lossy compression on the empty regions has been proposed in this paper. The resulting compression ratio along with lossless compression on tissue region is in acceptable range allowing efficient storage and transmission to and from the Cloud.

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

Directory of Open Access Journals (Sweden)

Dominik Wojciech

2017-04-01

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

Infrared reflection nebulae in Orion Molecular Cloud

International Nuclear Information System (INIS)

Pendleton, Y.; Werner, M.W.; Capps, R.; Lester, D.; Hawaii Univ., Honolulu; Texas Univ., Austin)

1986-01-01

New observations of Orion Molecular Cloud 2 have been made from 1 to 100 microns using the NASA Infrared Telescope Facility and the Kuiper Airborne Observatory. An extensive program of polarimetry, photometry, and spectrophotometry has shown that the extended emission regions associated with two of the previously known near-infrared sources, IRS 1 and IRS 4, are infrared reflection nebulae, and that the compact sources IRS 1 and IRS 4 are the main luminosity sources in the cloud. The constraints from the far-infrared observations and an analysis of the scattered light from the IRS 1 nebula show that OMC-2/IRS 1 can be characterized by L of 500 solar luminosities or less and T of roughly 1000 K. The near-infrared albedo of the grains in the IRS 1 nebula is greater than 0.08. 27 references

Investigation into Cloud Computing for More Robust Automated Bulk Image Geoprocessing

Science.gov (United States)

Brown, Richard B.; Smoot, James C.; Underwood, Lauren; Armstrong, C. Duane

2012-01-01

Geospatial resource assessments frequently require timely geospatial data processing that involves large multivariate remote sensing data sets. In particular, for disasters, response requires rapid access to large data volumes, substantial storage space and high performance processing capability. The processing and distribution of this data into usable information products requires a processing pipeline that can efficiently manage the required storage, computing utilities, and data handling requirements. In recent years, with the availability of cloud computing technology, cloud processing platforms have made available a powerful new computing infrastructure resource that can meet this need. To assess the utility of this resource, this project investigates cloud computing platforms for bulk, automated geoprocessing capabilities with respect to data handling and application development requirements. This presentation is of work being conducted by Applied Sciences Program Office at NASA-Stennis Space Center. A prototypical set of image manipulation and transformation processes that incorporate sample Unmanned Airborne System data were developed to create value-added products and tested for implementation on the "cloud". This project outlines the steps involved in creating and testing of open source software developed process code on a local prototype platform, and then transitioning this code with associated environment requirements into an analogous, but memory and processor enhanced cloud platform. A data processing cloud was used to store both standard digital camera panchromatic and multi-band image data, which were subsequently subjected to standard image processing functions such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), band stacking, reprojection, and other similar type data processes. Cloud infrastructure service providers were evaluated by taking these locally tested processing functions, and then

Evaluating the impact of aerosol particles above cloud on cloud optical depth retrievals from MODIS

Science.gov (United States)

Alfaro-Contreras, Ricardo; Zhang, Jianglong; Campbell, James R.; Holz, Robert E.; Reid, Jeffrey S.

2014-05-01

Using two different operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical depth (COD) retrievals (0.86 versus 1.6 µm), we evaluate the impact of above-cloud smoke aerosol particles on near-IR (0.86 µm) COD retrievals. Aerosol Index (AI) from the collocated Ozone Monitoring Instrument (OMI) are used to identify above-cloud aerosol particle loading over the southern Atlantic Ocean, including both smoke and dust from the African subcontinent. Collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation data constrain cloud phase and provide contextual above-cloud aerosol optical depth. The frequency of occurrence of above-cloud aerosol events is depicted on a global scale for the spring and summer seasons from OMI and Cloud Aerosol Lidar with Orthogonal Polarization. Seasonal frequencies for smoke-over-cloud off the southwestern Africa coastline reach 20-50% in boreal summer. We find a corresponding low COD bias of 10-20% for standard MODIS COD retrievals when averaged OMI AI are larger than 1. No such bias is found over the Saharan dust outflow region off northern Africa, since both MODIS 0.86 and 1.6 µm channels are vulnerable to radiance attenuation due to dust particles. A similar result is found for a smaller domain, in the Gulf of Tonkin region, from smoke advection over marine stratocumulus clouds and outflow into the northern South China Sea in spring. This study shows the necessity of accounting for the above-cloud aerosol events for future studies using standard MODIS cloud products in biomass burning outflow regions, through the use of collocated OMI AI and supplementary MODIS 1.6 µm COD products.

CubeSat Constellation Cloud Winds(C3Winds) A New Wind Observing System to Study Mesoscale Cloud Dynamics and Processes

Science.gov (United States)

Wu, D. L.; Kelly, M.A.; Yee, J.-H.; Boldt, J.; Demajistre, R.; Reynolds, E. L.; Tripoli, G. J.; Oman, L. D.; Prive, N.; Heidinger, A. K.;

Cloud Classification in Wide-Swath Passive Sensor Images Aided by Narrow-Swath Active Sensor Data

Directory of Open Access Journals (Sweden)

Hongxia Wang

2018-05-01

Full Text Available It is a challenge to distinguish between different cloud types because of the complexity and diversity of cloud coverage, which is a significant clutter source that impacts on target detection and identification from the images of space-based infrared sensors. In this paper, a novel strategy for cloud classification in wide-swath passive sensor images is developed, which is aided by narrow-swath active sensor data. The strategy consists of three steps, that is, the orbit registration, most matching donor pixel selection, and cloud type assignment for each recipient pixel. A new criterion for orbit registration is proposed so as to improve the matching accuracy. The most matching donor pixel is selected via the Euclidean distance and the square sum of the radiance relative differences between the recipient and the potential donor pixels. Each recipient pixel is then assigned a cloud type that corresponds to the most matching donor. The cloud classification of the Moderate Resolution Imaging Spectroradiometer (MODIS images is performed with the aid of the data from Cloud Profiling Radar (CPR. The results are compared with the CloudSat product 2B-CLDCLASS, as well as those that are obtained using the method of the International Satellite Cloud Climatology Project (ISCCP, which demonstrates the superior classification performance of the proposed strategy.

An Improved Cloud Classification Algorithm for China's FY-2C Multi-Channel Images Using Artificial Neural Network.

Science.gov (United States)

Liu, Yu; Xia, Jun; Shi, Chun-Xiang; Hong, Yang

2009-01-01

The crowning objective of this research was to identify a better cloud classification method to upgrade the current window-based clustering algorithm used operationally for China's first operational geostationary meteorological satellite FengYun-2C (FY-2C) data. First, the capabilities of six widely-used Artificial Neural Network (ANN) methods are analyzed, together with the comparison of two other methods: Principal Component Analysis (PCA) and a Support Vector Machine (SVM), using 2864 cloud samples manually collected by meteorologists in June, July, and August in 2007 from three FY-2C channel (IR1, 10.3-11.3 μm; IR2, 11.5-12.5 μm and WV 6.3-7.6 μm) imagery. The result shows that: (1) ANN approaches, in general, outperformed the PCA and the SVM given sufficient training samples and (2) among the six ANN networks, higher cloud classification accuracy was obtained with the Self-Organizing Map (SOM) and Probabilistic Neural Network (PNN). Second, to compare the ANN methods to the present FY-2C operational algorithm, this study implemented SOM, one of the best ANN network identified from this study, as an automated cloud classification system for the FY-2C multi-channel data. It shows that SOM method has improved the results greatly not only in pixel-level accuracy but also in cloud patch-level classification by more accurately identifying cloud types such as cumulonimbus, cirrus and clouds in high latitude. Findings of this study suggest that the ANN-based classifiers, in particular the SOM, can be potentially used as an improved Automated Cloud Classification Algorithm to upgrade the current window-based clustering method for the FY-2C operational products.

A Classification-oriented Method of Feature Image Generation for Vehicle-borne Laser Scanning Point Clouds

Directory of Open Access Journals (Sweden)

YANG Bisheng

2016-02-01

Full Text Available An efficient method of feature image generation of point clouds to automatically classify dense point clouds into different categories is proposed, such as terrain points, building points. The method first uses planar projection to sort points into different grids, then calculates the weights and feature values of grids according to the distribution of laser scanning points, and finally generates the feature image of point clouds. Thus, the proposed method adopts contour extraction and tracing means to extract the boundaries and point clouds of man-made objects (e.g. buildings and trees in 3D based on the image generated. Experiments show that the proposed method provides a promising solution for classifying and extracting man-made objects from vehicle-borne laser scanning point clouds.

An Intelligent Cloud Storage Gateway for Medical Imaging.

Science.gov (United States)

Viana-Ferreira, Carlos; Guerra, António; Silva, João F; Matos, Sérgio; Costa, Carlos

2017-09-01

Historically, medical imaging repositories have been supported by indoor infrastructures. However, the amount of diagnostic imaging procedures has continuously increased over the last decades, imposing several challenges associated with the storage volume, data redundancy and availability. Cloud platforms are focused on delivering hardware and software services over the Internet, becoming an appealing solution for repository outsourcing. Although this option may bring financial and technological benefits, it also presents new challenges. In medical imaging scenarios, communication latency is a critical issue that still hinders the adoption of this paradigm. This paper proposes an intelligent Cloud storage gateway that optimizes data access times. This is achieved through a new cache architecture that combines static rules and pattern recognition for eviction and prefetching. The evaluation results, obtained from experiments over a real-world dataset, show that cache hit ratios can reach around 80%, leading to reductions of image retrieval times by over 60%. The combined use of eviction and prefetching policies proposed can significantly reduce communication latency, even when using a small cache in comparison to the total size of the repository. Apart from the performance gains, the proposed system is capable of adjusting to specific workflows of different institutions.

FT-IR imaging for quantitative determination of liver fat content in non-alcoholic fatty liver.

Science.gov (United States)

Kochan, K; Maslak, E; Chlopicki, S; Baranska, M

2015-08-07

In this work we apply FT-IR imaging of large areas of liver tissue cross-section samples (∼5 cm × 5 cm) for quantitative assessment of steatosis in murine model of Non-Alcoholic Fatty Liver (NAFLD). We quantified the area of liver tissue occupied by lipid droplets (LDs) by FT-IR imaging and Oil Red O (ORO) staining for comparison. Two alternative FT-IR based approaches are presented. The first, straightforward method, was based on average spectra from tissues and provided values of the fat content by using a PLS regression model and the reference method. The second one – the chemometric-based method – enabled us to determine the values of the fat content, independently of the reference method by means of k-means cluster (KMC) analysis. In summary, FT-IR images of large size liver sections may prove to be useful for quantifying liver steatosis without the need of tissue staining.

3D Aerosol-Cloud Radiative Interaction Observed in Collocated MODIS and ASTER Images of Cumulus Cloud Fields

Science.gov (United States)

Wen, Guoyong; Marshak, Alexander; Cahalan, Robert F.; Remer, Lorraine A.; Kleidman, Richard G.

2007-01-01

3D aerosol-cloud interaction is examined by analyzing two images containing cumulus clouds in biomass burning regions in Brazil. The research consists of two parts. The first part focuses on identifying 3D clo ud impacts on the reflectance of pixel selected for the MODIS aerosol retrieval based purely on observations. The second part of the resea rch combines the observations with radiative transfer computations to identify key parameters in 3D aerosol-cloud interaction. We found that 3D cloud-induced enhancement depends on optical properties of nearb y clouds as well as wavelength. The enhancement is too large to be ig nored. Associated biased error in 1D aerosol optical thickness retrie val ranges from 50% to 140% depending on wavelength and optical prope rties of nearby clouds as well as aerosol optical thickness. We caution the community to be prudent when applying 1D approximations in comp uting solar radiation in dear regions adjacent to clouds or when usin g traditional retrieved aerosol optical thickness in aerosol indirect effect research.

AUTOMATIC CLOUD DETECTION FROM MULTI-TEMPORAL SATELLITE IMAGES: TOWARDS THE USE OF PLÉIADES TIME SERIES

Directory of Open Access Journals (Sweden)

N. Champion

2012-08-01

Full Text Available Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images and is based on a region-growing procedure. Seeds (corresponding to clouds are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images. Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011. In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.

A novel technique for extracting clouds base height using ground based imaging

Directory of Open Access Journals (Sweden)

E. Hirsch

2011-01-01

Full Text Available The height of a cloud in the atmospheric column is a key parameter in its characterization. Several remote sensing techniques (passive and active, either ground-based or on space-borne platforms and in-situ measurements are routinely used in order to estimate top and base heights of clouds. In this article we present a novel method that combines thermal imaging from the ground and sounded wind profile in order to derive the cloud base height. This method is independent of cloud types, making it efficient for both low boundary layer and high clouds. In addition, using thermal imaging ensures extraction of clouds' features during daytime as well as at nighttime. The proposed technique was validated by comparison to active sounding by ceilometers (which is a standard ground based method, to lifted condensation level (LCL calculations, and to MODIS products obtained from space. As all passive remote sensing techniques, the proposed method extracts only the height of the lowest cloud layer, thus upper cloud layers are not detected. Nevertheless, the information derived from this method can be complementary to space-borne cloud top measurements when deep-convective clouds are present. Unlike techniques such as LCL, this method is not limited to boundary layer clouds, and can extract the cloud base height at any level, as long as sufficient thermal contrast exists between the radiative temperatures of the cloud and its surrounding air parcel. Another advantage of the proposed method is its simplicity and modest power needs, making it particularly suitable for field measurements and deployment at remote locations. Our method can be further simplified for use with visible CCD or CMOS camera (although nighttime clouds will not be observed.

A Medical Image Backup Architecture Based on a NoSQL Database and Cloud Computing Services.

Science.gov (United States)

Santos Simões de Almeida, Luan Henrique; Costa Oliveira, Marcelo

2015-01-01

The use of digital systems for storing medical images generates a huge volume of data. Digital images are commonly stored and managed on a Picture Archiving and Communication System (PACS), under the DICOM standard. However, PACS is limited because it is strongly dependent on the server's physical space. Alternatively, Cloud Computing arises as an extensive, low cost, and reconfigurable resource. However, medical images contain patient information that can not be made available in a public cloud. Therefore, a mechanism to anonymize these images is needed. This poster presents a solution for this issue by taking digital images from PACS, converting the information contained in each image file to a NoSQL database, and using cloud computing to store digital images.

Venus: cloud level circulation during 1982 as determined from Pioneer cloud photopolarimeter images. 11. Solar longitude dependent circulation

International Nuclear Information System (INIS)

Limaye, S.S.

1988-01-01

Pioneer Venus Orbiter images obtained in 1982 indicate a marked solar-locked dependence of cloud level circulation in both averaged cloud motions and cloud layer UV reflectivity. An apparent relationship is noted between horizontal divergence and UV reflectivity: the highest reflectivities are associated with regions of convergence at high latitudes, while lower values are associated with equatorial latitude regions where the motions are divergent. In solar-locked coordinates, the rms deviation of normalized UV brightness is higher at 45-deg latitudes than in equatorial regions. 37 references

Testing a polarimetric cloud imager aboard research vessel Polarstern: comparison of color-based and polarimetric cloud detection algorithms.

Science.gov (United States)

Barta, András; Horváth, Gábor; Horváth, Ákos; Egri, Ádám; Blahó, Miklós; Barta, Pál; Bumke, Karl; Macke, Andreas

2015-02-10

Cloud cover estimation is an important part of routine meteorological observations. Cloudiness measurements are used in climate model evaluation, nowcasting solar radiation, parameterizing the fluctuations of sea surface insolation, and building energy transfer models of the atmosphere. Currently, the most widespread ground-based method to measure cloudiness is based on analyzing the unpolarized intensity and color distribution of the sky obtained by digital cameras. As a new approach, we propose that cloud detection can be aided by the additional use of skylight polarization measured by 180° field-of-view imaging polarimetry. In the fall of 2010, we tested such a novel polarimetric cloud detector aboard the research vessel Polarstern during expedition ANT-XXVII/1. One of our goals was to test the durability of the measurement hardware under the extreme conditions of a trans-Atlantic cruise. Here, we describe the instrument and compare the results of several different cloud detection algorithms, some conventional and some newly developed. We also discuss the weaknesses of our design and its possible improvements. The comparison with cloud detection algorithms developed for traditional nonpolarimetric full-sky imagers allowed us to evaluate the added value of polarimetric quantities. We found that (1) neural-network-based algorithms perform the best among the investigated schemes and (2) global information (the mean and variance of intensity), nonoptical information (e.g., sun-view geometry), and polarimetric information (e.g., the degree of polarization) improve the accuracy of cloud detection, albeit slightly.

Cloud cover detection combining high dynamic range sky images and ceilometer measurements

Science.gov (United States)

Román, R.; Cazorla, A.; Toledano, C.; Olmo, F. J.; Cachorro, V. E.; de Frutos, A.; Alados-Arboledas, L.

2017-11-01

This paper presents a new algorithm for cloud detection based on high dynamic range images from a sky camera and ceilometer measurements. The algorithm is also able to detect the obstruction of the sun. This algorithm, called CPC (Camera Plus Ceilometer), is based on the assumption that under cloud-free conditions the sky field must show symmetry. The symmetry criteria are applied depending on ceilometer measurements of the cloud base height. CPC algorithm is applied in two Spanish locations (Granada and Valladolid). The performance of CPC retrieving the sun conditions (obstructed or unobstructed) is analyzed in detail using as reference pyranometer measurements at Granada. CPC retrievals are in agreement with those derived from the reference pyranometer in 85% of the cases (it seems that this agreement does not depend on aerosol size or optical depth). The agreement percentage goes down to only 48% when another algorithm, based on Red-Blue Ratio (RBR), is applied to the sky camera images. The retrieved cloud cover at Granada and Valladolid is compared with that registered by trained meteorological observers. CPC cloud cover is in agreement with the reference showing a slight overestimation and a mean absolute error around 1 okta. A major advantage of the CPC algorithm with respect to the RBR method is that the determined cloud cover is independent of aerosol properties. The RBR algorithm overestimates cloud cover for coarse aerosols and high loads. Cloud cover obtained only from ceilometer shows similar results than CPC algorithm; but the horizontal distribution cannot be obtained. In addition, it has been observed that under quick and strong changes on cloud cover ceilometers retrieve a cloud cover fitting worse with the real cloud cover.

An Improved Cloud Classification Algorithm for China’s FY-2C Multi-Channel Images Using Artificial Neural Network

Directory of Open Access Journals (Sweden)

Chun-Xiang Shi

2009-07-01

Full Text Available The crowning objective of this research was to identify a better cloud classification method to upgrade the current window-based clustering algorithm used operationally for China’s first operational geostationary meteorological satellite FengYun-2C (FY-2C data. First, the capabilities of six widely-used Artificial Neural Network (ANN methods are analyzed, together with the comparison of two other methods: Principal Component Analysis (PCA and a Support Vector Machine (SVM, using 2864 cloud samples manually collected by meteorologists in June, July, and August in 2007 from three FY-2C channel (IR1, 10.3-11.3 μm; IR2, 11.5-12.5 μm and WV 6.3-7.6 μm imagery. The result shows that: (1 ANN approaches, in general, outperformed the PCA and the SVM given sufficient training samples and (2 among the six ANN networks, higher cloud classification accuracy was obtained with the Self-Organizing Map (SOM and Probabilistic Neural Network (PNN. Second, to compare the ANN methods to the present FY-2C operational algorithm, this study implemented SOM, one of the best ANN network identified from this study, as an automated cloud classification system for the FY-2C multi-channel data. It shows that SOM method has improved the results greatly not only in pixel-level accuracy but also in cloud patch-level classification by more accurately identifying cloud types such as cumulonimbus, cirrus and clouds in high latitude. Findings of this study suggest that the ANN-based classifiers, in particular the SOM, can be potentially used as an improved Automated Cloud Classification Algorithm to upgrade the current window-based clustering method for the FY-2C operational products.

University of California, San Diego (UCSD) Sky Imager Cloud Position Study Field Campaign Report

Energy Technology Data Exchange (ETDEWEB)

Kleissl, J. [Univ. of California, San Diego, CA (United States); Urquhart, B. [Univ. of California, San Diego, CA (United States); Ghonima, M. [Univ. of California, San Diego, CA (United States); Dahlin, E. [Univ. of California, San Diego, CA (United States); Nguyen, A. [Univ. of California, San Diego, CA (United States); Kurtz, B. [Univ. of California, San Diego, CA (United States); Chow, C. W. [Univ. of California, San Diego, CA (United States); Mejia, F. A. [Univ. of California, San Diego, CA (United States)

2016-04-01

During the University of California, San Diego (UCSD) Sky Imager Cloud Position Study, two University of California, San Diego Sky Imagers (USI) (Figure 1) were deployed the U.S. Department of Energy(DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility Southern Great Plains SGP) research facility. The UCSD Sky Imagers were placed 1.7 km apart to allow for stereographic determination of the cloud height for clouds over approximately 1.5 km. Images with a 180-degree field of view were captured from both systems during daylight hours every 30 seconds beginning on March 11, 2013 and ending on November 4, 2013. The spatial resolution of the images was 1,748 × 1,748, and the intensity resolution was 16 bits using a high-dynamic-range capture process. The cameras use a fisheye lens, so the images are distorted following an equisolid angle projection.

Mid-infrared multi-wavelength imaging of Ophiuchus IRS 48 transitional disk†

Science.gov (United States)

Honda, Mitsuhiko; Okada, Kazushi; Miyata, Takashi; Mulders, Gijs D.; Swearingen, Jeremy R.; Kamizuka, Takashi; Ohsawa, Ryou; Fujiyoshi, Takuya; Fujiwara, Hideaki; Uchiyama, Mizuho; Yamashita, Takuya; Onaka, Takashi

2018-04-01

Transitional disks around the Herbig Ae/Be stars are fascinating targets in the contexts of disk evolution and planet formation. Oph IRS 48 is one of such Herbig Ae stars, which shows an inner dust cavity and azimuthally lopsided large dust distribution. We present new images of Oph IRS 48 at eight mid-infrared (MIR) wavelengths from 8.59 to 24.6 μm taken with COMICS mounted on the 8.2 m Subaru Telescope. The N-band (7 to 13 μm) images show that the flux distribution is centrally peaked with a slight spatial extent, while the Q-band (17 to 25 μm) images show asymmetric double peaks (east and west). Using 18.8- and 24.6 μm images, we derived the dust temperature at both east and west peaks to be 135 ± 22 K. Thus, the asymmetry may not be attributed to a difference in the temperature. Comparing our results with previous modeling works, we conclude that the inner disk is aligned to the outer disk. A shadow cast by the optically thick inner disk has a great influence on the morphology of MIR thermal emission from the outer disk.

Mid-infrared multi-wavelength imaging of Ophiuchus IRS 48 transitional disk†

Science.gov (United States)

Honda, Mitsuhiko; Okada, Kazushi; Miyata, Takashi; Mulders, Gijs D.; Swearingen, Jeremy R.; Kamizuka, Takashi; Ohsawa, Ryou; Fujiyoshi, Takuya; Fujiwara, Hideaki; Uchiyama, Mizuho; Yamashita, Takuya; Onaka, Takashi

2018-06-01

Transitional disks around the Herbig Ae/Be stars are fascinating targets in the contexts of disk evolution and planet formation. Oph IRS 48 is one of such Herbig Ae stars, which shows an inner dust cavity and azimuthally lopsided large dust distribution. We present new images of Oph IRS 48 at eight mid-infrared (MIR) wavelengths from 8.59 to 24.6 μm taken with COMICS mounted on the 8.2 m Subaru Telescope. The N-band (7 to 13 μm) images show that the flux distribution is centrally peaked with a slight spatial extent, while the Q-band (17 to 25 μm) images show asymmetric double peaks (east and west). Using 18.8- and 24.6 μm images, we derived the dust temperature at both east and west peaks to be 135 ± 22 K. Thus, the asymmetry may not be attributed to a difference in the temperature. Comparing our results with previous modeling works, we conclude that the inner disk is aligned to the outer disk. A shadow cast by the optically thick inner disk has a great influence on the morphology of MIR thermal emission from the outer disk.

Creating cloud-free Landsat ETM+ data sets in tropical landscapes: cloud and cloud-shadow removal

Science.gov (United States)

Sebastián Martinuzzi; William A. Gould; Olga M. Ramos Gonzalez

2007-01-01

Clouds and cloud shadows are common features of visible and infrared remotelysensed images collected from many parts of the world, particularly in humid and tropical regions. We have developed a simple and semiautomated method to mask clouds and shadows in Landsat ETM+ imagery, and have developed a recent cloud-free composite of multitemporal images for Puerto Rico and...

Pediatric Trauma Transfer Imaging Inefficiencies-Opportunities for Improvement with Cloud Technology.

Science.gov (United States)

Puckett, Yana; To, Alvin

2016-01-01

This study examines the inefficiencies of radiologic imaging transfers from one hospital to the other during pediatric trauma transfers in an era of cloud based information sharing. Retrospective review of all patients transferred to a pediatric trauma center from 2008-2014 was performed. Imaging was reviewed for whether imaging accompanied the patient, whether imaging was able to be uploaded onto computer for records, whether imaging had to be repeated, and whether imaging obtained at outside hospitals (OSH) was done per universal pediatric trauma guidelines. Of the 1761 patients retrospectively reviewed, 559 met our inclusion criteria. Imaging was sent with the patient 87.7% of the time. Imaging was unable to be uploaded 31.9% of the time. CT imaging had to be repeated 1.8% of the time. CT scan was not done per universal pediatric trauma guidelines 1.2% of the time. Our study demonstrated that current imaging transfer is inefficient, leads to excess ionizing radiation, and increased healthcare costs. Universal implementation of cloud based radiology has the potential to eliminate excess ionizing radiation to children, improve patient care, and save cost to healthcare system.

Pediatric Trauma Transfer Imaging Inefficiencies—Opportunities for Improvement with Cloud Technology

Directory of Open Access Journals (Sweden)

Yana Puckett

2016-02-01

Full Text Available BACKGROUND: This study examines the inefficiencies of radiologic imaging transfers from one hospital to the other during pediatric trauma transfers in an era of cloud based information sharing. METHODS: Retrospective review of all patients transferred to a pediatric trauma center from 2008–2014 was performed. Imaging was reviewed for whether imaging accompanied the patient, whether imaging was able to be uploaded onto computer for records, whether imaging had to be repeated, and whether imaging obtained at outside hospitals (OSH was done per universal pediatric trauma guidelines. RESULTS: Of the 1761 patients retrospectively reviewed, 559 met our inclusion criteria. Imaging was sent with the patient 87.7% of the time. Imaging was unable to be uploaded 31.9% of the time. CT imaging had to be repeated 1.8% of the time. CT scan was not done per universal pediatric trauma guidelines 1.2% of the time. CONCLUSION: Our study demonstrated that current imaging transfer is inefficient, leads to excess ionizing radiation, and increased healthcare costs. Universal implementation of cloud based radiology has the potential to eliminate excess ionizing radiation to children, improve patient care, and save cost to healthcare system.

The relationships between precipitation, convective cloud and tropical cyclone intensity change

Science.gov (United States)

Ruan, Z.; Wu, Q.

2017-12-01

Using 16 years precipitation, brightness temperature (IR BT) data and tropical cyclone (TC) information, this study explores the relationship between precipitation, convective cloud and tropical cyclone (TC) intensity change in the Western North Pacific Ocean. It is found that TC intensity has positive relation with TC precipitation. TC precipitation increases with increased TC intensity. Based on the different phase of diurnal cycle, convective TC clouds were divided into very cold deep convective clouds (IR BTs<208K) and cold high clouds (208K

Innovative monolithic detector for tri-spectral (THz, IR, Vis) imaging

Science.gov (United States)

Pocas, S.; Perenzoni, M.; Massari, N.; Simoens, F.; Meilhan, J.; Rabaud, W.; Martin, S.; Delplanque, B.; Imperinetti, P.; Goudon, V.; Vialle, C.; Arnaud, A.

2012-10-01

Fusion of multispectral images has been explored for many years for security and used in a number of commercial products. CEA-Leti and FBK have developed an innovative sensor technology that gathers monolithically on a unique focal plane arrays, pixels sensitive to radiation in three spectral ranges that are terahertz (THz), infrared (IR) and visible. This technology benefits of many assets for volume market: compactness, full CMOS compatibility on 200mm wafers, advanced functions of the CMOS read-out integrated circuit (ROIC), and operation at room temperature. The ROIC houses visible APS diodes while IR and THz detections are carried out by microbolometers collectively processed above the CMOS substrate. Standard IR bolometric microbridges (160x160 pixels) are surrounding antenna-coupled bolometers (32X32 pixels) built on a resonant cavity customized to THz sensing. This paper presents the different technological challenges achieved in this development and first electrical and sensitivity experimental tests.

Image selection as a service for cloud computing environments

KAUST Repository

Filepp, Robert; Shwartz, Larisa; Ward, Christopher; Kearney, Robert D.; Cheng, Karen; Young, Christopher C.; Ghosheh, Yanal

2010-01-01

Customers of Cloud Services are expected to choose specific machine images to instantiate in order to host their workloads. Unfortunately very little information is provided to the users to enable them to make intelligent choices. We believe

Tidal Distortion of the Envelope of an AGB Star IRS 3 near Sgr A{sup *}

Energy Technology Data Exchange (ETDEWEB)

Yusef-Zadeh, F.; Royster, M. J.; Roberts, D. A. [Department of Physics and Astronomy, Northwestern University, Evanston, IL 60208 (United States); Wardle, M. [Department of Physics and Astronomy and Research Center for Astronomy, Astrophysics and Astrophotonics, Macquarie University, Sydney NSW 2109 (Australia); Cotton, W.; Kunneriath, D. [National Radio Astronomy Observatory, Charlottesville, VA 22903 (United States); Schödel, R. [Instituto de Astfisica de Andalucia (CSIC), Glorieta de la Astronomia S/N, E-18008 Granada (Spain)

2017-03-01

We present radio and millimeter continuum observations of the Galactic center taken with the Very Large Array (VLA) and ALMA at 44 and 226 GHz, respectively. We detect radio and millimeter emission from IRS 3, lying ∼4.″5 NW of Sgr A*, with a spectrum that is consistent with the photospheric emission from an AGB star at the Galactic center. Millimeter images reveal that the envelope of IRS 3, the brightest and most extended 3.8 μ m Galactic center stellar source, consists of two semicircular dust shells facing the direction of Sgr A*. The outer circumstellar shell, at a distance of 1.6 × 10{sup 4} au, appears to break up into “fingers” of dust directed toward Sgr A*. These features coincide with molecular CS (5–4) emission and a near-IR extinction cloud distributed between IRS 3 and Sgr A*. The NE–SW asymmetric shapes of the IRS 3 shells seen at 3.8 μ m and radio are interpreted as structures that are tidally distorted by Sgr A*. Using the kinematics of CS emission and the proper motion of IRS 3, the tidally distorted outflowing material from the envelope after 5000 yr constrains the distance of IRS 3 to ∼0.7 pc in front of or ∼0.5 pc behind Sgr A*. This suggests that the mass loss by stars near Sgr A* can supply a reservoir of molecular material near Sgr A*. We also present dark features in radio continuum images coincident with the envelope of IRS 3. These dusty stars provide examples in which high-resolution radio continuum images can identify dust-enshrouded stellar sources embedded in an ionized medium.

Influence of carbon dioxide clouds on early martian climate.

Science.gov (United States)

Mischna, M A; Kasting, J F; Pavlov, A; Freedman, R

2000-06-01

Recent studies have shown that clouds made of carbon dioxide ice may have warmed the surface of early Mars by reflecting not only incoming solar radiation but upwelling IR radiation as well. However, these studies have not treated scattering self-consistently in the thermal IR. Our own calculations, which treat IR scattering properly, confirm these earlier calculations but show that CO2 clouds can also cool the surface, especially if they are low and optically thick. Estimating the actual effect of CO2 clouds on early martian climate will require three-dimensional models in which cloud location, height, and optical depth, as well as surface temperature and pressure, are determined self-consistently. Our calculations further confirm that CO2 clouds should extend the outer boundary of the habitable zone around a star but that there is still a finite limit beyond which above-freezing surface temperatures cannot be maintained by a CO2-H2O atmosphere. For our own Solar System, the absolute outer edge of the habitable zone is at approximately 2.4 AU.

Wide-band IR imaging in the NIR-MIR-FIR regions for in situ analysis of frescoes

Science.gov (United States)

Daffara, C.; Pezzati, L.; Ambrosini, D.; Paoletti, D.; Di Biase, R.; Mariotti, P. I.; Frosinini, C.

2011-06-01

Imaging methods offer several advantages in the field of conservation allowing to perform non-invasive inspection of works of art. In particular, non-invasive techniques based on imaging in different infrared (IR) regions are widely used for the investigation of paintings. Using radiation beyond the visible range, different characteristics of the inspected artwork may be revealed according to the bandwidth acquired. In this paper we present the recent results of a joint project among the two research institutes DIMEG and CNR-INO, and the restoration facility Opificio delle Pietre Dure, concerning the wide-band integration of IR imaging techniques, in the spectral ranges NIR 0.8-2.5 μm, MIR 3-5 μm, and FIR 8-12 μm, for in situ analysis of artworks. A joint, multi-mode use of reflection and thermal bands is proposed for the diagnostics of mural paintings, and it is demonstrated to be an effective tool in inspecting the layered structure. High resolution IR reflectography and, to a greater extent, IR imaging in the 3-5 μm band, are effectively used to characterize the superficial layer of the fresco and to analyze the stratigraphy of different pictorial layers. IR thermography in the 8-12 μm band is used to characterize the support deep structure. The integration of all the data provides a multi- layered and multi-spectral representation of the fresco that yields a comprehensive analysis.

International inter-rater agreement in scoring acne severity utilizing cloud-based image sharing of mobile phone photographs.

Science.gov (United States)

Foolad, Negar; Ornelas, Jennifer N; Clark, Ashley K; Ali, Ifrah; Sharon, Victoria R; Al Mubarak, Luluah; Lopez, Andrés; Alikhan, Ali; Al Dabagh, Bishr; Firooz, Alireza; Awasthi, Smita; Liu, Yu; Li, Chin-Shang; Sivamani, Raja K

2017-09-01

Cloud-based image sharing technology allows facilitated sharing of images. Cloud-based image sharing technology has not been well-studied for acne assessments or treatment preferences, among international evaluators. We evaluated inter-rater variability of acne grading and treatment recommendations among an international group of dermatologists that assessed photographs. This is a prospective, single visit photographic study to assess inter-rater agreement of acne photographs shared through an integrated mobile device, cloud-based, and HIPAA-compliant platform. Inter-rater agreements for global acne assessment and acne lesion counts were evaluated by the Kendall's coefficient of concordance while correlations between treatment recommendations and acne severity were calculated by Spearman's rank correlation coefficient. There was good agreement for the evaluation of inflammatory lesions (KCC = 0.62, P cloud-based image sharing for acne assessment. Cloud-based sharing may facilitate acne care and research among international collaborators. © 2017 The International Society of Dermatology.

CO-REGISTRATION AIRBORNE LIDAR POINT CLOUD DATA AND SYNCHRONOUS DIGITAL IMAGE REGISTRATION BASED ON COMBINED ADJUSTMENT

Directory of Open Access Journals (Sweden)

Z. H. Yang

2016-06-01

Full Text Available Aim at the problem of co-registration airborne laser point cloud data with the synchronous digital image, this paper proposed a registration method based on combined adjustment. By integrating tie point, point cloud data with elevation constraint pseudo observations, using the principle of least-squares adjustment to solve the corrections of exterior orientation elements of each image, high-precision registration results can be obtained. In order to ensure the reliability of the tie point, and the effectiveness of pseudo observations, this paper proposed a point cloud data constrain SIFT matching and optimizing method, can ensure that the tie points are located on flat terrain area. Experiments with the airborne laser point cloud data and its synchronous digital image, there are about 43 pixels error in image space using the original POS data. If only considering the bore-sight of POS system, there are still 1.3 pixels error in image space. The proposed method regards the corrections of the exterior orientation elements of each image as unknowns and the errors are reduced to 0.15 pixels.

Increasing Security for Cloud Computing By Steganography in Image Edges

Directory of Open Access Journals (Sweden)

Hassan Hadi Saleh

2017-03-01

Full Text Available The security of data storage in “cloud” is big challenge because the data keep within resources that may be accessed by particular machines. The managing of these data and services may not be high reliable. Therefore, the security of data is highly challenging. To increase the security of data in data center of cloud, we have introduced good method to ensure data security in “cloud computing” by methods of data hiding using color images which is called steganography. The fundamental objective of this paper is to prevent "Data Access” by unauthorized or opponent users. This scheme stores data at data centers within edges of color images and retrieves data from it when it is wanted.

Information Recovery Algorithm for Ground Objects in Thin Cloud Images by Fusing Guide Filter and Transfer Learning

Directory of Open Access Journals (Sweden)

HU Gensheng

2018-03-01

Full Text Available Ground object information of remote sensing images covered with thin clouds is obscure. An information recovery algorithm for ground objects in thin cloud images is proposed by fusing guide filter and transfer learning. Firstly, multi-resolution decomposition of thin cloud target images and cloud-free guidance images is performed by using multi-directional nonsubsampled dual-tree complex wavelet transform. Then the decomposed low frequency subbands are processed by using support vector guided filter and transfer learning respectively. The decomposed high frequency subbands are enhanced by using modified Laine enhancement function. The low frequency subbands output by guided filter and those predicted by transfer learning model are fused by the method of selection and weighting based on regional energy. Finally, the enhanced high frequency subbands and the fused low frequency subbands are reconstructed by using inverse multi-directional nonsubsampled dual-tree complex wavelet transform to obtain the ground object information recovery images. Experimental results of Landsat-8 OLI multispectral images show that, support vector guided filter can effectively preserve the detail information of the target images, domain adaptive transfer learning can effectively extend the range of available multi-source and multi-temporal remote sensing images, and good effects for ground object information recover are obtained by fusing guide filter and transfer learning to remove thin cloud on the remote sensing images.

Dense range images from sparse point clouds using multi-scale processing

NARCIS (Netherlands)

Do, Q.L.; Ma, L.; With, de P.H.N.

2013-01-01

Multi-modal data processing based on visual and depth/range images has become relevant in computer vision for 3D reconstruction applications such as city modeling, robot navigation etc. In this paper, we generate highaccuracy dense range images from sparse point clouds to facilitate such

Effects of high altitude clouds on the earth's infrared radiation flux

Science.gov (United States)

Wang, W.-C.; Kaplan, L. D.

1983-01-01

Attention is given to the results of a study of cirrus cloud properties which employed the Goddard Laboratory for Atmospheric Sciences' general circulation model and concentrated on the effects of the nonblackness of high clouds on the IR radiation flux. Although the thermal radiation flux is very sensitive to the treatment of cirrus optical properties in the IR, a more realistic assessment will depend on better parameterizations for cirrus cloud formation, persistence, and dissipation.

EVALUATION OF METHODS FOR COREGISTRATION AND FUSION OF RPAS-BASED 3D POINT CLOUDS AND THERMAL INFRARED IMAGES

Directory of Open Access Journals (Sweden)

L. Hoegner

2016-06-01

Full Text Available This paper discusses the automatic coregistration and fusion of 3d point clouds generated from aerial image sequences and corresponding thermal infrared (TIR images. Both RGB and TIR images have been taken from a RPAS platform with a predefined flight path where every RGB image has a corresponding TIR image taken from the same position and with the same orientation with respect to the accuracy of the RPAS system and the inertial measurement unit. To remove remaining differences in the exterior orientation, different strategies for coregistering RGB and TIR images are discussed: (i coregistration based on 2D line segments for every single TIR image and the corresponding RGB image. This method implies a mainly planar scene to avoid mismatches; (ii coregistration of both the dense 3D point clouds from RGB images and from TIR images by coregistering 2D image projections of both point clouds; (iii coregistration based on 2D line segments in every single TIR image and 3D line segments extracted from intersections of planes fitted in the segmented dense 3D point cloud; (iv coregistration of both the dense 3D point clouds from RGB images and from TIR images using both ICP and an adapted version based on corresponding segmented planes; (v coregistration of both image sets based on point features. The quality is measured by comparing the differences of the back projection of homologous points in both corrected RGB and TIR images.

Assuring virtual network function image integrity and host sealing in telco cloud

NARCIS (Netherlands)

Lal, S.; Ravidas, S.; Oliver, I.; Taleb, T.

In Telco cloud environment, virtual network func- tions (VNFs) can be shipped in the form of virtual machine images and hosted over commodity hardware. It is likely that these VNF images will contain highly sensitive data and mission critical network operations. For this reason, these VNF images are

Estimation of cloud optical thickness by processing SEVIRI images and implementing a semi analytical cloud property retrieval algorithm

Science.gov (United States)

Pandey, P.; De Ridder, K.; van Lipzig, N.

2009-04-01

Clouds play a very important role in the Earth's climate system, as they form an intermediate layer between Sun and the Earth. Satellite remote sensing systems are the only means to provide information about clouds on large scales. The geostationary satellite, Meteosat Second Generation (MSG) has onboard an imaging radiometer, the Spinning Enhanced Visible and Infrared Imager (SEVIRI). SEVIRI is a 12 channel imager, with 11 channels observing the earth's full disk with a temporal resolution of 15 min and spatial resolution of 3 km at nadir, and a high resolution visible (HRV) channel. The visible channels (0.6 µm and 0.81 µm) and near infrared channel (1.6µm) of SEVIRI are being used to retrieve the cloud optical thickness (COT). The study domain is over Europe covering the region between 35°N - 70°N and 10°W - 30°E. SEVIRI level 1.5 images over this domain are being acquired from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) archive. The processing of this imagery, involves a number of steps before estimating the COT. The steps involved in pre-processing are as follows. First, the digital count number is acquired from the imagery. Image geo-coding is performed in order to relate the pixel positions to the corresponding longitude and latitude. Solar zenith angle is determined as a function of latitude and time. The radiometric conversion is done using the values of offsets and slopes of each band. The values of radiance obtained are then used to calculate the reflectance for channels in the visible spectrum using the information of solar zenith angle. An attempt is made to estimate the COT from the observed radiances. A semi analytical algorithm [Kokhanovsky et al., 2003] is implemented for the estimation of cloud optical thickness from the visible spectrum of light intensity reflected from clouds. The asymptotical solution of the radiative transfer equation, for clouds with large optical thickness, is the basis of

Retrieval of subvisual cirrus cloud optical thickness from limb-scatter measurements

Directory of Open Access Journals (Sweden)

J. T. Wiensz

2013-01-01

Full Text Available We present a technique for estimating the optical thickness of subvisual cirrus clouds detected by OSIRIS (Optical Spectrograph and Infrared Imaging System, a limb-viewing satellite instrument that measures scattered radiances from the UV to the near-IR. The measurement set is composed of a ratio of limb radiance profiles at two wavelengths that indicates the presence of cloud-scattering regions. Cross-sections and phase functions from an in situ database are used to simulate scattering by cloud-particles. With appropriate configurations discussed in this paper, the SASKTRAN successive-orders of scatter radiative transfer model is able to simulate accurately the in-cloud radiances from OSIRIS. Configured in this way, the model is used with a multiplicative algebraic reconstruction technique (MART to retrieve the cloud extinction profile for an assumed effective cloud particle size. The sensitivity of these retrievals to key auxiliary model parameters is shown, and it is shown that the retrieved extinction profile, for an assumed effective cloud particle size, models well the measured in-cloud radiances from OSIRIS. The greatest sensitivity of the retrieved optical thickness is to the effective cloud particle size. Since OSIRIS has an 11-yr record of subvisual cirrus cloud detections, the work described in this manuscript provides a very useful method for providing a long-term global record of the properties of these clouds.

Simulation of Thermal Processes in Metamaterial MM-to-IR Converter for MM-wave Imager

International Nuclear Information System (INIS)

Zagubisalo, Peter S; Paulish, Andrey G; Kuznetsov, Sergey A

2014-01-01

The main characteristics of MM-wave image detector were simulated by means of accurate numerical modelling of thermophysical processes in a metamaterial MM-to-IR converter. The converter represents a multilayer structure consisting of an ultra thin resonant metamaterial absorber and a perfect emissive layer. The absorber consists of a dielectric self-supporting film that is metallized from both sides. A micro-pattern is fabricated from one side. Resonant absorption of the MM waves induces the converter heating that yields enhancement of IR emission from the emissive layer. IR emission is detected by IR camera. In this contribution an accurate numerical model for simulation of the thermal processes in the converter structure was created by using COMSOL Multiphysics software. The simulation results are in a good agreement with experimental results that validates the model. The simulation shows that the real time operation is provided for the converter thickness less than 3 micrometers and time response can be improved by decreasing of the converter thickness. The energy conversion efficiency of MM waves into IR radiation is over 80%. The converter temperature increase is a linear function of a MM-wave radiation power within three orders of the dynamic range. The blooming effect and ways of its reducing are also discussed. The model allows us to choose the ways of converter structure optimization and improvement of image detector parameters

Monstrous Ice Cloud System in Titan's Present South Polar Stratosphere

Science.gov (United States)

Anderson, Carrie; Samuelson, Robert; McLain, Jason; Achterberg, Richard; Flasar, F. Michael; Milam, Stefanie

2015-11-01

During southern autumn when sunlight was still available, Cassini's Imaging Science Subsystem discovered a cloud around 300 km near Titan's south pole (West, R. A. et al., AAS/DPS Abstracts, 45, #305.03, 2013); the cloud was later determined by Cassini's Visible and InfraRed Mapping Spectrometer to contain HCN ice (de Kok et al., Nature, 514, pp 65-67, 2014). This cloud has proven to be only the tip of an extensive ice cloud system contained in Titan's south polar stratosphere, as seen through the night-vision goggles of Cassini's Composite InfraRed Spectrometer (CIRS). As the sun sets and the gloom of southern winter approaches, evidence is beginning to accumulate from CIRS far-IR spectra that a massive system of nitrile ice clouds is developing in Titan's south polar stratosphere. Even during the depths of northern winter, nothing like the strength of this southern system was evident in corresponding north polar regions.From the long slant paths that are available from limb-viewing CIRS far-IR spectra, we have the first definitive detection of the ν6 band of cyanoacetylene (HC3N) ice in Titan’s south polar stratosphere. In addition, we also see a strong blend of nitrile ice lattice vibration features around 160 cm-1. From these data we are able to derive ice abundances. The most prominent (and still chemically unidentified) ice emission feature, the Haystack, (at 220 cm-1) is also observed. We establish the vertical distributions of the ice cloud systems associated with both the 160 cm-1 feature and the Haystack. The ultimate aim is to refine the physical and possibly the chemical relationships between the two. Transmittance thin film spectra of nitrile ice mixtures obtained in our Spectroscopy for Planetary ICes Environments (SPICE) laboratory are used to support these analyses.

SPITZER IRS SPECTRA OF LUMINOUS 8 μm SOURCES IN THE LARGE MAGELLANIC CLOUD: TESTING COLOR-BASED CLASSIFICATIONS

International Nuclear Information System (INIS)

Buchanan, Catherine L.; Kastner, Joel H.; Hrivnak, Bruce J.; Sahai, Raghvendra

2009-01-01

We present archival Spitzer Infrared Spectrograph (IRS) spectra of 19 luminous 8 μm selected sources in the Large Magellanic Cloud (LMC). The object classes derived from these spectra and from an additional 24 spectra in the literature are compared with classifications based on Two Micron All Sky Survey (2MASS)/MSX (J, H, K, and 8 μm) colors in order to test the 'JHK8' (Kastner et al.) classification scheme. The IRS spectra confirm the classifications of 22 of the 31 sources that can be classified under the JHK8 system. The spectroscopic classification of 12 objects that were unclassifiable in the JHK8 scheme allow us to characterize regions of the color-color diagrams that previously lacked spectroscopic verification, enabling refinements to the JHK8 classification system. The results of these new classifications are consistent with previous results concerning the identification of the most infrared-luminous objects in the LMC. In particular, while the IRS spectra reveal several new examples of asymptotic giant branch (AGB) stars with O-rich envelopes, such objects are still far outnumbered by carbon stars (C-rich AGB stars). We show that Spitzer IRAC/MIPS color-color diagrams provide improved discrimination between red supergiants and oxygen-rich and carbon-rich AGB stars relative to those based on 2MASS/MSX colors. These diagrams will enable the most luminous IR sources in Local Group galaxies to be classified with high confidence based on their Spitzer colors. Such characterizations of stellar populations will continue to be possible during Spitzer's warm mission through the use of IRAC [3.6]-[4.5] and 2MASS colors.

NOAA GOES-R Series Advanced Baseline Imager (ABI) Level 2+ Cloud Top Pressure (CTP)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Cloud Top Pressure product contains an image with pixel values identifying the atmospheric pressure at the top of a cloud layer. The product is generated in...

Characterization of a novel miniaturized burst-mode infrared laser system for IR-MALDESI mass spectrometry imaging.

Science.gov (United States)

Ekelöf, Måns; Manni, Jeffrey; Nazari, Milad; Bokhart, Mark; Muddiman, David C

2018-03-01

Laser systems are widely used in mass spectrometry as sample probes and ionization sources. Mid-infrared lasers are particularly suitable for analysis of high water content samples such as animal and plant tissues, using water as a resonantly excited sacrificial matrix. Commercially available mid-IR lasers have historically been bulky and expensive due to cooling requirements. This work presents a novel air-cooled miniature mid-IR laser with adjustable burst-mode output and details an evaluation of its performance for mass spectrometry imaging. The miniature laser was found capable of generating sufficient energy for complete ablation of animal tissue in the context of an IR-MALDESI experiment with exogenously added ice matrix, yielding several hundred confident metabolite identifications. Graphical abstract The use of a novel miniature 2.94 μm burst-mode laser in IR-MALDESI allows for rapid and sensitive mass spectrometry imaging of a whole mouse.

CERES cloud property retrievals from imagers on TRMM, Terra, and Aqua

Science.gov (United States)

Minnis, Patrick; Young, David F.; Sun-Mack, Sunny; Heck, Patrick W.; Doelling, David R.; Trepte, Qing Z.

2004-02-01

The micro- and macrophysical properties of clouds play a crucial role in Earth"s radiation budget. The NASA Clouds and Earth"s Radiant Energy System (CERES) is providing simultaneous measurements of the radiation and cloud fields on a global basis to improve the understanding and modeling of the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. Cloud properties derived for CERES from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites are compared to ensure consistency between the products to ensure the reliability of the retrievals from multiple platforms at different times of day. Comparisons of cloud fraction, height, optical depth, phase, effective particle size, and ice and liquid water paths from the two satellites show excellent consistency. Initial calibration comparisons are also very favorable. Differences between the Aqua and Terra results are generally due to diurnally dependent changes in the clouds. Additional algorithm refinement is needed over the polar regions for Aqua and at night over those same areas for Terra. The results should be extremely valuable for model validation and improvement and for improving our understanding of the relationship between clouds and the radiation budget.

Study on the cloud detection of GOCI by using the simulated surface reflectance from BRDF-model for the land application and meteorological utilization

Science.gov (United States)

Kim, Hye-Won; Yeom, Jong-Min; Woo, Sun-Hee; Chae, Tae-Byeong

2016-04-01

COMS (Communication, Ocean, and Meteorological Satellite) was launched at French Guiana Kourou space center on 27 June 2010. Geostationary Ocean Color Imager (GOCI), which is the first ocean color geostationary satellite in the world for observing the ocean phenomena, is able to obtain the scientific data per an hour from 00UTC to 07UTC. Moreover, the spectral channels of GOCI would enable not only monitoring for the ocean, but for extracting the information of the land surface over the Korean Peninsula, Japan, and Eastern China. Since it is extremely important to utilize GOCI data accurately for the land application, cloud pixels over the surface have to be removed. Unfortunately, infra-red (IR) channels that can easily detect the water vapor with the cloud top temperature, are not included in the GOCI sensor. In this paper, the advanced cloud masking algorithm will be proposed with visible and near-IR (NIR) bands that are within GOCI bands. The main obstacle of cloud masking with GOCI is how to handle the high variable surface reflectance, which is mainly depending on the solar zenith angle. In this study, we use semi-empirical BRDF model to simulate the surface reflectance by using 16 day composite cloudy free image. When estimating the simulated surface reflectance, same geometry for GOCI observation was applied. The simulated surface reflectance is used to discriminate cloud areas especially for the thin cloud and shows more reasonable result than original threshold methods.

DSCOVR/EPIC observations of SO2 reveal dynamics of young volcanic eruption clouds

Science.gov (United States)

Carn, S. A.; Krotkov, N. A.; Taylor, S.; Fisher, B. L.; Li, C.; Bhartia, P. K.; Prata, F. J.

2017-12-01

Volcanic emissions of sulfur dioxide (SO2) and ash have been measured by ultraviolet (UV) and infrared (IR) sensors on US and European polar-orbiting satellites since the late 1970s. Although successful, the main limitation of these observations from low Earth orbit (LEO) is poor temporal resolution (once per day at low latitudes). Furthermore, most currently operational geostationary satellites cannot detect SO2, a key tracer of volcanic plumes, limiting our ability to elucidate processes in fresh, rapidly evolving volcanic eruption clouds. In 2015, the launch of the Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR) provided the first opportunity to observe volcanic clouds from the L1 Lagrange point. EPIC is a 10-band spectroradiometer spanning UV to near-IR wavelengths with two UV channels sensitive to SO2, and a ground resolution of 25 km. The unique L1 vantage point provides continuous observations of the sunlit Earth disk, from sunrise to sunset, offering multiple daily observations of volcanic SO2 and ash clouds in the EPIC field of view. When coupled with complementary retrievals from polar-orbiting UV and IR sensors such as the Ozone Monitoring Instrument (OMI), the Ozone Mapping and Profiler Suite (OMPS), and the Atmospheric Infrared Sounder (AIRS), we demonstrate how the increased observation frequency afforded by DSCOVR/EPIC permits more timely volcanic eruption detection and novel analyses of the temporal evolution of volcanic clouds. Although EPIC has detected several mid- to high-latitude volcanic eruptions since launch, we focus on recent eruptions of Bogoslof volcano (Aleutian Islands, AK, USA). A series of EPIC exposures from May 28-29, 2017, uniquely captures the evolution of SO2 mass in a young Bogoslof eruption cloud, showing separation of SO2- and ice-rich regions of the cloud. We show how analyses of these sequences of EPIC SO2 data can elucidate poorly understood processes in transient eruption

Cloud screening Coastal Zone Color Scanner images using channel 5

Science.gov (United States)

Eckstein, B. A.; Simpson, J. J.

1991-01-01

Clouds are removed from Coastal Zone Color Scanner (CZCS) data using channel 5. Instrumentation problems require pre-processing of channel 5 before an intelligent cloud-screening algorithm can be used. For example, at intervals of about 16 lines, the sensor records anomalously low radiances. Moreover, the calibration equation yields negative radiances when the sensor records zero counts, and pixels corrupted by electronic overshoot must also be excluded. The remaining pixels may then be used in conjunction with the procedure of Simpson and Humphrey to determine the CZCS cloud mask. These results plus in situ observations of phytoplankton pigment concentration show that pre-processing and proper cloud-screening of CZCS data are necessary for accurate satellite-derived pigment concentrations. This is especially true in the coastal margins, where pigment content is high and image distortion associated with electronic overshoot is also present. The pre-processing algorithm is critical to obtaining accurate global estimates of pigment from spacecraft data.

3D change detection at street level using mobile laser scanning point clouds and terrestrial images

Science.gov (United States)

Qin, Rongjun; Gruen, Armin

2014-04-01

Automatic change detection and geo-database updating in the urban environment are difficult tasks. There has been much research on detecting changes with satellite and aerial images, but studies have rarely been performed at the street level, which is complex in its 3D geometry. Contemporary geo-databases include 3D street-level objects, which demand frequent data updating. Terrestrial images provides rich texture information for change detection, but the change detection with terrestrial images from different epochs sometimes faces problems with illumination changes, perspective distortions and unreliable 3D geometry caused by the lack of performance of automatic image matchers, while mobile laser scanning (MLS) data acquired from different epochs provides accurate 3D geometry for change detection, but is very expensive for periodical acquisition. This paper proposes a new method for change detection at street level by using combination of MLS point clouds and terrestrial images: the accurate but expensive MLS data acquired from an early epoch serves as the reference, and terrestrial images or photogrammetric images captured from an image-based mobile mapping system (MMS) at a later epoch are used to detect the geometrical changes between different epochs. The method will automatically mark the possible changes in each view, which provides a cost-efficient method for frequent data updating. The methodology is divided into several steps. In the first step, the point clouds are recorded by the MLS system and processed, with data cleaned and classified by semi-automatic means. In the second step, terrestrial images or mobile mapping images at a later epoch are taken and registered to the point cloud, and then point clouds are projected on each image by a weighted window based z-buffering method for view dependent 2D triangulation. In the next step, stereo pairs of the terrestrial images are rectified and re-projected between each other to check the geometrical

Observation of a cavitation cloud in tissue using correlation between ultrafast ultrasound images.

Science.gov (United States)

Prieur, Fabrice; Zorgani, Ali; Catheline, Stefan; Souchon, Rémi; Mestas, Jean-Louis; Lafond, Maxime; Lafon, Cyril

2015-07-01

The local application of ultrasound is known to improve drug intake by tumors. Cavitating bubbles are one of the contributing effects. A setup in which two ultrasound transducers are placed confocally is used to generate cavitation in ex vivo tissue. As the transducers emit a series of short excitation bursts, the evolution of the cavitation activity is monitored using an ultrafast ultrasound imaging system. The frame rate of the system is several thousands of images per second, which provides several tens of images between consecutive excitation bursts. Using the correlation between consecutive images for speckle tracking, a decorrelation of the imaging signal appears due to the creation, fast movement, and dissolution of the bubbles in the cavitation cloud. By analyzing this area of decorrelation, the cavitation cloud can be localized and the spatial extent of the cavitation activity characterized.

Discriminating satellite IR anomalies associated with the MS 7.1 Yushu earthquake in China

Science.gov (United States)

Qin, Kai; Wu, Lixin; Zheng, Shuo; Ma, Weiyu

2018-03-01

In the process of exploring pre-earthquake thermal anomalies using satellite infrared data, Blackett et al. (2011) found that the previously reported anomalies before the 2001 Mw 7.7 Gujarat earthquake, in India, were related to positive biases caused by data gaps due to cloud cover and mosaicing of neighboring orbits of MODIS satellite data. They supposed that such effects could also be responsible for other cases. We noted a strip-shaped TIR anomaly on March 17th, 2010, 28 days before the Ms. 7.1 Yushu earthquake (Qin et al., 2011). Here we again investigate multi-year infrared satellite data in different bands to discriminate whether the anomaly is associated with the earthquake, or is only bias caused by the data gaps. From the water vapor images, we find lots of clouds that have TIR anomalies. However, on the cloudiness background, there is an obvious strip-shaped gap matching the tectonic faults almost perfectly. In particular, the animation loops of hourly water vapor images show that the cloud kept moving from west to east, while they never covered the strip-shaped gap. We consider that the cloud with this special spatial pattern should have implied the abnormal signals associated with the seismogenic process. Based on current physical models, the satellite IR anomalies both on TIR and water vapor bands can qualitatively be explained using synthetic mechanisms.

AUGUSTO'S Sundial: Image-Based Modeling for Reverse Engeneering Purposes

Science.gov (United States)

Baiocchi, V.; Barbarella, M.; Del Pizzo, S.; Giannone, F.; Troisi, S.; Piccaro, C.; Marcantonio, D.

2017-02-01

A photogrammetric survey of a unique archaeological site is reported in this paper. The survey was performed using both a panoramic image-based solution and by classical procedure. The panoramic image-based solution was carried out employing a commercial solution: the Trimble V10 Imaging Rover (IR). Such instrument is an integrated cameras system that captures 360 degrees digital panoramas, composed of 12 images, with a single push. The direct comparison of the point clouds obtained with traditional photogrammetric procedure and V10 stations, using the same GCP coordinates has been carried out in Cloud Compare, open source software that can provide the comparison between two point clouds supplied by all the main statistical data. The site is a portion of the dial plate of the "Horologium Augusti" inaugurated in 9 B.C.E. in the area of Campo Marzio and still present intact in the same position, in a cellar of a building in Rome, around 7 meter below the present ground level.

α-Lipoic acid stabilized DTX/IR780 micelles for photoacoustic/fluorescence imaging guided photothermal therapy/chemotherapy of breast cancer.

Science.gov (United States)

Li, WenTing; Peng, JinRong; Yang, Qian; Chen, LiJuan; Zhang, Lan; Chen, XiaoXin; Qian, ZhiYong

2018-05-01

Micellar nanoparticles have unique advantages as carriers for therapeutic or imaging agents, owing to their smaller size and better penetration of tumors. However, some agents, due to their physical or chemical properties, are difficult to load into micelles. IR780 is one of these agents, and is also a promising near-infrared dye for fluorescence imaging (FI)/photoacoustic imaging (PAI) and cancer photothermal therapy (PTT). Its hydrophobic and high crystallization structure results in limited bioavailability in vivo. It is difficult to load into micelles constructed from an amphiphilic block polymer with relatively low molecular weight. In this study, we use computer simulation and introduce another small biomolecule, α-lipoic acid, into the micelles constructed from a mPEG-PCL copolymer, to lower the energy of molecular interaction between MPEG-PCL and IR780, and expect to enhance the loading capacity of the micelles to IR780. The introduction of α-lipoic acid decreases the energy of molecular interaction between MEPG-PCL and IR780 from -46.18 kJ mol-1 to -196.52 kJ mol-1 and increases the loading capacity and stability of the mPEG-PCL micelles to IR780, which also maintains the loading capacity to DTX. We further construct DTX/IR780 co-loaded mPEG-PCL micelles for FI/PAI dual modal imaging guided PTT/chemotherapy of cancer. By FI and PAI evaluation in vitro and in vivo, we demonstrate that the DTX/IR780 co-loaded micelles can be used as FI and PAI probes. By further evaluating the therapeutic outcome of PTT/chemotherapy co-therapy of breast cancer, we demonstrate that the DTX/IR780 co-loaded mPEG-PCL micelles can serve as promising candidates for FI and PAI guided PTT/chemotherapy of breast cancer.

FAR-INFRARED OBSERVATIONS OF THE VERY LOW LUMINOSITY EMBEDDED SOURCE L1521F-IRS IN THE TAURUS STAR-FORMING REGION

International Nuclear Information System (INIS)

Terebey, Susan; Fich, Michel; Noriega-Crespo, Alberto; Padgett, Deborah L.; Brooke, Tim; Carey, Sean; McCabe, Caer-Eve; Rebull, Luisa; Fukagawa, Misato; Audard, Marc; Evans, Neal J.; Guedel, Manuel; Hines, Dean; Huard, Tracy; Knapp, Gillian R.; Menard, Francois; Monin, Jean-Louis

2009-01-01

We investigate the environment of the very low luminosity object L1521F-IRS using data from the Taurus Spitzer Legacy Survey. The MIPS 160 μm image shows both extended emission from the Taurus cloud and emission from multiple cold cores over a 1 0 x 2 0 region. Analysis shows that the cloud dust temperature is 14.2 ± 0.4 K and the extinction ratio is A 160 /A K = 0.010 ± 0.001 up to A V ∼ 4 mag. We find κ 160 = 0.23 ± 0.046 cm 2 g -1 for the specific opacity of the gas-dust mixture. Therefore, for dust in the Taurus cloud we find that the 160 μm opacity is significantly higher than that measured for the diffuse interstellar medium, but not too different from dense cores, even at modest extinction values. Furthermore, the 160 μm image shows features that do not appear in the IRAS 100 μm image. We identify six regions as cold cores, i.e., colder than 14.2 K, all of which have counterparts in extinction maps or C 18 O maps. Three of the six cores contain embedded young stellar objects, which demonstrates the cores are sites of current star formation. We compare the effects of L1521F-IRS on its natal core and find there is no evidence for dust heating at 160 or 100 μm by the embedded source. From the infrared luminosity L TIR = 0.024 L sun we find L bol-int =0.034-0.046 L odot , thus confirming the source's low luminosity. Comparison of L1521F-IRS with theoretical simulations for the very early phases of star formation appears to rule out the first core collapse phase. The evolutionary state appears similar to or younger than the class 0 phase, and the estimated mass is likely to be substellar.

Reconstruction of 3D Shapes of Opaque Cumulus Clouds from Airborne Multiangle Imaging: A Proof-of-Concept

Science.gov (United States)

Davis, A. B.; Bal, G.; Chen, J.

2015-12-01

Operational remote sensing of microphysical and optical cloud properties is invariably predicated on the assumption of plane-parallel slab geometry for the targeted cloud. The sole benefit of this often-questionable assumption about the cloud is that it leads to one-dimensional (1D) radiative transfer (RT)---a textbook, computationally tractable model. We present new results as evidence that, thanks to converging advances in 3D RT, inverse problem theory, algorithm implementation, and computer hardware, we are at the dawn of a new era in cloud remote sensing where we can finally go beyond the plane-parallel paradigm. Granted, the plane-parallel/1D RT assumption is reasonable for spatially extended stratiform cloud layers, as well as the smoothly distributed background aerosol layers. However, these 1D RT-friendly scenarios exclude cases that are critically important for climate physics. 1D RT---whence operational cloud remote sensing---fails catastrophically for cumuliform clouds that have fully 3D outer shapes and internal structures driven by shallow or deep convection. For these situations, the first order of business in a robust characterization by remote sensing is to abandon the slab geometry framework and determine the 3D geometry of the cloud, as a first step toward bone fide 3D cloud tomography. With this specific goal in mind, we deliver a proof-of-concept for an entirely new kind of remote sensing applicable to 3D clouds. It is based on highly simplified 3D RT and exploits multi-angular suites of cloud images at high spatial resolution. Airborne sensors like AirMSPI readily acquire such data. The key element of the reconstruction algorithm is a sophisticated solution of the nonlinear inverse problem via linearization of the forward model and an iteration scheme supported, where necessary, by adaptive regularization. Currently, the demo uses a 2D setting to show how either vertical profiles or horizontal slices of the cloud can be accurately reconstructed

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

Directory of Open Access Journals (Sweden)

E. Widyaningrum

2017-09-01

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

Design and use of the IR gas-cloud scanner for measurement and imaging of the spatial distribution of gases at workplaces

Science.gov (United States)

ter Kuile, Willem M.; van Veen, J. J.; Knoll, Bas

1995-02-01

Usual sampling methods and instruments for checking compliance with `threshold limit values' (TLV) of gaseous components do not provide much information on the mechanism which caused the measured workday average concentration. In the case of noncompliance this information is indispensable for the design of cost effective measures. The infrared gas cloud (IGC) scanner visualizes the spatial distribution of specific gases at a workplace in a quantitative image with a calibrated grayvalue scale. This helps to find the cause of an over- exposure, and so it permits effective abatement of high exposures in the working environment. This paper deals with the technical design of the IGC scanner. Its use is illustrated by some real-world problems. The measuring principle and the technical operation of the IGC-scanner are described. Special attention is given to the pros and cons of retro-reflector screens, the noise reduction methods and image presentation and interpretation. The latter is illustrated by the images produced by the measurements. Essentially the IGC scanner can be used for selective open-path measurement of all gases with a concentration in the ppm range and sufficiently strong distinct absorption lines in the infrared region between 2.5 micrometers and 14.0 micrometers . Further it could be useful for testing the efficiency of ventilation systems and the remote detection of gas leaks. We conclude that a new powerful technique has been added to the industrial hygiene facilities for controlling and improving the work environment.

3D FT-IR imaging spectroscopy of phase-separation in a poly(3-hydroxybutyrate)/poly(L-lactic acid) blend

Science.gov (United States)

Miriam Unger; Julia Sedlmair; Heinz W. Siesler; Carol Hirschmugl; Barbara Illman

2014-01-01

In the present study, 3D FT-IR spectroscopic imaging measurements were applied to study the phase separation of a poly(3-hydroxybutyrate) (PHB)/poly(L-lactic acid) (PLA) (50:50 wt.%) polymer blend film. While in 2D projection imaging the z-dependent information is overlapped, thereby complicating the analysis, FT-IR spectro-micro-tomography,...

The benefit of limb cloud imaging for infrared limb sounding of tropospheric trace gases

OpenAIRE

G. Heinemann; P. Preusse; R. Spang; S. Adams

2009-01-01

Advances in detector technology enable a new generation of infrared limb sounders to measure 2-D images of the atmosphere. A proposed limb cloud imager (LCI) mode will detect clouds with a spatial resolution unprecedented for limb sounding. For the inference of temperature and trace gas distributions, detector pixels of the LCI have to be combined into super-pixels which provide the required signal-to-noise and information content for the retrievals. This study examines the extent to which tr...

Modulation transfer function cascade model for a sampled IR imaging system.

Science.gov (United States)

de Luca, L; Cardone, G

1991-05-01

The performance of the infrared scanning radiometer (IRSR) is strongly stressed in convective heat transfer applications where high spatial frequencies in the signal that describes the thermal image are present. The need to characterize more deeply the system spatial resolution has led to the formulation of a cascade model for the evaluation of the actual modulation transfer function of a sampled IR imaging system. The model can yield both the aliasing band and the averaged modulation response for a general sampling subsystem. For a line scan imaging system, which is the case of a typical IRSR, a rule of thumb that states whether the combined sampling-imaging system is either imaging-dependent or sampling-dependent is proposed. The model is tested by comparing it with other noncascade models as well as by ad hoc measurements performed on a commercial digitized IRSR.

Study of the relations between cloud properties and atmospheric conditions using ground-based digital images

Science.gov (United States)

Bakalova, Kalinka

The aerosol constituents of the earth atmosphere are of great significance for the radiation budget and global climate of the planet. They are the precursors of clouds that in turn play an essential role in these processes and in the hydrological cycle of the Earth. Understanding the complex aerosol-cloud interactions requires a detailed knowledge of the dynamical processes moving the water vapor through the atmosphere, and of the physical mechanisms involved in the formation and growth of cloud particles. Ground-based observations on regional and short time scale provide valuable detailed information about atmospheric dynamics and cloud properties, and are used as a complementary tool to the global satellite observations. The objective of the present paper is to study the physical properties of clouds as displayed in ground-based visible images, and juxtapose them to the specific surface and atmospheric meteorological conditions. The observations are being carried out over the urban area of the city of Sofia, Bulgaria. The data obtained from visible images of clouds enable a quantitative description of texture and morphological features of clouds such as shape, thickness, motion, etc. These characteristics are related to cloud microphysical properties. The changes of relative humidity and the horizontal visibility are considered to be representative of the variations of the type (natural/manmade) and amount of the atmospheric aerosols near the earth surface, and potentially, the cloud drop number concentration. The atmospheric dynamics is accounted for by means of the values of the atmospheric pressure, temperature, wind velocity, etc., observed at the earth's surface. The advantage of ground-based observations of clouds compared to satellite ones is in the high spatial and temporal resolution of the obtained data about the lowermost cloud layer, which in turn is sensitive to the meteorological regimes that determine cloud formation and evolution. It turns out

Improvements in AVHRR Daytime Cloud Detection Over the ARM NSA Site

Science.gov (United States)

Chakrapani, V.; Spangenberg, D. A.; Doelling, D. R.; Minnis, P.; Trepte, Q. Z.; Arduini, R. F.

2001-01-01

Clouds play an important role in the radiation budget over Arctic and Antarctic. Because of limited surface observing capabilities, it is necessary to detect clouds over large areas using satellite imagery. At low and mid-latitudes, satellite-observed visible (VIS; 0.65 micrometers) and infrared (IR; 11 micrometers) radiance data are used to derive cloud fraction, temperature, and optical depth. However, the extreme variability in the VIS surface albedo makes the detection of clouds from satellite a difficult process in polar regions. The IR data often show that the surface is nearly the same temperature or even colder than clouds, further complicating cloud detection. Also, the boundary layer can have large areas of haze, thin fog, or diamond dust that are not seen in standard satellite imagery. Other spectral radiances measured by satellite imagers provide additional information that can be used to more accurately discriminate clouds from snow and ice. Most techniques currently use a fixed reflectance or temperature threshold to decide between clouds and clear snow. Using a subjective approach, Minnis et al. (2001) found that the clear snow radiance signatures vary as a function of viewing and illumination conditions as well as snow condition. To routinely process satellite imagery over polar regions with an automated algorithm, it is necessary to account for this angular variability and the change in the background reflectance as snow melts, vegetation grows over land, and melt ponds form on pack ice. This paper documents the initial satellite-based cloud product over the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site at Barrow for use by the modeling community. Cloud amount and height are determined subjectively using an adaptation of the methodology of Minnis et al. (2001) and the radiation fields arc determined following the methods of Doelling et al. (2001) as applied to data taken during the Surface Heat and Energy Budget of the

Using IR Imaging of Water Surfaces for Estimating Piston Velocities

Science.gov (United States)

Gålfalk, M.; Bastviken, D.; Arneborg, L.

2013-12-01

The transport of gasses dissolved in surface waters across the water-atmosphere interface is controlled by the piston velocity (k). This coefficient has large implications for, e.g., greenhouse gas fluxes but is challenging to quantify in situ. At present, empirical k-wind speed relationships from a small number of studies and systems are often extrapolated without knowledge of model performance. It is therefore of interest to search for new methods for estimating k, and to compare the pros and cons of existing and new methods. Wind speeds in such models are often measured at a height of 10 meters. In smaller bodies of water such as lakes, wind speeds can vary dramatically across the surface through varying degrees of wind shadow from e.g. trees at the shoreline. More local measurements of the water surface, through wave heights or surface motion mapping, could give improved k-estimates over a surface, also taking into account wind fetch. At thermal infrared (IR) wavelengths water has very low reflectivity (depending on viewing angle) than can go below 1%, meaning that more than 99% is heat radiation giving a direct measurement of surface temperature variations. Using an IR camera at about 100 frames/s one could map surface temperature structures at a fraction of a mm depth even with waves present. In this presentation I will focus on IR imaging as a possible tool for estimating piston velocities. Results will be presented from IR field measurements, relating the motions of surface temperature structures to k calculated from other simultaneous measurements (flux chamber and ADV-Based Dissipation Rate), but also attempting to calculate k directly from the IR surface divergence. A relation between wave height and k will also be presented.

Enabling outsourcing XDS for imaging on the public cloud.

Science.gov (United States)

Ribeiro, Luís S; Rodrigues, Renato P; Costa, Carlos; Oliveira, José Luís

2013-01-01

Picture Archiving and Communication System (PACS) has been the main paradigm in supporting medical imaging workflows during the last decades. Despite its consolidation, the appearance of Cross-Enterprise Document Sharing for imaging (XDS-I), within IHE initiative, constitutes a great opportunity to readapt PACS workflow for inter-institutional data exchange. XDS-I provides a centralized discovery of medical imaging and associated reports. However, the centralized XDS-I actors (document registry and repository) must be deployed in a trustworthy node in order to safeguard patient privacy, data confidentiality and integrity. This paper presents XDS for Protected Imaging (XDS-p), a new approach to XDS-I that is capable of being outsourced (e.g. Cloud Computing) while maintaining privacy, confidentiality, integrity and legal concerns about patients' medical information.

Automatic registration of Iphone images to LASER point clouds of the urban structures using shape features

Directory of Open Access Journals (Sweden)

B. Sirmacek

2013-10-01

Full Text Available Fusion of 3D airborne laser (LIDAR data and terrestrial optical imagery can be applied in 3D urban modeling and model up-dating. The most challenging aspect of the fusion procedure is registering the terrestrial optical images on the LIDAR point clouds. In this article, we propose an approach for registering these two different data from different sensor sources. As we use iPhone camera images which are taken in front of the interested urban structure by the application user and the high resolution LIDAR point clouds of the acquired by an airborne laser sensor. After finding the photo capturing position and orientation from the iPhone photograph metafile, we automatically select the area of interest in the point cloud and transform it into a range image which has only grayscale intensity levels according to the distance from the image acquisition position. We benefit from local features for registering the iPhone image to the generated range image. In this article, we have applied the registration process based on local feature extraction and graph matching. Finally, the registration result is used for facade texture mapping on the 3D building surface mesh which is generated from the LIDAR point cloud. Our experimental results indicate possible usage of the proposed algorithm framework for 3D urban map updating and enhancing purposes.

The Measurement of cloud velocity using the pulsed laser and image tracking technique

Energy Technology Data Exchange (ETDEWEB)

Kwon, Seong-Ouk; Baik, Seung-Hoon; Park, Seung-Kyu; Park, Nak-Gyu; Kim, Dong-lyul; Ahn, Yong-Jin [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2015-05-15

The height of the clouds is also important for the three dimensional radiative interaction of aerosols and clouds, since the radiative effects vary strongly depending whether the cloud is above, below or even embedded in an aerosol layer. Clouds play an important role in climate change, in the prediction of local weather, and also in aviation safety when instrument assisted flying is unavailable. Presently, various ground-based instruments used for the measurements of the cloud base height or velocity. Lidar techniques are powerful and have many applications in climate studies, including the clouds' temperature measurement, the aerosol particle properties, etc. Otherwise, it is very circumscribed in cloud velocity measurements In this paper, we propose a new method to measure the cloud velocity. In this paper, we presented a method for the measurement of the cloud altitude and velocity using lidar's range detection and the tracking system. For the lidar system, we used an injection-seeded pulsed Nd:YAG laser as the transmitter to measure the distance to the target clouds. We used the DIC system to track the cloud image and calculate the actual displacement per unit time. The configured lidar system acquired the lidar signal of clouds at a distance of about 4 km. The developed fast correlation algorithm of the tracking, which is used to track the fast moving cloud relatively, was efficient for measuring the cloud velocity in real time. The measurement values had a linear distribution.

Content-based histopathology image retrieval using CometCloud.

Science.gov (United States)

Qi, Xin; Wang, Daihou; Rodero, Ivan; Diaz-Montes, Javier; Gensure, Rebekah H; Xing, Fuyong; Zhong, Hua; Goodell, Lauri; Parashar, Manish; Foran, David J; Yang, Lin

2014-08-26

The development of digital imaging technology is creating extraordinary levels of accuracy that provide support for improved reliability in different aspects of the image analysis, such as content-based image retrieval, image segmentation, and classification. This has dramatically increased the volume and rate at which data are generated. Together these facts make querying and sharing non-trivial and render centralized solutions unfeasible. Moreover, in many cases this data is often distributed and must be shared across multiple institutions requiring decentralized solutions. In this context, a new generation of data/information driven applications must be developed to take advantage of the national advanced cyber-infrastructure (ACI) which enable investigators to seamlessly and securely interact with information/data which is distributed across geographically disparate resources. This paper presents the development and evaluation of a novel content-based image retrieval (CBIR) framework. The methods were tested extensively using both peripheral blood smears and renal glomeruli specimens. The datasets and performance were evaluated by two pathologists to determine the concordance. The CBIR algorithms that were developed can reliably retrieve the candidate image patches exhibiting intensity and morphological characteristics that are most similar to a given query image. The methods described in this paper are able to reliably discriminate among subtle staining differences and spatial pattern distributions. By integrating a newly developed dual-similarity relevance feedback module into the CBIR framework, the CBIR results were improved substantially. By aggregating the computational power of high performance computing (HPC) and cloud resources, we demonstrated that the method can be successfully executed in minutes on the Cloud compared to weeks using standard computers. In this paper, we present a set of newly developed CBIR algorithms and validate them using two

Cloud Height Retrieval with Oxygen A and B Bands for the Deep Space Climate Observatory (DSCOVR) Mission

Science.gov (United States)

Yang, Yuekui; Marshak, Alexander; Mao, Jianping; Lyapustin, Alexei; Herman, Jay

2012-01-01

Planned to fly in 2014, the Deep Space Climate Observatory (DSCOVR) would see the whole sunlit half of the Earth from the L 1 Lagrangian point and would provide simultaneous data on cloud and aerosol properties with its Earth Polychromatic Imaging Camera (EPIC). EPIC images the Earth on a 2Kx2K CCD array, which gives a horizontal resolution of about 10 km at nadir. A filter-wheel provides consecutive images in 10 spectral channels ranging from the UV to the near-IR, including the oxygen A and B bands. This paper presents a study of retrieving cloud height with EPIC's oxygen A and B bands. As the first step, we analyzed the effect of cloud optical and geometrical properties, sun-view geometry, and surface type on the cloud height determination. Second, we developed two cloud height retrieval algorithms that are based on the Mixed Lambertian-Equivalent Reflectivity (MLER) concept: one utilizes the absolute radiances at the Oxygen A and B bands and the other uses the radiance ratios between the absorption and reference channels of the two bands. Third, we applied the algorithms to the simulated EPIC data and to the data from SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY (SCIAMACHY) observations. Results show that oxygen A and B bands complement each other: A band is better suited for retrievals over ocean, while B band is better over vegetated land due to a much darker surface. Improvements to the MLER model, including corrections to surface contribution and photon path inside clouds, will also be discussed.

Cloud Imagers Offer New Details on Earth's Health

Science.gov (United States)

2009-01-01

A stunning red sunset or purple sunrise is an aesthetic treat with a scientific explanation: The colors are a direct result of the absorption or reflectance of solar radiation by atmospheric aerosols, minute particles (either solid or liquid) in the Earth s atmosphere that occur both naturally and because of human activity. At the beginning or end of the day, the Sun s rays travel farther through the atmosphere to reach an observer s eyes and more green and yellow light is scattered, making the Sun appear red. Sunset and sunrise are especially colorful when the concentration of atmospheric particles is high. This ability of aerosols to absorb and reflect sunlight is not just pretty; it also determines the amount of radiation and heat that reaches the Earth s surface, and can profoundly affect climate. In the atmosphere, aerosols are also important as nuclei for the condensation of water droplets and ice crystals. Clouds with fewer aerosols cannot form as many water droplets (called cloud particles), and consequently, do not scatter light well. In this case, more sunlight reaches the Earth s surface. When aerosol levels in clouds are high, however, more nucleation points can form small liquid water droplets. These smaller cloud particles can reflect up to 90 percent of visible radiation to space, keeping the heat from ever reaching Earth s surface. The tendency for these particles to absorb or reflect the Sun s energy - called extinction by astronomers - depends on a number of factors, including chemical composition and the humidity and temperature in the surrounding air; because cloud particles are so small, they are affected quickly by minute changes in the atmosphere. Because of this sensitivity, atmospheric scientists study cloud particles to anticipate patterns and shifts in climate. Until recently, NASA s study of atmospheric aerosols and cloud particles has been focused primarily on satellite images, which, while granting large-scale atmospheric analysis

Spatiotemporal High-Resolution Cloud Mapping with a Ground-Based IR Scanner

NARCIS (Netherlands)

Brede, Benjamin; Thies, Boris; Bendix, Jörg; Feister, Uwe

2017-01-01

The high spatiotemporal variability of clouds requires automated monitoring systems. This study presents a retrieval algorithm that evaluates observations of a hemispherically scanning thermal infrared radiometer, the NubiScope, to produce georeferenced, spatially explicit cloud maps. The algorithm

Development of Multi-Sensor Global Cloud and Radiance Composites for DSCOVR EPIC Imager with Subpixel Definition

Science.gov (United States)

Khlopenkov, K. V.; Duda, D. P.; Thieman, M. M.; Sun-Mack, S.; Su, W.; Minnis, P.; Bedka, K. M.

2017-12-01

The Deep Space Climate Observatory (DSCOVR) is designed to study the daytime Earth radiation budget by means of onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). EPIC imager observes in several shortwave bands (317-780 nm), while NISTAR measures the top-of-atmosphere (TOA) whole-disk radiance in shortwave and total broadband windows. Calculation of albedo and outgoing longwave flux requires a high-resolution scene identification such as the radiance observations and cloud property retrievals from low earth orbit and geostationary satellite imagers. These properties have to be co-located with EPIC imager pixels to provide scene identification and to select anisotropic directional models, which are then used to adjust the NISTAR-measured radiance and subsequently obtain the global daytime shortwave and longwave fluxes. This work presents an algorithm for optimal merging of selected radiances and cloud properties derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. The highest quality observation is selected by means of an aggregated rating which incorporates several factors such as the nearest time relative to EPIC observation, lowest viewing zenith angle, and others. This process provides a smoother transition and avoids abrupt changes in the merged composite data. Higher spatial accuracy in the composite product is achieved by using the inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling. The composite data are subsequently remapped into the EPIC-view domain by convolving composite pixels with the EPIC point spread function (PSF) defined with a half-pixel accuracy. Within every EPIC footprint, the PSF-weighted average radiances and cloud properties are computed for each cloud phase and then stored within five data subsets (clear-sky, water cloud, ice cloud, total cloud, and no

Auto-Scaling of Geo-Based Image Processing in an OpenStack Cloud Computing Environment

OpenAIRE

Sanggoo Kang; Kiwon Lee

2016-01-01

Cloud computing is a base platform for the distribution of large volumes of data and high-performance image processing on the Web. Despite wide applications in Web-based services and their many benefits, geo-spatial applications based on cloud computing technology are still developing. Auto-scaling realizes automatic scalability, i.e., the scale-out and scale-in processing of virtual servers in a cloud computing environment. This study investigates the applicability of auto-scaling to geo-bas...

Absorbing Aerosols Above Cloud: Detection, Quantitative Retrieval, and Radiative Forcing from Satellite-based Passive Sensors

Science.gov (United States)

Jethva, H.; Torres, O.; Remer, L. A.; Bhartia, P. K.

2012-12-01

Light absorbing particles such as carbonaceous aerosols generated from biomass burning activities and windblown dust particles can exert a net warming effect on climate; the strength of which depends on the absorption capacity of the particles and brightness of the underlying reflecting background. When advected over low-level bright clouds, these aerosols absorb the cloud reflected radiation from ultra-violet (UV) to shortwave-IR (SWIR) and makes cloud scene darker-a phenomenon commonly known as "cloud darkening". The apparent "darkening" effect can be seen by eyes in satellite images as well as quantitatively in the spectral reflectance measurements made by space borne sensors over regions where light absorbing carbonaceous and dust aerosols overlay low-level cloud decks. Theoretical radiative transfer simulations support the observational evidence, and further reveal that the strength of the cloud darkening and its spectral signature (or color ratio) between measurements at two wavelengths are a bi-function of aerosol and cloud optical thickness (AOT and COT); both are measures of the total amount of light extinction caused by aerosols and cloud, respectively. Here, we developed a retrieval technique, named as the "color ratio method" that uses the satellite measurements at two channels, one at shorter wavelength in the visible and one at longer wavelength in the shortwave-IR for the simultaneous retrieval of AOT and COT. The present technique requires assumptions on the aerosol single-scattering albedo and aerosol-cloud separation which are supplemented by the Aerosol Robotic Network (AERONET) and space borne CALIOP lidar measurements. The retrieval technique has been tested making use of the near-UV and visible reflectance observations made by the Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) for distinct above-cloud smoke and dust aerosol events observed seasonally over the southeast and tropical Atlantic Ocean

Automatic Cloud and Shadow Detection in Optical Satellite Imagery Without Using Thermal Bands—Application to Suomi NPP VIIRS Images over Fennoscandia

Directory of Open Access Journals (Sweden)

Eija Parmes

2017-08-01

Full Text Available In land monitoring applications, clouds and shadows are considered noise that should be removed as automatically and quickly as possible, before further analysis. This paper presents a method to detect clouds and shadows in Suomi NPP satellite’s VIIRS (Visible Infrared Imaging Radiometer Suite satellite images. The proposed cloud and shadow detection method has two distinct features when compared to many other methods. First, the method does not use the thermal bands and can thus be applied to other sensors which do not contain thermal channels, such as Sentinel-2 data. Secondly, the method uses the ratio between blue and green reflectance to detect shadows. Seven hundred and forty-seven VIIRS images over Fennoscandia from August 2014 to April 2016 were processed to train and develop the method. Twenty four points from every tenth of the images were used in accuracy assessment. These 1752 points were interpreted visually to cloud, cloud shadow and clear classes, then compared to the output of the cloud and shadow detection. The comparison on VIIRS images showed 94.2% correct detection rates and 11.1% false alarms for clouds, and respectively 36.1% and 82.7% for shadows. The results on cloud detection were similar to state-of-the-art methods. Shadows showed correctly on the northern edge of the clouds, but many shadows were wrongly assigned to other classes in some cases (e.g., to water class on lake and forest boundary, or with shadows over cloud. This may be due to the low spatial resolution of VIIRS images, where shadows are only a few pixels wide and contain lots of mixed pixels.

Image velocimetry for clouds with relaxation labeling based on deformation consistency

International Nuclear Information System (INIS)

Horinouchi, Takeshi; Murakami, Shin-ya; Yamazaki, Atsushi; Kouyama, Toru; Ogohara, Kazunori; Yamada, Manabu; Watanabe, Shigeto

2017-01-01

Correlation-based cloud tracking has been extensively used to measure atmospheric winds, but still difficulty remains. In this study, aiming at developing a cloud tracking system for Akatsuki, an artificial satellite orbiting Venus, a formulation is developed for improving the relaxation labeling technique to select appropriate peaks of cross-correlation surfaces which tend to have multiple peaks. The formulation makes an explicit use of consistency inherent in the type of cross-correlation method where template sub-images are slid without deformation; if the resultant motion vectors indicate a too-large deformation, it is contradictory to the assumption of the method. The deformation consistency is exploited further to develop two post processes; one clusters the motion vectors into groups within each of which the consistency is perfect, and the other extends the groups using the original candidate lists. These processes are useful to eliminate erroneous vectors, distinguish motion vectors at different altitudes, and detect phase velocities of waves in fluids such as atmospheric gravity waves. As a basis of the relaxation labeling and the post processes as well as uncertainty estimation, the necessity to find isolated (well-separated) peaks of cross-correlation surfaces is argued, and an algorithm to realize it is presented. All the methods are implemented, and their effectiveness is demonstrated with initial images obtained by the ultraviolet imager onboard Akatsuki. Since the deformation consistency regards the logical consistency inherent in template matching methods, it should have broad application beyond cloud tracking. (paper)

Image velocimetry for clouds with relaxation labeling based on deformation consistency

Science.gov (United States)

Horinouchi, Takeshi; Murakami, Shin-ya; Kouyama, Toru; Ogohara, Kazunori; Yamazaki, Atsushi; Yamada, Manabu; Watanabe, Shigeto

2017-08-01

Correlation-based cloud tracking has been extensively used to measure atmospheric winds, but still difficulty remains. In this study, aiming at developing a cloud tracking system for Akatsuki, an artificial satellite orbiting Venus, a formulation is developed for improving the relaxation labeling technique to select appropriate peaks of cross-correlation surfaces which tend to have multiple peaks. The formulation makes an explicit use of consistency inherent in the type of cross-correlation method where template sub-images are slid without deformation; if the resultant motion vectors indicate a too-large deformation, it is contradictory to the assumption of the method. The deformation consistency is exploited further to develop two post processes; one clusters the motion vectors into groups within each of which the consistency is perfect, and the other extends the groups using the original candidate lists. These processes are useful to eliminate erroneous vectors, distinguish motion vectors at different altitudes, and detect phase velocities of waves in fluids such as atmospheric gravity waves. As a basis of the relaxation labeling and the post processes as well as uncertainty estimation, the necessity to find isolated (well-separated) peaks of cross-correlation surfaces is argued, and an algorithm to realize it is presented. All the methods are implemented, and their effectiveness is demonstrated with initial images obtained by the ultraviolet imager onboard Akatsuki. Since the deformation consistency regards the logical consistency inherent in template matching methods, it should have broad application beyond cloud tracking.

IR sensitivity enhancement of CMOS Image Sensor with diffractive light trapping pixels.

Science.gov (United States)

Yokogawa, Sozo; Oshiyama, Itaru; Ikeda, Harumi; Ebiko, Yoshiki; Hirano, Tomoyuki; Saito, Suguru; Oinoue, Takashi; Hagimoto, Yoshiya; Iwamoto, Hayato

2017-06-19

We report on the IR sensitivity enhancement of back-illuminated CMOS Image Sensor (BI-CIS) with 2-dimensional diffractive inverted pyramid array structure (IPA) on crystalline silicon (c-Si) and deep trench isolation (DTI). FDTD simulations of semi-infinite thick c-Si having 2D IPAs on its surface whose pitches over 400 nm shows more than 30% improvement of light absorption at λ = 850 nm and the maximum enhancement of 43% with the 540 nm pitch at the wavelength is confirmed. A prototype BI-CIS sample with pixel size of 1.2 μm square containing 400 nm pitch IPAs shows 80% sensitivity enhancement at λ = 850 nm compared to the reference sample with flat surface. This is due to diffraction with the IPA and total reflection at the pixel boundary. The NIR images taken by the demo camera equip with a C-mount lens show 75% sensitivity enhancement in the λ = 700-1200 nm wavelength range with negligible spatial resolution degradation. Light trapping CIS pixel technology promises to improve NIR sensitivity and appears to be applicable to many different image sensor applications including security camera, personal authentication, and range finding Time-of-Flight camera with IR illuminations.

Cloud and radiance measurements with the VIS/NIR Daylight Whole Sky Imager at Lindenberg (Germany)

Energy Technology Data Exchange (ETDEWEB)

Feister, U. [Deutscher Wetterdienst, Meteorologisches Observatorium Lindenberg (Germany); Shields, J. [Scripps Inst. of Oceanography, Univ. of California, San Diego (United States)

2005-10-01

Ground-based cloud data acquired with the whole sky imager (WSI) are analyzed in relation to measurements of solar radiation performed at the Lindenberg Meteorological Observatory. Cloud fractions derived by the cloud detection algorithm from WSI images acquired during daylight hours between 2002 and 2004 are compared with conventional cloud observations for the two sites Potsdam and Lindenberg, and also with ceilometer data of cloud-base heights at Lindenberg. The comparison statistics are discussed in the context of different principles of measurement. A few case studies illustrate the strong scattering effect of clouds on solar radiance and irradiance measured at the ground in different spectral regions. Particularly clouds close to the apparent position of the sun lead to strong enhancements of solar diffuse irradiance incident on horizontal planes and hemispheres that substantially exceed corresponding clear-sky values. Irradiances derived from WSI sky radiance fields are shown in comparison to pyranometer data of diffuse irradiance and radiative transfer model calculations performed for clear sky conditions. Examples of spectral sky radiances with moving contrails illustrate the significant enhancement the contrails have compared to clear sky, even though they may have a relatively small direct effect on global irradiance values. As contrails are observed at Lindenberg for about 18 to 19% of daylight hours, and part of them become clouds, the indirect impact of these changes on solar irradiance received at the ground may not be negligible. (orig.)

High-resolution T1-weighted 3D real IR imaging of the temporal bone using triple-dose contrast material

Energy Technology Data Exchange (ETDEWEB)

Naganawa, Shinji; Koshikawa, Tokiko; Nakamura, Tatsuya; Fukatsu, Hiroshi; Ishigaki, Takeo [Department of Radiology, Nagoya University School of Medicine, 65 Tsurumai-cho, Shouwa-ku, 466-8550, Nagoya (Japan); Aoki, Ikuo [Medical System Company, Toshiba Corporation, Tokyo (Japan)

2003-12-01

The small structures in the temporal bone are surrounded by bone and air. The objectives of this study were (a) to compare contrast-enhanced T1-weighted images acquired by fast spin-echo-based three-dimensional real inversion recovery (3D rIR) against those acquired by gradient echo-based 3D SPGR in the visualization of the enhancement of small structures in the temporal bone, and (b) to determine whether either 3D rIR or 3D SPGR is useful for visualizing enhancement of the cochlear lymph fluid. Seven healthy men (age range 27-46 years) volunteered to participate in this study. All MR imaging was performed using a dedicated bilateral quadrature surface phased-array coil for temporal bone imaging at 1.5 T (Visart EX, Toshiba, Tokyo, Japan). The 3D rIR images (TR/TE/TI: 1800 ms/10 ms/500 ms) and flow-compensated 3D SPGR images (TR/TE/FA: 23 ms/10 ms/25 ) were obtained with a reconstructed voxel size of 0.6 x 0.7 x 0.8 mm{sup 3}. Images were acquired before and 1, 90, 180, and 270 min after the administration of triple-dose Gd-DTPA-BMA (0.3 mmol/kg). In post-contrast MR images, the degree of enhancement of the cochlear aqueduct, endolymphatic sac, subarcuate artery, geniculate ganglion of the facial nerve, and cochlear lymph fluid space was assessed by two radiologists. The degree of enhancement was scored as follows: 0 (no enhancement); 1 (slight enhancement); 2 (intermediate between 1 and 3); and 3 (enhancement similar to that of vessels). Enhancement scores for the endolymphatic sac, subarcuate artery, and geniculate ganglion were higher in 3D rIR than in 3D SPGR. Washout of enhancement in the endolymphatic sac appeared to be delayed compared with that in the subarcuate artery, suggesting that the enhancement in the endolymphatic sac may have been due in part to non-vascular tissue enhancement. Enhancement of the cochlear lymph space was not observed in any of the subjects in 3D rIR and 3D SPGR. The 3D rIR sequence may be more sensitive than the 3D SPGR sequence in

Cloud Computing for radiologists.

Science.gov (United States)

Kharat, Amit T; Safvi, Amjad; Thind, Ss; Singh, Amarjit

2012-07-01

Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future.

Cloud Computing for radiologists

International Nuclear Information System (INIS)

Kharat, Amit T; Safvi, Amjad; Thind, SS; Singh, Amarjit

2012-01-01

Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future

Cloud computing for radiologists

Directory of Open Access Journals (Sweden)

Amit T Kharat

2012-01-01

Full Text Available Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future.

A high resolution IR/visible imaging system for the W7-X limiter

Energy Technology Data Exchange (ETDEWEB)

Wurden, G. A., E-mail: wurden@lanl.gov; Dunn, J. P. [Los Alamos National Laboratory, Los Alamos, New Mexico 87545 (United States); Stephey, L. A. [University of Wisconsin, Madison, Wisconsin 53706 (United States); Biedermann, C.; Jakubowski, M. W.; Gamradt, M. [Max Planck Institut für Plasma Physik, Wendelsteinstrasse 1, 17491 Greifswald (Germany)

2016-11-15

A high-resolution imaging system, consisting of megapixel mid-IR and visible cameras along the same line of sight, has been prepared for the new W7-X stellarator and was operated during Operational Period 1.1 to view one of the five inboard graphite limiters. The radial line of sight, through a large diameter (184 mm clear aperture) uncoated sapphire window, couples a direct viewing 1344 × 784 pixel FLIR SC8303HD camera. A germanium beam-splitter sends visible light to a 1024 × 1024 pixel Allied Vision Technologies Prosilica GX1050 color camera. Both achieve sub-millimeter resolution on the 161 mm wide, inertially cooled, segmented graphite tiles. The IR and visible cameras are controlled via optical fibers over full Camera Link and dual GigE Ethernet (2 Gbit/s data rates) interfaces, respectively. While they are mounted outside the cryostat at a distance of 3.2 m from the limiter, they are close to a large magnetic trim coil and require soft iron shielding. We have taken IR data at 125 Hz to 1.25 kHz frame rates and seen that surface temperature increases in excess of 350 °C, especially on leading edges or defect hot spots. The IR camera sees heat-load stripe patterns on the limiter and has been used to infer limiter power fluxes (∼1–4.5 MW/m{sup 2}), during the ECRH heating phase. IR images have also been used calorimetrically between shots to measure equilibrated bulk tile temperature, and hence tile energy inputs (in the range of 30 kJ/tile with 0.6 MW, 6 s heating pulses). Small UFO’s can be seen and tracked by the FLIR camera in some discharges. The calibrated visible color camera (100 Hz frame rate) has also been equipped with narrow band C-III and H-alpha filters, to compare with other diagnostics, and is used for absolute particle flux determination from the limiter surface. Sometimes, but not always, hot-spots in the IR are also seen to be bright in C-III light.

A high resolution IR/visible imaging system for the W7-X limiter

International Nuclear Information System (INIS)

Wurden, G. A.; Dunn, J. P.; Stephey, L. A.; Biedermann, C.; Jakubowski, M. W.; Gamradt, M.

2016-01-01

A high-resolution imaging system, consisting of megapixel mid-IR and visible cameras along the same line of sight, has been prepared for the new W7-X stellarator and was operated during Operational Period 1.1 to view one of the five inboard graphite limiters. The radial line of sight, through a large diameter (184 mm clear aperture) uncoated sapphire window, couples a direct viewing 1344 × 784 pixel FLIR SC8303HD camera. A germanium beam-splitter sends visible light to a 1024 × 1024 pixel Allied Vision Technologies Prosilica GX1050 color camera. Both achieve sub-millimeter resolution on the 161 mm wide, inertially cooled, segmented graphite tiles. The IR and visible cameras are controlled via optical fibers over full Camera Link and dual GigE Ethernet (2 Gbit/s data rates) interfaces, respectively. While they are mounted outside the cryostat at a distance of 3.2 m from the limiter, they are close to a large magnetic trim coil and require soft iron shielding. We have taken IR data at 125 Hz to 1.25 kHz frame rates and seen that surface temperature increases in excess of 350 °C, especially on leading edges or defect hot spots. The IR camera sees heat-load stripe patterns on the limiter and has been used to infer limiter power fluxes (∼1–4.5 MW/m"2), during the ECRH heating phase. IR images have also been used calorimetrically between shots to measure equilibrated bulk tile temperature, and hence tile energy inputs (in the range of 30 kJ/tile with 0.6 MW, 6 s heating pulses). Small UFO’s can be seen and tracked by the FLIR camera in some discharges. The calibrated visible color camera (100 Hz frame rate) has also been equipped with narrow band C-III and H-alpha filters, to compare with other diagnostics, and is used for absolute particle flux determination from the limiter surface. Sometimes, but not always, hot-spots in the IR are also seen to be bright in C-III light.

HIERARCHICAL REGULARIZATION OF POLYGONS FOR PHOTOGRAMMETRIC POINT CLOUDS OF OBLIQUE IMAGES

Directory of Open Access Journals (Sweden)

L. Xie

2017-05-01

Full Text Available Despite the success of multi-view stereo (MVS reconstruction from massive oblique images in city scale, only point clouds and triangulated meshes are available from existing MVS pipelines, which are topologically defect laden, free of semantical information and hard to edit and manipulate interactively in further applications. On the other hand, 2D polygons and polygonal models are still the industrial standard. However, extraction of the 2D polygons from MVS point clouds is still a non-trivial task, given the fact that the boundaries of the detected planes are zigzagged and regularities, such as parallel and orthogonal, cannot preserve. Aiming to solve these issues, this paper proposes a hierarchical polygon regularization method for the photogrammetric point clouds from existing MVS pipelines, which comprises of local and global levels. After boundary points extraction, e.g. using alpha shapes, the local level is used to consolidate the original points, by refining the orientation and position of the points using linear priors. The points are then grouped into local segments by forward searching. In the global level, regularities are enforced through a labeling process, which encourage the segments share the same label and the same label represents segments are parallel or orthogonal. This is formulated as Markov Random Field and solved efficiently. Preliminary results are made with point clouds from aerial oblique images and compared with two classical regularization methods, which have revealed that the proposed method are more powerful in abstracting a single building and is promising for further 3D polygonal model reconstruction and GIS applications.

Jupiter's Multi-level Clouds

Science.gov (United States)

1997-01-01

Clouds and hazes at various altitudes within the dynamic Jovian atmosphere are revealed by multi-color imaging taken by the Near-Infrared Mapping Spectrometer (NIMS) onboard the Galileo spacecraft. These images were taken during the second orbit (G2) on September 5, 1996 from an early-morning vantage point 2.1 million kilometers (1.3 million miles) above Jupiter. They show the planet's appearance as viewed at various near-infrared wavelengths, with distinct differences due primarily to variations in the altitudes and opacities of the cloud systems. The top left and right images, taken at 1.61 microns and 2.73 microns respectively, show relatively clear views of the deep atmosphere, with clouds down to a level about three times the atmospheric pressure at the Earth's surface.By contrast, the middle image in top row, taken at 2.17 microns, shows only the highest altitude clouds and hazes. This wavelength is severely affected by the absorption of light by hydrogen gas, the main constituent of Jupiter's atmosphere. Therefore, only the Great Red Spot, the highest equatorial clouds, a small feature at mid-northern latitudes, and thin, high photochemical polar hazes can be seen. In the lower left image, at 3.01 microns, deeper clouds can be seen dimly against gaseous ammonia and methane absorption. In the lower middle image, at 4.99 microns, the light observed is the planet's own indigenous heat from the deep, warm atmosphere.The false color image (lower right) succinctly shows various cloud and haze levels seen in the Jovian atmosphere. This image indicates the temperature and altitude at which the light being observed is produced. Thermally-rich red areas denote high temperatures from photons in the deep atmosphere leaking through minimal cloud cover; green denotes cool temperatures of the tropospheric clouds; blue denotes cold of the upper troposphere and lower stratosphere. The polar regions appear purplish, because small-particle hazes allow leakage and reflectivity

A comparison of performance of automatic cloud coverage assessment algorithm for Formosat-2 image using clustering-based and spatial thresholding methods

Science.gov (United States)

Hsu, Kuo-Hsien

2012-11-01

Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.

Explicit prediction of ice clouds in general circulation models

Science.gov (United States)

Kohler, Martin

1999-11-01

Although clouds play extremely important roles in the radiation budget and hydrological cycle of the Earth, there are large quantitative uncertainties in our understanding of their generation, maintenance and decay mechanisms, representing major obstacles in the development of reliable prognostic cloud water schemes for General Circulation Models (GCMs). Recognizing their relative neglect in the past, both observationally and theoretically, this work places special focus on ice clouds. A recent version of the UCLA - University of Utah Cloud Resolving Model (CRM) that includes interactive radiation is used to perform idealized experiments to study ice cloud maintenance and decay mechanisms under various conditions in term of: (1) background static stability, (2) background relative humidity, (3) rate of cloud ice addition over a fixed initial time-period and (4) radiation: daytime, nighttime and no-radiation. Radiation is found to have major effects on the life-time of layer-clouds. Optically thick ice clouds decay significantly slower than expected from pure microphysical crystal fall-out (taucld = 0.9--1.4 h as opposed to no-motion taumicro = 0.5--0.7 h). This is explained by the upward turbulent fluxes of water induced by IR destabilization, which partially balance the downward transport of water by snowfall. Solar radiation further slows the ice-water decay by destruction of the inversion above cloud-top and the resulting upward transport of water. Optically thin ice clouds, on the other hand, may exhibit even longer life-times (>1 day) in the presence of radiational cooling. The resulting saturation mixing ratio reduction provides for a constant cloud ice source. These CRM results are used to develop a prognostic cloud water scheme for the UCLA-GCM. The framework is based on the bulk water phase model of Ose (1993). The model predicts cloud liquid water and cloud ice separately, and which is extended to split the ice phase into suspended cloud ice (predicted

Water ice clouds observations with PFS on Mars Express

Science.gov (United States)

Moroz, V. I.; Zasova, L. V.; Formisano, V.; Grassi, D.; Ignatiev, N. I.; Giuranna, M.; Maturilli, A.; Pfs Team

The water ice cloud observation is one of the scientific goals of PFS. Presence and properties of the ice particles are identified from absorption features, observed in both spectral ranges of PFS. Being in the near perihelion condition, the temperature of the Martian atmosphere is pretty high and ice clouds exist only in some places, for example, related to topography or at north high latitudes et etc. The ice clouds are observed often above the tops of the volcanoes. We have found the ice clouds above Olympus (orbit 37) and Ascraeus Mons (orbit 68). Effective radius of particles according to the thermal IR is preliminary estimated of 1 μ m, which leads to the visual opacity of 0.2 -0.3 above Olympus and of maximum of 0.6 above Ascraeus Mons. In the case of Ascraeus Mons the ice clouds are observed on the south slope near the top of the volcano. The maximum surface temperature, observed there, results in the upward flux of warm air, which, cooling, provides the condensation of H2O. We will present a detailed analysis of the ice clouds, observed over the planet in the IR spectral range.

Exploration of the Infrared Sensitivity for a ZnSe Electrode of an IR Image Converter

Science.gov (United States)

Kurt, H. Hilal

2018-05-01

Significant improvement has been carried out in the field of the II-VI group semiconductor device technology. Semiconductors based on the II-VI group are attractive due to their alternative uses for thermal imaging systems and photonic applications. This study focuses on experimental work on the optical, electrical and structural characterization of an infrared (IR) photodetector zinc selenide (ZnSe). In addition, the IR sensitivity of the ZnSe has primarily been investigated by exploiting the IR responses of the material for various gas pressures, p, and interelectrode distances, d, in the IR converter. The experimental findings include the results of plasma current and plasma discharge emission under various illumination conditions in the IR region. The electron density distributions inside the gas discharge gap have also been simulated in two-dimensional media. Experimentally, the current-voltage, current-time, and discharge light emission plots are produced for a wide experimental parameter range. Consequently, the structural and optical properties have been studied through atomic force microscopy and Fourier-transform infrared spectroscopy techniques to obtain a comprehensive knowledge of the material.

CCD and IR array controllers

Science.gov (United States)

Leach, Robert W.; Low, Frank J.

2000-08-01

A family of controllers has bene developed that is powerful and flexible enough to operate a wide range of CCD and IR focal plane arrays in a variety of ground-based applications. These include fast readout of small CCD and IR arrays for adaptive optics applications, slow readout of large CCD and IR mosaics, and single CCD and IR array operation at low background/low noise regimes as well as high background/high speed regimes. The CCD and IR controllers have a common digital core based on user- programmable digital signal processors that are used to generate the array clocking and signal processing signals customized for each application. A fiber optic link passes image data and commands to VME or PCI interface boards resident in a host computer to the controller. CCD signal processing is done with a dual slope integrator operating at speeds of up to one Megapixel per second per channel. Signal processing of IR arrays is done either with a dual channel video processor or a four channel video processor that has built-in image memory and a coadder to 32-bit precision for operating high background arrays. Recent developments underway include the implementation of a fast fiber optic data link operating at a speed of 12.5 Megapixels per second for fast image transfer from the controller to the host computer, and supporting image acquisition software and device drivers for the PCI interface board for the Sun Solaris, Linux and Windows 2000 operating systems.

Diurnal, Seasonal, and Interannual Variations of Cloud Properties Derived for CERES From Imager Data

Science.gov (United States)

Minnis, Patrick; Young, David F.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Brown, Richard R.; Gibson, Sharon; Heck, Patrick W.

2004-01-01

Simultaneous measurement of the radiation and cloud fields on a global basis is a key component in the effort to understand and model the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project, begun in 1998, is meeting this need. Broadband shortwave (SW) and longwave radiance measurements taken by the CERES scanners at resolutions between 10 and 20 km on the Tropical Rainfall Measuring Mission (TRMM), Terra, and Aqua satellites are matched to simultaneous retrievals of cloud height, phase, particle size, water path, and optical depth OD from the TRMM Visible Infrared Scanner (VIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Besides aiding the interpretation of the broadband radiances, the CERES cloud properties are valuable for understanding cloud variations at a variety of scales. In this paper, the resulting CERES cloud data taken to date are averaged at several temporal scales to examine the temporal and spatial variability of the cloud properties on a global scale at a 1 resolution.

The cloud monitor by an infrared camera at the Telescope Array experiment

International Nuclear Information System (INIS)

Shibata, F.

2011-01-01

The mesurement of the extensive air shower using the fluorescence detectors (FDs) is affected by the condition of the atmosphere. In particular, FD aperture is limited by cloudiness. If cloud exists on the light path from extensive air shower to FDs, fluorescence photons will be absorbed drastically. Therefore cloudiness of FD's field of view (FOV) is one of important quality cut condition in FD analysis. In the Telescope Array (TA), an infrared (IR) camera with 320x236 pixels and a filed of view of 25.8 deg. x19.5 deg. has been installed at an observation site for cloud monitoring during FD observations. This IR camera measures temperature of the sky every 30 min during FD observation. IR camera is mounted on steering table, which can be changed in elevation and azimuthal direction. Clouds can be seen at a higher temperature than areas of cloudless sky from these temperature maps. In this paper, we discuss the quality of the cloud monitoring data, the analysis method, and current quality cut condition of cloudiness in FD analysis.

About possibility of temperature trace observing on a human skin through clothes by using computer processing of IR image

Science.gov (United States)

Trofimov, Vyacheslav A.; Trofimov, Vladislav V.; Shestakov, Ivan L.; Blednov, Roman G.

2017-05-01

One of urgent security problems is a detection of objects placed inside the human body. Obviously, for safety reasons one cannot use X-rays for such object detection widely and often. For this purpose, we propose to use THz camera and IR camera. Below we continue a possibility of IR camera using for a detection of temperature trace on a human body. In contrast to passive THz camera using, the IR camera does not allow to see very pronounced the object under clothing. Of course, this is a big disadvantage for a security problem solution based on the IR camera using. To find possible ways for this disadvantage overcoming we make some experiments with IR camera, produced by FLIR Company and develop novel approach for computer processing of images captured by IR camera. It allows us to increase a temperature resolution of IR camera as well as human year effective susceptibility enhancing. As a consequence of this, a possibility for seeing of a human body temperature changing through clothing appears. We analyze IR images of a person, which drinks water and eats chocolate. We follow a temperature trace on human body skin, caused by changing of temperature inside the human body. Some experiments are made with observing of temperature trace from objects placed behind think overall. Demonstrated results are very important for the detection of forbidden objects, concealed inside the human body, by using non-destructive control without using X-rays.

Real-time near-IR imaging of laser-ablation crater evolution in dental enamel

Science.gov (United States)

Darling, Cynthia L.; Fried, Daniel

2007-02-01

We have shown that the enamel of the tooth is almost completely transparent near 1310-nm in the near-infrared and that near-IR (NIR) imaging has considerable potential for the optical discrimination of sound and demineralized tissue and for observing defects in the interior of the tooth. Lasers are now routinely used for many applications in dentistry including the ablation of dental caries. The objective of this study was to test the hypothesis that real-time NIR imaging can be used to monitor laser-ablation under varying conditions to assess peripheral thermal and transient-stress induced damage and to measure the rate and efficiency of ablation. Moreover, NIR imaging may have considerable potential for monitoring the removal of demineralized areas of the tooth during cavity preparations. Sound human tooth sections of approximately 3-mm thickness were irradiated by a CO II laser under varying conditions with and without a water spray. The incision area in the interior of each sample was imaged using a tungsten-halogen lamp with band-pass filter centered at 131--nm combined with an InGaAs focal plane array with a NIR zoom microscope in transillumination. Due to the high transparency of enamel at 1310-nm, laser-incisions were clearly visible to the dentin-enamel junction and crack formation, dehydration and irreversible thermal changes were observed during ablation. This study showed that there is great potential for near-IR imaging to monitor laser-ablation events in real-time to: assess safe laser operating parameters by imaging thermal and stress-induced damage, elaborate the mechanisms involved in ablation such as dehydration, and monitor the removal of demineralized enamel.

Upconversion imager measures single mid-IR photons

DEFF Research Database (Denmark)

Dam, Jeppe Seidelin; Tidemand-Lichtenberg, Peter; Pedersen, Christian

2013-01-01

the performance of today's state of the art IR detectors for the visible/near-IR region shows a striking contrast, as the latter can have dark currents in the range of 0.001 electrons per second. Demonstrated performance of waveguide upconversion techniques still show considerable dark noise, even when working...

Jupiter's Great Red Spot upper cloud morphology and dynamics from JunoCam images

Science.gov (United States)

Sanchez-Lavega, A.; Hueso, R.; Eichstädt, G.; Orton, G.; Rogers, J.; Hansen, C. J.; Momary, T.; Tabataba-Vakili, F.

2017-12-01

We present an analysis of RGB color-composite images of the Great Red Spot (GRS) obtained with JunoCam during Juno's seventh close flyby (PJ7) on July 11, 2017. The images have been projected as 4 cylindrical maps with a resolution of 180 pixels per degree (about 7 km/pixel) spanning a temporal interval of 9 min 41s. The GRS shows a rich variety of cloud morphologies that reveal different dynamical processes in its interior. We consider three major regions. (1) An outer peripheral ring of homogeneous reddish clouds (width about 1,300 km) traces a laminar flow. A family of at least three packets of gravity waves with a mean wavelength of 75 km is present at the internal edge of the ring (in its northern side). They occupy an area of 2,500 km in length (East-West, EW) and 670 km in the North-South (NS) direction. Single clouds in the groups forming the wave have extents of 35 km EW and 70-135 km NS. (2) A large internal region of red clouds (width about 3,200 km) contains three morphologies: (a) fields of bright cumulus-like clusters, (b) long, dark curved filaments (about 7,000 km length with 100 km width), two of them converging into an arrowhead shape, and (c) individual anticyclonic vortices with radius of 500 km that grow due to the radial shear of the wind velocity in the GRS interior as previously measured. A cumulus cluster is conspicuous inside one such anticyclone. Each single cloud element is 50 km in size and the cluster has a 25-30 percent area coverage in cumulus-convective activity, presumably due to ammonia moist convection. (3) A central core has quasi-rectangular shape, extending about 5000 km EW and 3000 km NS, that is confined by elongated clouds distributed along its periphery. Its interior is filled with the redder clouds in the GRS that have a scale 100 km and form a turbulent pattern whose cloud orientations suggest three adjacent areas with alternating cyclonic-cyclonic-anticyclonic vorticity, each with radius 650-850 km.

Interferometric laser imaging for in-flight cloud droplet sizing

International Nuclear Information System (INIS)

Dunker, Christina; Roloff, Christoph; Grassmann, Arne

2016-01-01

A non-intrusive particle sizing method with a high spatial distribution is used to estimate cloud droplet spectra during flight test campaigns. The interferometric laser imaging for droplet sizing (ILIDS) method derives particle diameters of transparent spheres by evaluating the out-of-focus image patterns. This sizing approach requires a polarized monochromatic light source, a camera including an objective lens with a slit aperture, a synchronization unit and a processing tool for data evaluation. These components are adapted to a flight test environment to enable the microphysical investigation of different cloud genera. The present work addresses the design and specifications of ILIDS system, flight test preparation and selected results obtained in the lower and middle troposphere. The research platform was a Dornier Do228-101 commuter aircraft at the DLR Flight Operation Center in Braunschweig. It was equipped with the required instrumentation including a high-energy laser as the light source. A comprehensive data set of around 71 800 ILIDS images was acquired over the course of five flights. The data evaluation of the characteristic ILIDS fringe patterns relies, among other things, on a relationship between the fringe spacing and the diameter of the particle. The simplest way to extract this information from a pattern is by fringe counting, which is not viable for such an extensive number of data. A brief contrasting comparison of evaluation methods based on frequency analysis by means of fast Fourier transform and on correlation methods such as minimum quadratic difference is used to encompass the limits and accuracy of the ILIDS method for such applications. (paper)

CO and IRAS detection of an intermediate-velocity cloud

International Nuclear Information System (INIS)

Desert, F.X.; Bazell, D.; Blitz, L.

1990-01-01

In the course of a radio survey of high-Galactic-latitude clouds, CO emission was detected at the position l = 210.8 deg and b = 63.1 deg with an LSR velocity of -39 km/sec. This molecular cloud constitutes the third one with an unusually large absolute velocity at these latitudes, as compared with the 5.4-km/sec cloud-to-cloud velocity dispersion of the high-latitude molecular clouds. The position is coincident with an H I intermediate-velocity cloud (GHL 11, Verschuur H, OLM 268) and the IR-excess cloud 306 in the list by Desert et al. (1988). This cloud is clearly detected at all four IRAS wavelengths and has warmer colors than the local ISM. 27 refs

Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm.

Science.gov (United States)

Yang, Mengzhao; Song, Wei; Mei, Haibin

2017-07-23

The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient.

Cloud top structure of Venus revealed by Subaru/COMICS mid-infrared images

Science.gov (United States)

Sato, T. M.; Sagawa, H.; Kouyama, T.; Mitsuyama, K.; Satoh, T.; Ohtsuki, S.; Ueno, M.; Kasaba, Y.; Nakamura, M.; Imamura, T.

2014-11-01

We have investigated the cloud top structure of Venus by analyzing ground-based images taken at the mid-infrared wavelengths of 8.66 μm and 11.34 μm. Venus at a solar phase angle of ∼90°, with the morning terminator in view, was observed by the Cooled Mid-Infrared Camera and Spectrometer (COMICS), mounted on the 8.2-m Subaru Telescope, during the period October 25-29, 2007. The disk-averaged brightness temperatures for the observation period are ∼230 K and ∼238 K at 8.66 μm and 11.34 μm, respectively. The obtained images with good signal-to-noise ratio and with high spatial resolution (∼200 km at the sub-observer point) provide several important findings. First, we present observational evidence, for the first time, of the possibility that the westward rotation of the polar features (the hot polar spots and the surrounding cold collars) is synchronized between the northern and southern hemispheres. Second, after high-pass filtering, the images reveal that streaks and mottled and patchy patterns are distributed over the entire disk, with typical amplitudes of ∼0.5 K, and vary from day to day. The detected features, some of which are similar to those seen in past UV images, result from inhomogeneities of both the temperature and the cloud top altitude. Third, the equatorial center-to-limb variations of brightness temperatures have a systematic day-night asymmetry, except those on October 25, that the dayside brightness temperatures are higher than the nightside brightness temperatures by 0-4 K under the same viewing geometry. Such asymmetry would be caused by the propagation of the migrating semidiurnal tide. Finally, by applying the lapse rates deduced from previous studies, we demonstrate that the equatorial center-to-limb curves in the two spectral channels give access to two parameters: the cloud scale height H and the cloud top altitude zc. The acceptable models for data on October 25 are obtained at H = 2.4-4.3 km and zc = 66-69 km; this supports

A method of retrieving cloud top height and cloud geometrical thickness with oxygen A and B bands for the Deep Space Climate Observatory (DSCOVR) mission: Radiative transfer simulations

International Nuclear Information System (INIS)

Yang, Yuekui; Marshak, Alexander; Mao, Jianping; Lyapustin, Alexei; Herman, Jay

2013-01-01

The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) was designed to measure the atmosphere and surface properties over the whole sunlit half of the Earth from the L1 Lagrangian point. It has 10 spectral channels ranging from the UV to the near-IR, including two pairs of oxygen (O 2 ) A-band (779.5 and 764 nm) and B-band (680 and 687.75 nm) reference and absorption channels selected for the cloud height measurements. This paper presents the radiative transfer analysis pertinent to retrieving cloud top height and cloud geometrical thickness with EPIC A- and B-band observations. Due to photon cloud penetration, retrievals from either O 2 A- or B-band channels alone gives the corresponding cloud centroid height, which is lower than the cloud top. However, we show both the sum and the difference between the retrieved cloud centroid heights in the A and B bands are functions of cloud top height and cloud geometrical thickness. Based on this fact, the paper develops a new method to retrieve cloud top height and cloud geometrical thickness simultaneously for fully cloudy scenes over ocean surface. First, cloud centroid heights are calculated for both A and B bands using the ratios between the reflectances of the absorbing and reference channels; then the cloud top height and the cloud geometrical thickness are retrieved from the two dimensional look up tables that relate the sum and the difference between the retrieved centroid heights for A and B bands to the cloud top height and the cloud geometrical thickness. This method is applicable for clouds thicker than an optical depth of 5. -- Highlights: ► EPIC onboard DSCOVR is equipped with O 2 A and B band channels. ► Photon cloud penetration depths of A and B bands contain information of cloud thickness. ► A method is developed to retrieve cloud top height and cloud geometrical thickness with EPIC O 2 A- and B-band

The Impact of Cross-track Infrared Sounder (CrIS) Cloud-Cleared Radiances on Hurricane Joaquin (2015) and Matthew (2016) Forecasts

Science.gov (United States)

Wang, Pei; Li, Jun; Li, Zhenglong; Lim, Agnes H. N.; Li, Jinlong; Schmit, Timothy J.; Goldberg, Mitchell D.

2017-12-01

Hyperspectral infrared (IR) sounders provide high vertical resolution atmospheric sounding information that can improve the forecast skill in numerical weather prediction. Commonly, only clear radiances are assimilated, because IR sounder observations are highly affected by clouds. A cloud-clearing (CC) technique, which removes the cloud effects from an IR cloudy field of view (FOV) and derives the cloud-cleared radiances (CCRs) or clear-sky equivalent radiances, can be an alternative yet effective way to take advantage of the thermodynamic information from cloudy skies in data assimilation. This study develops a Visible Infrared Imaging Radiometer Suite (VIIRS)-based CC method for deriving Cross-track Infrared Sounder (CrIS) CCRs under partially cloudy conditions. Due to the lack of absorption bands on VIIRS, two important quality control steps are implemented in the CC process. Validation using VIIRS clear radiances indicates that the CC method can effectively obtain the CrIS CCRs for FOVs with partial cloud cover. To compare the impacts from assimilation of CrIS original radiances and CCRs, three experiments are carried out on two storm cases, Hurricane Joaquin (2015) and Hurricane Matthew (2016), using Gridpoint Statistical Interpolation assimilation system and Weather Research and Forecasting-Advanced Research Version models. At the analysis time, more CrIS observations are assimilated when using CrIS CCRs than with CrIS original radiances. Comparing temperature, specific humidity, and U/V winds with radiosondes indicates that the data impacts are growing larger with longer time forecasts (beyond 72 h forecast). Hurricane track forecasts also show improvements from the assimilation of CrIS CCRs due to better weather system forecasts. The impacts of CCRs on intensity are basically neutral with mixed positive and negative results.

A cloud collaborative medical image platform oriented by social network

Science.gov (United States)

Muniz, Frederico B.; Araújo, Luciano V.; Nunes, Fátima L. S.

2017-03-01

Computer-aided diagnosis systems using medical images and three-dimensional models as input data have greatly expanded and developed, but in terms of building suitable image databases to assess them, the challenge remains. Although there are some image databases available for this purpose, they are generally limited to certain types of exams or contain a limited number of medical cases. The objective of this work is to present the concepts and the development of a collaborative platform for sharing medical images and three-dimensional models, providing a resource to share and increase the number of images available for researchers. The collaborative cloud platform, called CATALYZER, aims to increase the availability and sharing of graphic objects, including 3D images, and their reports that are essential for research related to medical images. A survey conducted with researchers and health professionals indicated that this could be an innovative approach in the creation of medical image databases, providing a wider variety of cases together with a considerable amount of shared information among its users.

Accelerating statistical image reconstruction algorithms for fan-beam x-ray CT using cloud computing

Science.gov (United States)

Srivastava, Somesh; Rao, A. Ravishankar; Sheinin, Vadim

2011-03-01

Statistical image reconstruction algorithms potentially offer many advantages to x-ray computed tomography (CT), e.g. lower radiation dose. But, their adoption in practical CT scanners requires extra computation power, which is traditionally provided by incorporating additional computing hardware (e.g. CPU-clusters, GPUs, FPGAs etc.) into a scanner. An alternative solution is to access the required computation power over the internet from a cloud computing service, which is orders-of-magnitude more cost-effective. This is because users only pay a small pay-as-you-go fee for the computation resources used (i.e. CPU time, storage etc.), and completely avoid purchase, maintenance and upgrade costs. In this paper, we investigate the benefits and shortcomings of using cloud computing for statistical image reconstruction. We parallelized the most time-consuming parts of our application, the forward and back projectors, using MapReduce, the standard parallelization library on clouds. From preliminary investigations, we found that a large speedup is possible at a very low cost. But, communication overheads inside MapReduce can limit the maximum speedup, and a better MapReduce implementation might become necessary in the future. All the experiments for this paper, including development and testing, were completed on the Amazon Elastic Compute Cloud (EC2) for less than $20.

A ROBUST REGISTRATION ALGORITHM FOR POINT CLOUDS FROM UAV IMAGES FOR CHANGE DETECTION

Directory of Open Access Journals (Sweden)

A. Al-Rawabdeh

2016-06-01

Full Text Available Landslides are among the major threats to urban landscape and manmade infrastructure. They often cause economic losses, property damages, and loss of lives. Temporal monitoring data of landslides from different epochs empowers the evaluation of landslide progression. Alignment of overlapping surfaces from two or more epochs is crucial for the proper analysis of landslide dynamics. The traditional methods for point-cloud-based landslide monitoring rely on using a variation of the Iterative Closest Point (ICP registration procedure to align any reconstructed surfaces from different epochs to a common reference frame. However, sometimes the ICP-based registration can fail or may not provide sufficient accuracy. For example, point clouds from different epochs might fit to local minima due to lack of geometrical variability within the data. Also, manual interaction is required to exclude any non-stable areas from the registration process. In this paper, a robust image-based registration method is introduced for the simultaneous evaluation of all registration parameters. This includes the Interior Orientation Parameters (IOPs of the camera and the Exterior Orientation Parameters (EOPs of the involved images from all available observation epochs via a bundle block adjustment with self-calibration. Next, a semi-global dense matching technique is implemented to generate dense 3D point clouds for each epoch using the images captured in a particular epoch separately. The normal distances between any two consecutive point clouds can then be readily computed, because the point clouds are already effectively co-registered. A low-cost DJI Phantom II Unmanned Aerial Vehicle (UAV was customised and used in this research for temporal data collection over an active soil creep area in Lethbridge, Alberta, Canada. The customisation included adding a GPS logger and a Large-Field-Of-View (LFOV action camera which facilitated capturing high-resolution geo-tagged images

a Robust Registration Algorithm for Point Clouds from Uav Images for Change Detection

Science.gov (United States)

Al-Rawabdeh, A.; Al-Gurrani, H.; Al-Durgham, K.; Detchev, I.; He, F.; El-Sheimy, N.; Habib, A.

2016-06-01

Landslides are among the major threats to urban landscape and manmade infrastructure. They often cause economic losses, property damages, and loss of lives. Temporal monitoring data of landslides from different epochs empowers the evaluation of landslide progression. Alignment of overlapping surfaces from two or more epochs is crucial for the proper analysis of landslide dynamics. The traditional methods for point-cloud-based landslide monitoring rely on using a variation of the Iterative Closest Point (ICP) registration procedure to align any reconstructed surfaces from different epochs to a common reference frame. However, sometimes the ICP-based registration can fail or may not provide sufficient accuracy. For example, point clouds from different epochs might fit to local minima due to lack of geometrical variability within the data. Also, manual interaction is required to exclude any non-stable areas from the registration process. In this paper, a robust image-based registration method is introduced for the simultaneous evaluation of all registration parameters. This includes the Interior Orientation Parameters (IOPs) of the camera and the Exterior Orientation Parameters (EOPs) of the involved images from all available observation epochs via a bundle block adjustment with self-calibration. Next, a semi-global dense matching technique is implemented to generate dense 3D point clouds for each epoch using the images captured in a particular epoch separately. The normal distances between any two consecutive point clouds can then be readily computed, because the point clouds are already effectively co-registered. A low-cost DJI Phantom II Unmanned Aerial Vehicle (UAV) was customised and used in this research for temporal data collection over an active soil creep area in Lethbridge, Alberta, Canada. The customisation included adding a GPS logger and a Large-Field-Of-View (LFOV) action camera which facilitated capturing high-resolution geo-tagged images in two epochs

Time Series UAV Image-Based Point Clouds for Landslide Progression Evaluation Applications.

Science.gov (United States)

Al-Rawabdeh, Abdulla; Moussa, Adel; Foroutan, Marzieh; El-Sheimy, Naser; Habib, Ayman

2017-10-18

Landslides are major and constantly changing threats to urban landscapes and infrastructure. It is essential to detect and capture landslide changes regularly. Traditional methods for monitoring landslides are time-consuming, costly, dangerous, and the quality and quantity of the data is sometimes unable to meet the necessary requirements of geotechnical projects. This motivates the development of more automatic and efficient remote sensing approaches for landslide progression evaluation. Automatic change detection involving low-altitude unmanned aerial vehicle image-based point clouds, although proven, is relatively unexplored, and little research has been done in terms of accounting for volumetric changes. In this study, a methodology for automatically deriving change displacement rates, in a horizontal direction based on comparisons between extracted landslide scarps from multiple time periods, has been developed. Compared with the iterative closest projected point (ICPP) registration method, the developed method takes full advantage of automated geometric measuring, leading to fast processing. The proposed approach easily processes a large number of images from different epochs and enables the creation of registered image-based point clouds without the use of extensive ground control point information or further processing such as interpretation and image correlation. The produced results are promising for use in the field of landslide research.

Theoretical studies of radiative properties of broken clouds

International Nuclear Information System (INIS)

Titov, G.A.

1994-01-01

One of the three goals of the Atmospheric Radiation Measurement (ARM) Program is to improve the quality of radiation models under clear sky, homogeneous cloud, and broken cloud conditions. This report is concerned with the development of the theory of radiation transfer in the broken clouds. Our approach is based on a stochastic description of the interaction between the radiation and cloud field with stochastic geometry; In the following, we discuss (1) the mean radiation fluxes in the near IR spectral range 2.7 to 3.2 μm; (2) the influence of random geometry of individual cumulus clouds on the mean fluxes of visible solar radiation; (3) the equations of the mean radiance in the statistically inhomogeneous cloud fields

Hot Spots Detection of Operating PV Arrays through IR Thermal Image Using Method Based on Curve Fitting of Gray Histogram

Directory of Open Access Journals (Sweden)

Jiang Lin

2016-01-01

Full Text Available The overall efficiency of PV arrays is affected by hot spots which should be detected and diagnosed by applying responsible monitoring techniques. The method using the IR thermal image to detect hot spots has been studied as a direct, noncontact, nondestructive technique. However, IR thermal images suffer from relatively high stochastic noise and non-uniformity clutter, so the conventional methods of image processing are not effective. The paper proposes a method to detect hotspots based on curve fitting of gray histogram. The result of MATLAB simulation proves the method proposed in the paper is effective to detect the hot spots suppressing the noise generated during the process of image acquisition.

Retrieval of Cloud Properties for Partially Cloud-Filled Pixels During CRYSTAL-FACE

Science.gov (United States)

Nguyen, L.; Minnis, P.; Smith, W. L.; Khaiyer, M. M.; Heck, P. W.; Sun-Mack, S.; Uttal, T.; Comstock, J.

2003-12-01

Partially cloud-filled pixels can be a significant problem for remote sensing of cloud properties. Generally, the optical depth and effective particle sizes are often too small or too large, respectively, when derived from radiances that are assumed to be overcast but contain radiation from both clear and cloud areas within the satellite imager field of view. This study presents a method for reducing the impact of such partially cloud field pixels by estimating the cloud fraction within each pixel using higher resolution visible (VIS, 0.65mm) imager data. Although the nominal resolution for most channels on the Geostationary Operational Environmental Satellite (GOES) imager and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra are 4 and 1 km, respectively, both instruments also take VIS channel data at 1 km and 0.25 km, respectively. Thus, it may be possible to obtain an improved estimate of cloud fraction within the lower resolution pixels by using the information contained in the higher resolution VIS data. GOES and MODIS multi-spectral data, taken during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE), are analyzed with the algorithm used for the Atmospheric Radiation Measurement Program (ARM) and the Clouds and Earth's Radiant Energy System (CERES) to derive cloud amount, temperature, height, phase, effective particle size, optical depth, and water path. Normally, the algorithm assumes that each pixel is either entirely clear or cloudy. In this study, a threshold method is applied to the higher resolution VIS data to estimate the partial cloud fraction within each low-resolution pixel. The cloud properties are then derived from the observed low-resolution radiances using the cloud cover estimate to properly extract the radiances due only to the cloudy part of the scene. This approach is applied to both GOES and MODIS data to estimate the improvement in the retrievals for each

Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel

Science.gov (United States)

Stubenrauch, C. J.; Rossow, W. B.; Kinne, S.; Ackerman, S.; Cesana, G.; Chepfer, H.; Getzewich, B.; Di Girolamo, L.; Guignard, A.; Heidinger, A.;

A secure online image trading system for untrusted cloud environments.

Science.gov (United States)

Munadi, Khairul; Arnia, Fitri; Syaryadhi, Mohd; Fujiyoshi, Masaaki; Kiya, Hitoshi

2015-01-01

In conventional image trading systems, images are usually stored unprotected on a server, rendering them vulnerable to untrusted server providers and malicious intruders. This paper proposes a conceptual image trading framework that enables secure storage and retrieval over Internet services. The process involves three parties: an image publisher, a server provider, and an image buyer. The aim is to facilitate secure storage and retrieval of original images for commercial transactions, while preventing untrusted server providers and unauthorized users from gaining access to true contents. The framework exploits the Discrete Cosine Transform (DCT) coefficients and the moment invariants of images. Original images are visually protected in the DCT domain, and stored on a repository server. Small representation of the original images, called thumbnails, are generated and made publicly accessible for browsing. When a buyer is interested in a thumbnail, he/she sends a query to retrieve the visually protected image. The thumbnails and protected images are matched using the DC component of the DCT coefficients and the moment invariant feature. After the matching process, the server returns the corresponding protected image to the buyer. However, the image remains visually protected unless a key is granted. Our target application is the online market, where publishers sell their stock images over the Internet using public cloud servers.

Real-time near IR (1310 nm) imaging of CO2 laser ablation of enamel.

Science.gov (United States)

Darling, Cynthia L; Fried, Daniel

2008-02-18

The high-transparency of dental enamel in the near-IR (NIR) can be exploited for real-time imaging of ablation crater formation during drilling with lasers. NIR images were acquired with an InGaAs focal plane array and a NIR zoom microscope during drilling incisions in human enamel samples with a lambda=9.3-microm CO(2) laser operating at repetition rates of 50-300-Hz with and without a water spray. Crack formation, dehydration and thermal changes were observed during ablation. These initial images demonstrate the potential of NIR imaging to monitor laser-ablation events in real-time to provide information about the mechanism of ablation and to evaluate the potential for peripheral thermal and mechanical damage.

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)

Science.gov (United States)

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2018-01-01

This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (clouds the error is mostly limited to within 10%, although for thin clouds (COT cloud masking and cloud temperature retrievals are not considered in this study. PMID:29619116

IR-to-visible image upconverter under nonlinear crystal thermal gradient operation.

Science.gov (United States)

Maestre, H; Torregrosa, A J; Fernández-Pousa, C R; Capmany, J

2018-01-22

In this work we study the enhancement of the field-of-view of an infrared image up-converter by means of a thermal gradient in a PPLN crystal. Our work focuses on compact upconverters, in which both a short PPLN crystal length and high numerical aperture lenses are employed. We found a qualitative increase in both wavelength and angular tolerances, compared to a constant temperature upconverter, which makes it necessary a correct IR wavelength allocation in order to effectively increase the up-converted area.

Automated jitter correction for IR image processing to assess the quality of W7-X high heat flux components

International Nuclear Information System (INIS)

Greuner, H; De Marne, P; Herrmann, A; Boeswirth, B; Schindler, T; Smirnow, M

2009-01-01

An automated IR image processing method was developed to evaluate the surface temperature distribution of cyclically loaded high heat flux (HHF) plasma facing components. IPP Garching will perform the HHF testing of a high percentage of the series production of the WENDELSTEIN 7-X (W7-X) divertor targets to minimize the number of undiscovered uncertainties in the finally installed components. The HHF tests will be performed as quality assurance (QA) complementary to the non-destructive examination (NDE) methods used during the manufacturing. The IR analysis of an HHF-loaded component detects growing debonding of the plasma facing material, made of carbon fibre composite (CFC), after a few thermal cycles. In the case of the prototype testing, the IR data was processed manually. However, a QA method requires a reliable, reproducible and efficient automated procedure. Using the example of the HHF testing of W7-X pre-series target elements, the paper describes the developed automated IR image processing method. The algorithm is based on an iterative two-step correlation analysis with an individually defined reference pattern for the determination of the jitter.

Mid-IR hyperspectral imaging for label-free histopathology and cytology

Science.gov (United States)

Hermes, M.; Brandstrup Morrish, R.; Huot, L.; Meng, L.; Junaid, S.; Tomko, J.; Lloyd, G. R.; Masselink, W. T.; Tidemand-Lichtenberg, P.; Pedersen, C.; Palombo, F.; Stone, N.

2018-02-01

Mid-infrared (MIR) imaging has emerged as a valuable tool to investigate biological samples, such as tissue histological sections and cell cultures, by providing non-destructive chemical specificity without recourse to labels. While feasibility studies have shown the capabilities of MIR imaging approaches to address key biological and clinical questions, these techniques are still far from being deployable by non-expert users. In this review, we discuss the current state of the art of MIR technologies and give an overview on technical innovations and developments with the potential to make MIR imaging systems more readily available to a larger community. The most promising developments over the last few years are discussed here. They include improvements in MIR light sources with the availability of quantum cascade lasers and supercontinuum IR sources as well as the recently developed upconversion scheme to improve the detection of MIR radiation. These technical advances can substantially speed up data acquisition of multispectral or hyperspectral datasets thus providing the end user with vast amounts of data when imaging whole tissue areas of many mm2. Therefore, effective data analysis is of tremendous importance, and progress in method development is discussed with respect to the specific biomedical context.

Detection of Multi-Layer and Vertically-Extended Clouds Using A-Train Sensors

Science.gov (United States)

Joiner, J.; Vasilkov, A. P.; Bhartia, P. K.; Wind, G.; Platnick, S.; Menzel, W. P.

2010-01-01

The detection of mUltiple cloud layers using satellite observations is important for retrieval algorithms as well as climate applications. In this paper, we describe a relatively simple algorithm to detect multiple cloud layers and distinguish them from vertically-extended clouds. The algorithm can be applied to coincident passive sensors that derive both cloud-top pressure from the thermal infrared observations and an estimate of solar photon pathlength from UV, visible, or near-IR measurements. Here, we use data from the A-train afternoon constellation of satellites: cloud-top pressure, cloud optical thickness, the multi-layer flag from the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the optical centroid cloud pressure from the Aura Ozone Monitoring Instrument (OMI). For the first time, we use data from the CloudSat radar to evaluate the results of a multi-layer cloud detection scheme. The cloud classification algorithms applied with different passive sensor configurations compare well with each other as well as with data from CloudSat. We compute monthly mean fractions of pixels containing multi-layer and vertically-extended clouds for January and July 2007 at the OMI spatial resolution (l2kmx24km at nadir) and at the 5kmx5km MODIS resolution used for infrared cloud retrievals. There are seasonal variations in the spatial distribution of the different cloud types. The fraction of cloudy pixels containing distinct multi-layer cloud is a strong function of the pixel size. Globally averaged, these fractions are approximately 20% and 10% for OMI and MODIS, respectively. These fractions may be significantly higher or lower depending upon location. There is a much smaller resolution dependence for fractions of pixels containing vertically-extended clouds (approx.20% for OMI and slightly less for MODIS globally), suggesting larger spatial scales for these clouds. We also find higher fractions of vertically-extended clouds over land as compared with

Submm-Wave Radiometry for Cloud/Humidity/Precipitation Sciences

Science.gov (United States)

Wu, Dong L.

2011-01-01

Although active sensors can provide cloud profiles at good vertical resolution, clouds are often coupled with dynamics to form fast and organized structures. Lack of understanding of these organized systems leads to great challenge for numerical models. The deficiency is partly reflected, for example, in poorly modeled intraseasonal variations (e.g., MJD). Remote sensing clouds in the middle and upper troposphere has been challenging from space. Vis/IR sensors are sensitive to the topmost cloud layers whereas low-frequency MW techniques are sensitivity to liquid and precipitation at the bottom of cloud layers. The middle-level clouds, mostly in the ice phase, require a sensor that has moderate penetration and sensitivity to cloud scattering, in order to measure cloud water content. Sensors at submm wavelengths provide promising sensitivity and coverage with the spatial resolution needed to measure cloud water content floating in the upper air. In addition, submm-wave sensors are able to provide better measurements of upper-tropospheric humidity than traditional microwave instruments.

Near-IR Spectral Imaging of Semiconductor Absorption Sites in Integrated Circuits

Directory of Open Access Journals (Sweden)

E. C. Samson

2004-12-01

Full Text Available We derive spectral maps of absorption sites in integrated circuits (ICs by varying the wavelength of the optical probe within the near-IR range. This method has allowed us to improve the contrast of the acquired images by revealing structures that have a different optical absorption from neighboring sites. A false color composite image from those acquired at different wavelengths is generated from which the response of each semiconductor structure can be deduced. With the aid of the spectral maps, nonuniform absorption was also observed in a semiconductor structure located near an electrical overstress defect. This method may prove important in failure analysis of ICs by uncovering areas exhibiting anomalous absorption, which could improve localization of defective edifices in the semiconductor parts of the microchip

Validation of the thermal code of RadTherm-IR, IR-Workbench, and F-TOM

Science.gov (United States)

Schwenger, Frédéric; Grossmann, Peter; Malaplate, Alain

2009-05-01

System assessment by image simulation requires synthetic scenarios that can be viewed by the device to be simulated. In addition to physical modeling of the camera, a reliable modeling of scene elements is necessary. Software products for modeling of target data in the IR should be capable of (i) predicting surface temperatures of scene elements over a long period of time and (ii) computing sensor views of the scenario. For such applications, FGAN-FOM acquired the software products RadTherm-IR (ThermoAnalytics Inc., Calumet, USA; IR-Workbench (OKTAL-SE, Toulouse, France). Inspection of the accuracy of simulation results by validation is necessary before using these products for applications. In the first step of validation, the performance of both "thermal solvers" was determined through comparison of the computed diurnal surface temperatures of a simple object with the corresponding values from measurements. CUBI is a rather simple geometric object with well known material parameters which makes it suitable for testing and validating object models in IR. It was used in this study as a test body. Comparison of calculated and measured surface temperature values will be presented, together with the results from the FGAN-FOM thermal object code F-TOM. In the second validation step, radiances of the simulated sensor views computed by RadTherm-IR and IR-Workbench will be compared with radiances retrieved from the recorded sensor images taken by the sensor that was simulated. Strengths and weaknesses of the models RadTherm-IR, IR-Workbench and F-TOM will be discussed.

An Automatic Cloud Detection Method for ZY-3 Satellite

Directory of Open Access Journals (Sweden)

CHEN Zhenwei

2015-03-01

Full Text Available Automatic cloud detection for optical satellite remote sensing images is a significant step in the production system of satellite products. For the browse images cataloged by ZY-3 satellite, the tree discriminate structure is adopted to carry out cloud detection. The image was divided into sub-images and their features were extracted to perform classification between clouds and grounds. However, due to the high complexity of clouds and surfaces and the low resolution of browse images, the traditional classification algorithms based on image features are of great limitations. In view of the problem, a prior enhancement processing to original sub-images before classification was put forward in this paper to widen the texture difference between clouds and surfaces. Afterwards, with the secondary moment and first difference of the images, the feature vectors were extended in multi-scale space, and then the cloud proportion in the image was estimated through comprehensive analysis. The presented cloud detection algorithm has already been applied to the ZY-3 application system project, and the practical experiment results indicate that this algorithm is capable of promoting the accuracy of cloud detection significantly.

High-contrast imaging in the cloud with klipReduce and Findr

Science.gov (United States)

Haug-Baltzell, Asher; Males, Jared R.; Morzinski, Katie M.; Wu, Ya-Lin; Merchant, Nirav; Lyons, Eric; Close, Laird M.

2016-08-01

Astronomical data sets are growing ever larger, and the area of high contrast imaging of exoplanets is no exception. With the advent of fast, low-noise detectors operating at 10 to 1000 Hz, huge numbers of images can be taken during a single hours-long observation. High frame rates offer several advantages, such as improved registration, frame selection, and improved speckle calibration. However, advanced image processing algorithms are computationally challenging to apply. Here we describe a parallelized, cloud-based data reduction system developed for the Magellan Adaptive Optics VisAO camera, which is capable of rapidly exploring tens of thousands of parameter sets affecting the Karhunen-Loève image processing (KLIP) algorithm to produce high-quality direct images of exoplanets. We demonstrate these capabilities with a visible wavelength high contrast data set of a hydrogen-accreting brown dwarf companion.

Evaluation of a cloud-based local-read paradigm for imaging evaluations in oncology clinical trials for lung cancer

International Nuclear Information System (INIS)

Sueoka-Aragane, Naoko; Kobayashi, Naomi; Bonnard, Eric; Charbonnier, Colette; Yamamichi, Junta; Mizobe, Hideaki; Kimura, Shinya

2015-01-01

Although tumor response evaluated with radiological imaging is frequently used as a primary endpoint in clinical trials, it is difficult to obtain precise results because of inter- and intra-observer differences. To evaluate usefulness of a cloud-based local-read paradigm implementing software solutions that standardize imaging evaluations among international investigator sites for clinical trials of lung cancer. Two studies were performed: KUMO I and KUMO I Extension. KUMO I was a pilot study aiming at demonstrating the feasibility of cloud implementation and identifying issues regarding variability of evaluations among sites. Chest CT scans at three time-points from baseline to progression, from 10 patients with lung cancer who were treated with EGFR tyrosine kinase inhibitors, were evaluated independently by two oncologists (Japan) and one radiologist (France), through a cloud-based software solution. The KUMO I Extension was performed based on the results of KUMO I. KUMO I showed discordance rates of 40% for target lesion selection, 70% for overall response at the first time-point, and 60% for overall response at the second time-point. Since the main reason for the discordance was differences in the selection of target lesions, KUMO I Extension added a cloud-based quality control service to achieve a consensus on the selection of target lesions, resulting in an improved rate of agreement of response evaluations. The study shows the feasibility of imaging evaluations at investigator sites, based on cloud services for clinical studies involving multiple international sites. This system offers a step forward in standardizing evaluations of images among widely dispersed sites

VENUS CLOUD MORPHOLOGY AND MOTIONS FROM GROUND-BASED IMAGES AT THE TIME OF THE AKATSUKI ORBIT INSERTION

Energy Technology Data Exchange (ETDEWEB)

Sánchez-Lavega, A.; Hueso, R.; Pérez-Hoyos, S.; Mendikoa, I.; Rojas, J. F. [Departamento de Física Aplicada I, Escuela de Ingeniería de Bilbao, Universidad del País Vasco UPV /EHU, Plaza Ingeniero Torres Quevedo, E-48013 Bilbao (Spain); Peralta, J.; Lee, Y. J. [Institute of Space and Astronautical Science (ISAS/JAXA), Sagamihara, Kanagawa (Japan); Gomez-Forrellad, J. M. [Fundació Observatori Esteve Duran, Montseny 46, E-08553 Seva, Barcelona (Spain); Horinouchi, T. [Faculty of Environment Earth Science, Hokkaido University, Hokkaido (Japan); Watanabe, S., E-mail: agustin.sanchez@ehu.es [Department of Cosmoscience, Hokkaido University, Hokkaido (Japan)

2016-12-10

We report Venus image observations around the two maximum elongations of the planet at 2015 June and October. From these images we describe the global atmospheric dynamics and cloud morphology in the planet before the arrival of JAXA’s Akatsuki mission on 2015 December 7. The majority of the images were acquired at ultraviolet wavelengths (380–410 nm) using small telescopes. The Venus dayside was also observed with narrowband filters at other wavelengths (890 nm, 725–950 nm, 1.435 μ m CO{sub 2} band) using the instrument PlanetCam-UPV/EHU at the 2.2 m telescope in Calar Alto Observatory. In all cases, the lucky imaging methodology was used to improve the spatial resolution of the images over the atmospheric seeing. During the April–June period, the morphology of the upper cloud showed an irregular and chaotic texture with a well-developed equatorial dark belt (afternoon hemisphere), whereas during October–December the dynamical regime was dominated by planetary-scale waves (Y-horizontal, C-reversed, and ψ -horizontal features) formed by long streaks, and banding suggesting more stable conditions. Measurements of the zonal wind velocity with cloud tracking in the latitude range from 50°N to 50°S shows agreement with retrievals from previous works.

FOREST Unbiased Galactic plane Imaging survey with the Nobeyama 45 m telescope (FUGIN): Molecular clouds toward W 33; possible evidence for a cloud-cloud collision triggering O star formation

Science.gov (United States)

Kohno, Mikito; Torii, Kazufumi; Tachihara, Kengo; Umemoto, Tomofumi; Minamidani, Tetsuhiro; Nishimura, Atsushi; Fujita, Shinji; Matsuo, Mitsuhiro; Yamagishi, Mitsuyoshi; Tsuda, Yuya; Kuriki, Mika; Kuno, Nario; Ohama, Akio; Hattori, Yusuke; Sano, Hidetoshi; Yamamoto, Hiroaki; Fukui, Yasuo

2018-05-01

We observed molecular clouds in the W 33 high-mass star-forming region associated with compact and extended H II regions using the NANTEN2 telescope as well as the Nobeyama 45 m telescope in the J = 1-0 transitions of 12CO, 13CO, and C18O as part of the FOREST Unbiased Galactic plane Imaging survey with the Nobeyama 45 m telescope (FUGIN) legacy survey. We detected three velocity components at 35 km s-1, 45 km s-1, and 58 km s-1. The 35 km s-1 and 58 km s-1 clouds are likely to be physically associated with W 33 because of the enhanced 12CO J = 3-2 to J = 1-0 intensity ratio as R_3-2/1-0} > 1.0 due to the ultraviolet irradiation by OB stars, and morphological correspondence between the distributions of molecular gas and the infrared and radio continuum emissions excited by high-mass stars. The two clouds show complementary distributions around W 33. The velocity separation is too large to be gravitationally bound, and yet not explained by expanding motion by stellar feedback. Therefore, we discuss whether a cloud-cloud collision scenario likely explains the high-mass star formation in W 33.

Comparison Between CCCM and CloudSat Radar-Lidar (RL) Cloud and Radiation Products

Science.gov (United States)

Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Sun-Mack, Sunny

2015-01-01

To enhance cloud properties, LaRC and CIRA developed each combination algorithm for obtained properties from passive, active and imager in A-satellite constellation. When comparing global cloud fraction each other, LaRC-produced CERES-CALIPSO-CloudSat-MODIS (CCCM) products larger low-level cloud fraction over tropic ocean, while CIRA-produced Radar-Lidar (RL) shows larger mid-level cloud fraction for high latitude region. The reason for different low-level cloud fraction is due to different filtering method of lidar-detected cloud layers. Meanwhile difference in mid-level clouds is occurred due to different priority of cloud boundaries from lidar and radar.

Cloud classification in a mediterranean location using radiation data and sky images

International Nuclear Information System (INIS)

Martinez-Chico, M.; Batlles, F.J.; Bosch, J.L.

2011-01-01

Knowledge regarding the solar radiation reaching the earth's surface and its geographical distribution is very important for the use of solar energy as a resource to produce electricity. Therefore, a proper assessment of available solar resource is particularly important to determine the placement and operation of solar thermal power plants. To perform this analysis correctly, it is necessary to determine the main factors influencing the radiation reaching the earth's surface, such as the earth's geometry, terrain, and atmospheric attenuation by gases, particles and clouds. Among these factors, it is important to emphasise the role of clouds as the main attenuating factor of radiation. Information about the amount and type of clouds present in the sky is therefore necessary to analyse both their attenuation levels and the prevalence of different sky conditions. Cloud cover is characterised according to attenuation levels, using the beam transmittance (k b , ratio of direct radiation incident on the surface to the extraterrestrial solar radiation) and hemispherical sky images. An analysis of the frequency and duration of each type of cloud cover blocking the sun's disk is also performed. Results show prevailing sky situations that make the studied area very suitable for the use of solar energy systems. -- Highlights: → Beam transmittance index k b have been used successfully to classify the cloud cover. → The proposed classification has been used to study a Mediterranean location in south-eastern Spain. → Percentage of cloudless/cloudy situations showed a good potential for solar energy applications in the studied area.

Ditching the Disc: The Effects of Cloud-Based Image Sharing on Department Efficiency and Report Turnaround Times in Mammography.

Science.gov (United States)

Morgan, Matthew B; Young, Elizabeth; Harada, Scott; Winkler, Nicole; Riegert, Joanna; Jones, Tony; Hu, Nan; Stein, Matthew

2017-12-01

In screening mammography, accessing prior examination images is crucial for accurate diagnosis and avoiding false-positives. When women visit multiple institutions for their screens, these "outside" examinations must be retrieved for comparison. Traditionally, prior images are obtained by faxing requests to other institutions and waiting for standard mail (film or CD-ROM), which can greatly delay report turnaround times. Recently, advancements in cloud-based image transfer technology have opened up more efficient options for examination transfer between institutions. The objective of this study was to evaluate the effect of cloud-based image transfer on mammography department workflow, time required to obtain prior images, and report turnaround times. Sixty screening examinations requiring prior images were placed into two groups (30 each). The control group used the standard institutional protocol for requesting prior images: faxing requests and waiting for mailed examinations. The experimental group used a cloud-based transfer for both requesting and receiving examinations. The mean number of days between examination request and examination receipt was measured for both groups and compared. The mean number of days from examination request to receipt was 6.08 days (SD 3.50) in the control group compared with 3.16 days (SD 3.95) in the experimental group. Using a cloud-based image transfer to obtain prior mammograms resulted in an average reduction of 2.92 days (P = .0361; 95% confidence interval 0.20-5.65) between examination request and receipt. This improvement in system efficiency is relevant for interpreting radiologists working to improve reporting times and for patients anxious to receive their mammography results. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

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

Directory of Open Access Journals (Sweden)

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.

RenderSelect: a Cloud Broker Framework for Cloud Renderfarm Services

OpenAIRE

Ruby, Annette J; Aisha, Banu W; Subash, Chandran P

2016-01-01

In the 3D studios the animation scene files undergo a process called as rendering, where the 3D wire frame models are converted into 3D photorealistic images. As the rendering process is both a computationally intensive and a time consuming task, the cloud services based rendering in cloud render farms is gaining popularity among the animators. Though cloud render farms offer many benefits, the animators hesitate to move from their traditional offline rendering to cloud services based render ...

Unveiling aerosol-cloud interactions - Part 1: Cloud contamination in satellite products enhances the aerosol indirect forcing estimate

Science.gov (United States)

Christensen, Matthew W.; Neubauer, David; Poulsen, Caroline A.; Thomas, Gareth E.; McGarragh, Gregory R.; Povey, Adam C.; Proud, Simon R.; Grainger, Roy G.

2017-11-01

Increased concentrations of aerosol can enhance the albedo of warm low-level cloud. Accurately quantifying this relationship from space is challenging due in part to contamination of aerosol statistics near clouds. Aerosol retrievals near clouds can be influenced by stray cloud particles in areas assumed to be cloud-free, particle swelling by humidification, shadows and enhanced scattering into the aerosol field from (3-D radiative transfer) clouds. To screen for this contamination we have developed a new cloud-aerosol pairing algorithm (CAPA) to link cloud observations to the nearest aerosol retrieval within the satellite image. The distance between each aerosol retrieval and nearest cloud is also computed in CAPA. Results from two independent satellite imagers, the Advanced Along-Track Scanning Radiometer (AATSR) and Moderate Resolution Imaging Spectroradiometer (MODIS), show a marked reduction in the strength of the intrinsic aerosol indirect radiative forcing when selecting aerosol pairs that are located farther away from the clouds (-0.28±0.26 W m-2) compared to those including pairs that are within 15 km of the nearest cloud (-0.49±0.18 W m-2). The larger aerosol optical depths in closer proximity to cloud artificially enhance the relationship between aerosol-loading, cloud albedo, and cloud fraction. These results suggest that previous satellite-based radiative forcing estimates represented in key climate reports may be exaggerated due to the inclusion of retrieval artefacts in the aerosol located near clouds.

Similarity maps and hierarchical clustering for annotating FT-IR spectral images.

Science.gov (United States)

Zhong, Qiaoyong; Yang, Chen; Großerüschkamp, Frederik; Kallenbach-Thieltges, Angela; Serocka, Peter; Gerwert, Klaus; Mosig, Axel

2013-11-20

Unsupervised segmentation of multi-spectral images plays an important role in annotating infrared microscopic images and is an essential step in label-free spectral histopathology. In this context, diverse clustering approaches have been utilized and evaluated in order to achieve segmentations of Fourier Transform Infrared (FT-IR) microscopic images that agree with histopathological characterization. We introduce so-called interactive similarity maps as an alternative annotation strategy for annotating infrared microscopic images. We demonstrate that segmentations obtained from interactive similarity maps lead to similarly accurate segmentations as segmentations obtained from conventionally used hierarchical clustering approaches. In order to perform this comparison on quantitative grounds, we provide a scheme that allows to identify non-horizontal cuts in dendrograms. This yields a validation scheme for hierarchical clustering approaches commonly used in infrared microscopy. We demonstrate that interactive similarity maps may identify more accurate segmentations than hierarchical clustering based approaches, and thus are a viable and due to their interactive nature attractive alternative to hierarchical clustering. Our validation scheme furthermore shows that performance of hierarchical two-means is comparable to the traditionally used Ward's clustering. As the former is much more efficient in time and memory, our results suggest another less resource demanding alternative for annotating large spectral images.

CloudSat-Based Assessment of GPM Microwave Imager Snowfall Observation Capabilities

Directory of Open Access Journals (Sweden)

Giulia Panegrossi

2017-12-01

Full Text Available The sensitivity of Global Precipitation Measurement (GPM Microwave Imager (GMI high-frequency channels to snowfall at higher latitudes (around 60°N/S is investigated using coincident CloudSat observations. The 166 GHz channel is highlighted throughout the study due to its ice scattering sensitivity and polarization information. The analysis of three case studies evidences the important combined role of total precipitable water (TPW, supercooled cloud water, and background surface composition on the brightness temperature (TB behavior for different snow-producing clouds. A regression tree statistical analysis applied to the entire GMI-CloudSat snowfall dataset indicates which variables influence the 166 GHz polarization difference (166 ∆TB and its relation to snowfall. Critical thresholds of various parameters (sea ice concentration (SIC, TPW, ice water path (IWP are established for optimal snowfall detection capabilities. The 166 ∆TB can identify snowfall events over land and sea when critical thresholds are exceeded (TPW > 3.6 kg·m−2, IWP > 0.24 kg·m−2 over land, and SIC > 57%, TPW > 5.1 kg·m−2 over sea. The complex combined 166 ∆TB-TB relationship at higher latitudes and the impact of supercooled water vertical distribution are also investigated. The findings presented in this study can be exploited to improve passive microwave snowfall detection algorithms.

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC).

Science.gov (United States)

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-01-01

This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (< 2%) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10%, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

Cloud detection, classification and motion estimation using geostationary satellite imagery for cloud cover forecast

International Nuclear Information System (INIS)

Escrig, H.; Batlles, F.J.; Alonso, J.; Baena, F.M.; Bosch, J.L.; Salbidegoitia, I.B.; Burgaleta, J.I.

2013-01-01

Considering that clouds are the greatest causes to solar radiation blocking, short term cloud forecasting can help power plant operation and therefore improve benefits. Cloud detection, classification and motion vector determination are key to forecasting sun obstruction by clouds. Geostationary satellites provide cloud information covering wide areas, allowing cloud forecast to be performed for several hours in advance. Herein, the methodology developed and tested in this study is based on multispectral tests and binary cross correlations followed by coherence and quality control tests over resulting motion vectors. Monthly synthetic surface albedo image and a method to reject erroneous correlation vectors were developed. Cloud classification in terms of opacity and height of cloud top is also performed. A whole-sky camera has been used for validation, showing over 85% of agreement between the camera and the satellite derived cloud cover, whereas error in motion vectors is below 15%. - Highlights: ► A methodology for detection, classification and movement of clouds is presented. ► METEOSAT satellite images are used to obtain a cloud mask. ► The prediction of cloudiness is estimated with 90% in overcast conditions. ► Results for partially covered sky conditions showed a 75% accuracy. ► Motion vectors are estimated from the clouds with a success probability of 86%

A New Algorithm for Detecting Cloud Height using OMPS/LP Measurements

Science.gov (United States)

Chen, Zhong; DeLand, Matthew; Bhartia, Pawan K.

2016-01-01

The Ozone Mapping and Profiler Suite Limb Profiler (OMPS/LP) ozone product requires the determination of cloud height for each event to establish the lower boundary of the profile for the retrieval algorithm. We have created a revised cloud detection algorithm for LP measurements that uses the spectral dependence of the vertical gradient in radiance between two wavelengths in the visible and near-IR spectral regions. This approach provides better discrimination between clouds and aerosols than results obtained using a single wavelength. Observed LP cloud height values show good agreement with coincident Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements.

Retrieval of Tropospheric Profiles from IR Emission Spectra: Field Experiment and Sensitivity Study

National Research Council Canada - National Science Library

Theriault, J

1993-01-01

.... The goal of this project was the retrieval of atmospheric temperature and water vapor profiles and possibly over relevant information on clouds and aerosol properties from high resolution IR emission...

ASTER cloud coverage reassessment using MODIS cloud mask products

Science.gov (United States)

Tonooka, Hideyuki; Omagari, Kunjuro; Yamamoto, Hirokazu; Tachikawa, Tetsushi; Fujita, Masaru; Paitaer, Zaoreguli

2010-10-01

In the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) Project, two kinds of algorithms are used for cloud assessment in Level-1 processing. The first algorithm based on the LANDSAT-5 TM Automatic Cloud Cover Assessment (ACCA) algorithm is used for a part of daytime scenes observed with only VNIR bands and all nighttime scenes, and the second algorithm based on the LANDSAT-7 ETM+ ACCA algorithm is used for most of daytime scenes observed with all spectral bands. However, the first algorithm does not work well for lack of some spectral bands sensitive to cloud detection, and the two algorithms have been less accurate over snow/ice covered areas since April 2008 when the SWIR subsystem developed troubles. In addition, they perform less well for some combinations of surface type and sun elevation angle. We, therefore, have developed the ASTER cloud coverage reassessment system using MODIS cloud mask (MOD35) products, and have reassessed cloud coverage for all ASTER archived scenes (>1.7 million scenes). All of the new cloud coverage data are included in Image Management System (IMS) databases of the ASTER Ground Data System (GDS) and NASA's Land Process Data Active Archive Center (LP DAAC) and used for ASTER product search by users, and cloud mask images are distributed to users through Internet. Daily upcoming scenes (about 400 scenes per day) are reassessed and inserted into the IMS databases in 5 to 7 days after each scene observation date. Some validation studies for the new cloud coverage data and some mission-related analyses using those data are also demonstrated in the present paper.

Day/night whole sky imagers for 24-h cloud and sky assessment: history and overview.

Science.gov (United States)

Shields, Janet E; Karr, Monette E; Johnson, Richard W; Burden, Art R

2013-03-10

A family of fully automated digital whole sky imagers (WSIs) has been developed at the Marine Physical Laboratory over many years, for a variety of research and military applications. The most advanced of these, the day/night whole sky imagers (D/N WSIs), acquire digital imagery of the full sky down to the horizon under all conditions from full sunlight to starlight. Cloud algorithms process the imagery to automatically detect the locations of cloud for both day and night. The instruments can provide absolute radiance distribution over the full radiance range from starlight through daylight. The WSIs were fielded in 1984, followed by the D/N WSIs in 1992. These many years of experience and development have resulted in very capable instruments and algorithms that remain unique. This article discusses the history of the development of the D/N WSIs, system design, algorithms, and data products. The paper cites many reports with more detailed technical documentation. Further details of calibration, day and night algorithms, and cloud free line-of-sight results will be discussed in future articles.

Atmospheric Polarization Imaging with Variable Aerosols, Clouds, and Surface Albedo

Science.gov (United States)

2013-07-01

values found in this region only during episodes of intense wildfire smoke. Detailed analysis of the aerosols in this smoke plume and their effect...Continuous outdoor operation of an all-sky polarization imager,” Proc. SPIE 7672 (Polarization: Measurement, Analysis , and Remote Sensing IX), 76720A-1-7, 7...Pust, “ Lunar corona in ice wave cloud,” 10th International Meeting on Light and Color in Nature, St. Mary’s College of Maryland, 16-20 June 2010. 2

Effect of cyclosporin A administration on the biodistribution and multipinhole {mu}SPECT imaging of [{sup 123}I]R91150 in rodent brain

Energy Technology Data Exchange (ETDEWEB)

Blanckaert, P.; Burvenich, I.; Bruyne, S. de; Moerman, L.; Wyffels, L.; Vos, F. de [Faculty of Pharmaceutical Sciences, Ghent University, Laboratory for Radiopharmacy, Gent (Belgium); Staelens, S. [Ghent University - IBBT, MEDISIP, Faculty of Engineering, Gent (Belgium)

2009-03-15

P-glycoprotein (Pgp) is an efflux protein found amongst other locations in the blood-brain barrier. It is important to investigate the effect of Pgp modulation on clinically used brain tracers, because brain uptake of the tracer can be altered by blocking of the Pgp efflux transporter. The function of Pgp can be blocked with cyclosporin A. We investigated the effect of cyclosporin A administration on the biodistribution of [{sup 123}I]R91150 in rodents, and the effect of Pgp blocking on the quality of multipinhole {mu}SPECT imaging with [{sup 123}I]R91150. The influence of increasing doses of cyclosporin A on the brain uptake of [{sup 123}I]R91150 was investigated in NMRI mice. A biodistribution study with [{sup 123}I]R91150 was performed in male Sprague-Dawley rats pretreated with cyclosporin A and not pretreated. Brain uptake of [{sup 123}I]R91150 after cyclosporin A injection was compared to the brain uptake in untreated animals, and a displacement study with ketanserin was performed in both groups. A multipinhole {mu}SPECT brain imaging study was also performed using a Milabs U-SPECT-II camera in male Sprague-Dawley rats. To exclude the effect of possible metabolites, a metabolite study was also performed. At the highest cyclosporin A dose (50 mg/kg), a sevenfold increase in brain radioactivity concentration was observed in NMRI mice. Also, a dose-response relationship was established between the dose of cyclosporin A and the brain uptake of [{sup 123}I]R91150 in mice. Compared to the control group, a five-fold increase in [{sup 123}I]R91150 radioactivity concentration was observed in the brain of Sprague-Dawley rats after cyclosporin A treatment (50 mg/kg). Radioactivity concentration in the frontal cortex increased from 0.24{+-}0.0092 to 1.58{+-}0.097% injected dose per gram of tissue after treatment with cyclosporin A (at the 1-h time-point). Blood radioactivity concentrations did not increase to the same extent. The cortical activity was displaced by

Megahertz rate, volumetric imaging of bubble clouds in sonothrombolysis using a sparse hemispherical receiver array

Science.gov (United States)

Acconcia, Christopher N.; Jones, Ryan M.; Goertz, David E.; O'Reilly, Meaghan A.; Hynynen, Kullervo

2017-09-01

It is well established that high intensity focused ultrasound can be used to disintegrate clots. This approach has the potential to rapidly and noninvasively resolve clot causing occlusions in cardiovascular diseases such as deep vein thrombosis (DVT). However, lack of an appropriate treatment monitoring tool is currently a limiting factor in its widespread adoption. Here we conduct cavitation imaging with a large aperture, sparse hemispherical receiver array during sonothrombolysis with multi-cycle burst exposures (0.1 or 1 ms burst lengths) at 1.51 MHz. It was found that bubble cloud generation on imaging correlated with the locations of clot degradation, as identified with high frequency (30 MHz) ultrasound following exposures. 3D images could be formed at integration times as short as 1 µs, revealing the initiation and rapid development of cavitation clouds. Equating to megahertz frame rates, this is an order of magnitude faster than any other imaging technique available for in vivo application. Collectively, these results suggest that the development of a device to perform DVT therapy procedures would benefit greatly from the integration of receivers tailored to bubble activity imaging.

Fluorenyl benzothiadiazole and benzoselenadiazole near-IR fluorescent probes for two-photon fluorescence imaging (Conference Presentation)

Science.gov (United States)

Belfield, Kevin D.; Yao, Sheng; Kim, Bosung; Yue, Xiling

2016-03-01

Imaging biological samples with two-photon fluorescence (2PF) microscopy has the unique advantage of resulting high contrast 3D resolution subcellular image that can reach up to several millimeters depth. 2PF probes that absorb and emit at near IR region need to be developed. Two-photon excitation (2PE) wavelengths are less concerned as 2PE uses wavelengths doubles the absorption wavelength of the probe, which means 2PE wavelengths for probes even with absorption at visible wavelength will fall into NIR region. Therefore, probes that fluoresce at near IR region with high quantum yields are needed. A series of dyes based on 5-thienyl-2, 1, 3-benzothiadiazole and 5-thienyl-2, 1, 3-benzoselenadiazole core were synthesized as near infrared two-photon fluorophores. Fluorescence maxima wavelengths as long as 714 nm and fluorescence quantum yields as high as 0.67 were achieved. The fluorescence quantum yields of the dyes were nearly constant, regardless of solvents polarity. These diazoles exhibited large Stokes shift (GM), and high two-photon fluorescence figure of merit (FM , 1.04×10-2 GM). Cells incubated on a 3D scaffold with one of the new probes (encapsulated in Pluronic micelles) exhibited bright fluorescence, enabling 3D two-photon fluorescence imaging to a depth of 100 µm.

Comparison of Cloud Properties from CALIPSO-CloudSat and Geostationary Satellite Data

Science.gov (United States)

Nguyen, L.; Minnis, P.; Chang, F.; Winker, D.; Sun-Mack, S.; Spangenberg, D.; Austin, R.

2007-01-01

Cloud properties are being derived in near-real time from geostationary satellite imager data for a variety of weather and climate applications and research. Assessment of the uncertainties in each of the derived cloud parameters is essential for confident use of the products. Determination of cloud amount, cloud top height, and cloud layering is especially important for using these real -time products for applications such as aircraft icing condition diagnosis and numerical weather prediction model assimilation. Furthermore, the distribution of clouds as a function of altitude has become a central component of efforts to evaluate climate model cloud simulations. Validation of those parameters has been difficult except over limited areas where ground-based active sensors, such as cloud radars or lidars, have been available on a regular basis. Retrievals of cloud properties are sensitive to the surface background, time of day, and the clouds themselves. Thus, it is essential to assess the geostationary satellite retrievals over a variety of locations. The availability of cloud radar data from CloudSat and lidar data from CALIPSO make it possible to perform those assessments over each geostationary domain at 0130 and 1330 LT. In this paper, CloudSat and CALIPSO data are matched with contemporaneous Geostationary Operational Environmental Satellite (GOES), Multi-functional Transport Satellite (MTSAT), and Meteosat-8 data. Unlike comparisons with cloud products derived from A-Train imagers, this study considers comparisons of nadir active sensor data with off-nadir retrievals. These matched data are used to determine the uncertainties in cloud-top heights and cloud amounts derived from the geostationary satellite data using the Clouds and the Earth s Radiant Energy System (CERES) cloud retrieval algorithms. The CERES multi-layer cloud detection method is also evaluated to determine its accuracy and limitations in the off-nadir mode. The results will be useful for

Cloud occurrences and cloud radiative effects (CREs) from CERES-CALIPSO-CloudSat-MODIS (CCCM) and CloudSat radar-lidar (RL) products

Science.gov (United States)

Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Winker, David; L'Ecuyer, Tristan; Mace, Gerald G.; Painemal, David; Sun-Mack, Sunny; Chen, Yan; Miller, Walter F.

2017-08-01

Two kinds of cloud products obtained from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, and Moderate Resolution Imaging Spectroradiometer (MODIS) are compared and analyzed in this study: Clouds and the Earth's Radiant Energy System (CERES)-CALIPSO-CloudSat-MODIS (CCCM) product and CloudSat radar-lidar products such as GEOPROF-LIDAR and FLXHR-LIDAR. Compared to GEOPROF-LIDAR, low-level (40°). The difference occurs when hydrometeors are detected by CALIPSO lidar but are undetected by CloudSat radar. In the comparison of cloud radiative effects (CREs), global mean differences between CCCM and FLXHR-LIDAR are mostly smaller than 5 W m-2, while noticeable regional differences are found. For example, CCCM shortwave (SW) and longwave (LW) CREs are larger than FXLHR-LIDAR along the west coasts of Africa and America because the GEOPROF-LIDAR algorithm misses shallow marine boundary layer clouds. In addition, FLXHR-LIDAR SW CREs are larger than the CCCM counterpart over tropical oceans away from the west coasts of America. Over midlatitude storm-track regions, CCCM SW and LW CREs are larger than the FLXHR-LIDAR counterpart.

Effects of Low Carbohydrate High Protein (LCHP) diet on atherosclerotic plaque phenotype in ApoE/LDLR-/- mice: FT-IR and Raman imaging.

Science.gov (United States)

Wrobel, T P; Marzec, K M; Chlopicki, S; Maślak, E; Jasztal, A; Franczyk-Żarów, M; Czyżyńska-Cichoń, I; Moszkowski, T; Kostogrys, R B; Baranska, M

2015-09-22

Low Carbohydrate High Protein (LCHP) diet displays pro-atherogenic effects, however, the exact mechanisms involved are still unclear. Here, with the use of vibrational imaging, such as Fourier transform infrared (FT-IR) and Raman (RS) spectroscopies, we characterize biochemical content of plaques in Brachiocephalic Arteries (BCA) from ApoE/LDLR(-/-) mice fed LCHP diet as compared to control, recomended by American Institute of Nutrition, AIN diet. FT-IR images were taken from 6-10 sections of BCA from each mice and were complemented with RS measurements with higher spatial resolution of chosen areas of plaque sections. In aortic plaques from LCHP fed ApoE/LDLR(-/-) mice, the content of cholesterol and cholesterol esters was increased, while that of proteins was decreased as evidenced by global FT-IR analysis. High resolution imaging by RS identified necrotic core/foam cells, lipids (including cholesterol crystals), calcium mineralization and fibrous cap. The decreased relative thickness of the outer fibrous cap and the presence of buried caps were prominent features of the plaques in ApoE/LDLR(-/-) mice fed LCHP diet. In conclusion, FT-IR and Raman-based imaging provided a complementary insight into the biochemical composition of the plaque suggesting that LCHP diet increased plaque cholesterol and cholesterol esters contents of atherosclerotic plaque, supporting the cholesterol-driven pathogenesis of LCHP-induced atherogenesis.

High-resolution imaging and target designation through clouds or smoke

Science.gov (United States)

Perry, Michael D.

2003-01-01

A method and system of combining gated intensifiers and advances in solid-state, short-pulse laser technology, compact systems capable of producing high resolution (i.e., approximately less than 20 centimeters) optical images through a scattering medium such as dense clouds, fog, smoke, etc. may be achieved from air or ground based platforms. Laser target designation through a scattering medium is also enabled by utilizing a short pulse illumination laser and a relatively minor change to the detectors on laser guided munitions.

Surface enhanced imaging and IR spectroscopy of the biological cells on the nanostructured gold film

Directory of Open Access Journals (Sweden)

G.I. Dovbeshko

2017-07-01

Full Text Available New approach for optical imaging, structural study and cell cultivation based on the effect of the enhancement of optical signals from biomolecules and biological cells near nanostructured rough gold surface is proposed. The surface enhanced IR absorption (SEIRA spectroscopy and confocal microscopy experiments were made using the culture of SPEV (porcine embryonic kidney epithelium transplantable line and fibroblast cells, cultivated and/or adsorbed on the gold substrate. The SEIRA spectra registered from monolayer of the SPEV cells cultivated on the rough gold showed a low frequency shift of about 2 to 7 cm 1 for the most characteristic IR vibrations, compared with those adsorbed from suspension on the same substrate. An enhancement factor of 15…30 was obtained for different molecular vibrations. The confocal microscopy contrast images of the SPEV cells on rough gold substrate were obtained in laser fluorescence mode. This approach opens new possibilities for visualization of the living cells in vivo without staining. The fluorescence of the rough gold surfaces and effects responsible for our findings have been discussed.

Signal and image processing algorithm performance in a virtual and elastic computing environment

Science.gov (United States)

Bennett, Kelly W.; Robertson, James

2013-05-01

The U.S. Army Research Laboratory (ARL) supports the development of classification, detection, tracking, and localization algorithms using multiple sensing modalities including acoustic, seismic, E-field, magnetic field, PIR, and visual and IR imaging. Multimodal sensors collect large amounts of data in support of algorithm development. The resulting large amount of data, and their associated high-performance computing needs, increases and challenges existing computing infrastructures. Purchasing computer power as a commodity using a Cloud service offers low-cost, pay-as-you-go pricing models, scalability, and elasticity that may provide solutions to develop and optimize algorithms without having to procure additional hardware and resources. This paper provides a detailed look at using a commercial cloud service provider, such as Amazon Web Services (AWS), to develop and deploy simple signal and image processing algorithms in a cloud and run the algorithms on a large set of data archived in the ARL Multimodal Signatures Database (MMSDB). Analytical results will provide performance comparisons with existing infrastructure. A discussion on using cloud computing with government data will discuss best security practices that exist within cloud services, such as AWS.

Wide-angle imaging LIDAR (WAIL): a ground-based instrument for monitoring the thickness and density of optically thick clouds

International Nuclear Information System (INIS)

Love, Steven P.; Davis, A.B.; Rohde, C.A.; Ho, Cheng

2001-01-01

Traditional lidar provides little information on dense clouds beyond the range to their base (ceilometry), due to their extreme opacity. At most optical wavelengths, however, laser photons are not absorbed but merely scattered out of the beam, and thus eventually escape the cloud via multiple scattering, producing distinctive extended space- and time-dependent patterns which are, in essence, the cloud's radiative Green functions. These Green functions, essentially 'movies' of the time evolution of the spatial distribution of escaping light, are the primary data products of a new type of lidar: Wide Angle Imaging Lidar (WAIL). WAIL data can be used to infer both optical depth and physical thickness of clouds, and hence the cloud liquid water content. The instrumental challenge is to accommodate a radiance field varying over many orders of magnitude and changing over widely varying time-scales. Our implementation uses a high-speed microchannel plate/crossed delay line imaging detector system with a 60-degree full-angle field of view, and a 532 nm doubled Nd:YAG laser. Nighttime field experiments testing various solutions to this problem show excellent agreement with diffusion theory, and retrievals yield plausible values for the optical and geometrical parameters of the observed cloud decks.

Studies of dynamics of electron clouds in STAR silicon drift detectors

CERN Document Server

Bellwied, R; Brandon, N; Caines, H; Chen, W; Dimassimo, D; Dyke, H; Hall, J R; Hardtke, D; Hoffmann, G W; Humanic, T J; Kotova, A I; Kotov, I V; Kraner, H W; Li, Z; Lynn, D; Middelkamp, P; Ott, G; Pandey, S U; Pruneau, C A; Rykov, V L; Schambach, J; Sedlmeir, J; Sugarbaker, E R; Takahashi, J; Wilson, W K

2000-01-01

The dynamics of electrons generated in silicon drift detectors was studied using an IR LED. Electrons were generated at different drift distances. In this way, the evolution of the cloud as a function of drift time was measured. Two methods were used to measure the cloud size. The method of cumulative functions was used to extract the electron cloud profiles. Another method obtains the cloud width from measurements of the charge collected on a single anode as a function of coordinate of the light spot. The evolution of the electron cloud width with drift time is compared with theoretical calculations. Experimental results agreed with theoretical expectations.

OPTICAL AND NEAR-INFRARED SHOCKS IN THE L988 CLOUD COMPLEX

International Nuclear Information System (INIS)

Walawender, J.; Reipurth, B.; Bally, J.

2013-01-01

We have searched the Lynds 988 dark cloud complex for optical (Hα and [S II]) and near-IR (H 2 2.12 μm) shocks from protostellar outflows. We find 20 new Herbig-Haro objects and 6 new H 2 shocks (MHO objects), 3 of which are cross detections. Using the morphology in the optical and near-IR, we connect several of these shocks into at least five distinct outflow systems and identify their source protostars from catalogs of infrared sources. Two outflows in the cloud, from IRAS 21014+5001 and IRAS 21007+4951, are in excess of 1 pc in length. The IRAS 21007+4951 outflow has carved a large cavity in the cloud through which background stars can be seen. Also, we have found an optical shock which is the counterflow to the previously discovered ''northwest outflow'' from LkHα 324SE

Multi-provider architecture for cloud outsourcing of medical imaging repositories.

Science.gov (United States)

Godinho, Tiago Marques; Bastião Silva, Luís A; Costa, Carlos; Oliveira, José Luís

2014-01-01

Over the last few years, the extended usage of medical imaging procedures has raised the medical community attention towards the optimization of their workflows. More recently, the federation of multiple institutions into a seamless distribution network has brought hope of increased quality healthcare services along with more efficient resource management. As a result, medical institutions are constantly looking for the best infrastructure to deploy their imaging archives. In this scenario, public cloud infrastructures arise as major candidates, as they offer elastic storage space, optimal data availability without great requirements of maintenance costs or IT personnel, in a pay-as-you-go model. However, standard methodologies still do not take full advantage of outsourced archives, namely because their integration with other in-house solutions is troublesome. This document proposes a multi-provider architecture for integration of outsourced archives with in-house PACS resources, taking advantage of foreign providers to store medical imaging studies, without disregarding security. It enables the retrieval of images from multiple archives simultaneously, improving performance, data availability and avoiding the vendor-locking problem. Moreover it enables load balancing and cache techniques.

A Routing Mechanism for Cloud Outsourcing of Medical Imaging Repositories.

Science.gov (United States)

Godinho, Tiago Marques; Viana-Ferreira, Carlos; Bastião Silva, Luís A; Costa, Carlos

2016-01-01

Web-based technologies have been increasingly used in picture archive and communication systems (PACS), in services related to storage, distribution, and visualization of medical images. Nowadays, many healthcare institutions are outsourcing their repositories to the cloud. However, managing communications between multiple geo-distributed locations is still challenging due to the complexity of dealing with huge volumes of data and bandwidth requirements. Moreover, standard methodologies still do not take full advantage of outsourced archives, namely because their integration with other in-house solutions is troublesome. In order to improve the performance of distributed medical imaging networks, a smart routing mechanism was developed. This includes an innovative cache system based on splitting and dynamic management of digital imaging and communications in medicine objects. The proposed solution was successfully deployed in a regional PACS archive. The results obtained proved that it is better than conventional approaches, as it reduces remote access latency and also the required cache storage space.

Influence of Desorption Conditions on Analyte Sensitivity and Internal Energy in Discrete Tissue or Whole Body Imaging by IR-MALDESI

Science.gov (United States)

Rosen, Elias P.; Bokhart, Mark T.; Ghashghaei, H. Troy; Muddiman, David C.

2015-06-01

Analyte signal in a laser desorption/postionization scheme such as infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) is strongly coupled to the degree of overlap between the desorbed plume of neutral material from a sample and an orthogonal electrospray. In this work, we systematically examine the effect of desorption conditions on IR-MALDESI response to pharmaceutical drugs and endogenous lipids in biological tissue using a design of experiments approach. Optimized desorption conditions have then been used to conduct an untargeted lipidomic analysis of whole body sagittal sections of neonate mouse. IR-MALDESI response to a wide range of lipid classes has been demonstrated, with enhanced lipid coverage received by varying the laser wavelength used for mass spectrometry imaging (MSI). Targeted MS2 imaging (MS2I) of an analyte, cocaine, deposited beneath whole body sections allowed determination of tissue-specific ion response factors, and CID fragments of cocaine were monitored to comment on wavelength-dependent internal energy deposition based on the "survival yield" method.

Non-invasive thermal IR detection of breast tumor development in vivo

Science.gov (United States)

Case, Jason R.; Young, Madison A.; Dréau, D.; Trammell, Susan R.

2015-03-01

Lumpectomy coupled with radiation therapy and/or chemotherapy comprises the treatment of breast cancer for many patients. We are developing an enhanced thermal IR imaging technique that can be used in real-time to guide tissue excision during a lumpectomy. This novel enhanced thermal imaging method is a combination of IR imaging (8- 10 μm) and selective heating of blood (~0.5 °C) relative to surrounding water-rich tissue using LED sources at low powers. Post-acquisition processing of these images highlights temporal changes in temperature and is sensitive to the presence of vascular structures. In this study, fluorescent and enhanced thermal imaging modalities were used to estimate breast cancer tumor volumes as a function of time in 19 murine subjects over a 30-day study period. Tumor volumes calculated from fluorescent imaging follow an exponential growth curve for the first 22 days of the study. Cell necrosis affected the tumor volume estimates based on the fluorescent images after Day 22. The tumor volumes estimated from enhanced thermal imaging show exponential growth over the entire study period. A strong correlation was found between tumor volumes estimated using fluorescent imaging and the enhanced IR images, indicating that enhanced thermal imaging is capable monitoring tumor growth. Further, the enhanced IR images reveal a corona of bright emission along the edges of the tumor masses. This novel IR technique could be used to estimate tumor margins in real-time during surgical procedures.

Feeding People's Curiosity: Leveraging the Cloud for Automatic Dissemination of Mars Images

Science.gov (United States)

Knight, David; Powell, Mark

2013-01-01

Smartphones and tablets have made wireless computing ubiquitous, and users expect instant, on-demand access to information. The Mars Science Laboratory (MSL) operations software suite, MSL InterfaCE (MSLICE), employs a different back-end image processing architecture compared to that of the Mars Exploration Rovers (MER) in order to better satisfy modern consumer-driven usage patterns and to offer greater server-side flexibility. Cloud services are a centerpiece of the server-side architecture that allows new image data to be delivered automatically to both scientists using MSLICE and the general public through the MSL website (http://mars.jpl.nasa.gov/msl/).

Photometric Calibration of the Barium Cloud Image in a Space Active Experiment: Determining the Release Efficiency

International Nuclear Information System (INIS)

Xie Liang-Hai; Li Lei; Wang Jing-Dong; Tao Ran; Cheng Bing-Jun; Zhang Yi-Teng

2014-01-01

The barium release experiment is an effective method to explore the near-earth environment and to study all kinds of space physics processes. The first space barium release experiment in China was successfully carried out by a sounding rocket on April 5, 2013. This work is devoted to calculating the release efficiency of the barium release by analyzing the optical image observed during the experiment. First, we present a method to calibrate the images grey value of barium cloud with the reference stars to obtain the radiant fluxes at different moments. Then the release efficiency is obtained by a curve fitting with the theoretical evolution model of barium cloud. The calculated result is basically consistent with the test value on ground

Point Cloud Based Change Detection - an Automated Approach for Cloud-based Services

Science.gov (United States)

Collins, Patrick; Bahr, Thomas

2016-04-01

The fusion of stereo photogrammetric point clouds with LiDAR data or terrain information derived from SAR interferometry has a significant potential for 3D topographic change detection. In the present case study latest point cloud generation and analysis capabilities are used to examine a landslide that occurred in the village of Malin in Maharashtra, India, on 30 July 2014, and affected an area of ca. 44.000 m2. It focuses on Pléiades high resolution satellite imagery and the Airbus DS WorldDEMTM as a product of the TanDEM-X mission. This case study was performed using the COTS software package ENVI 5.3. Integration of custom processes and automation is supported by IDL (Interactive Data Language). Thus, ENVI analytics is running via the object-oriented and IDL-based ENVITask API. The pre-event topography is represented by the WorldDEMTM product, delivered with a raster of 12 m x 12 m and based on the EGM2008 geoid (called pre-DEM). For the post-event situation a Pléiades 1B stereo image pair of the AOI affected was obtained. The ENVITask "GeneratePointCloudsByDenseImageMatching" was implemented to extract passive point clouds in LAS format from the panchromatic stereo datasets: • A dense image-matching algorithm is used to identify corresponding points in the two images. • A block adjustment is applied to refine the 3D coordinates that describe the scene geometry. • Additionally, the WorldDEMTM was input to constrain the range of heights in the matching area, and subsequently the length of the epipolar line. The "PointCloudFeatureExtraction" task was executed to generate the post-event digital surface model from the photogrammetric point clouds (called post-DEM). Post-processing consisted of the following steps: • Adding the geoid component (EGM 2008) to the post-DEM. • Pre-DEM reprojection to the UTM Zone 43N (WGS-84) coordinate system and resizing. • Subtraction of the pre-DEM from the post-DEM. • Filtering and threshold based classification of

New infrared observations of IRS 1, IRS 3, and the adjacent nebula in the OMC-2 cluster

International Nuclear Information System (INIS)

Pendelton, Y.; Werner, M.; Dinerstein, H.

1984-01-01

Recent reports show that near infrared reflection nebulae are often observed around embedded protostellar objects. New observations are here reported of the infrared cluster of low luminosity protostars in Orion Molecular Cloud 2 (OMC2). It has been determined that the asymmetric distribution of the extended emission seen about IRS1 is in fact another infrared reflection nebula. Observations of near infrared polarimetry, photometry, and spectrophotometry were carried out at the NASA Infrared Telescope Facility October 1982 and January 1983. (author)

Classification of Clouds and Deep Convection from GEOS-5 Using Satellite Observations

Science.gov (United States)

Putman, William; Suarez, Max

2010-01-01

With the increased resolution of global atmospheric models and the push toward global cloud resolving models, the resemblance of model output to satellite observations has become strikingly similar. As we progress with our adaptation of the Goddard Earth Observing System Model, Version 5 (GEOS-5) as a high resolution cloud system resolving model, evaluation of cloud properties and deep convection require in-depth analysis beyond a visual comparison. Outgoing long-wave radiation (OLR) provides a sufficient comparison with infrared (IR) satellite imagery to isolate areas of deep convection. We have adopted a binning technique to generate a series of histograms for OLR which classify the presence and fraction of clear sky versus deep convection in the tropics that can be compared with a similar analyses of IR imagery from composite Geostationary Operational Environmental Satellite (GOES) observations. We will present initial results that have been used to evaluate the amount of deep convective parameterization required within the model as we move toward cloud system resolving resolutions of 10- to 1-km globally.

Cloud computing for radiologists

OpenAIRE

Amit T Kharat; Amjad Safvi; S S Thind; Amarjit Singh

2012-01-01

Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as...

Into the Darkness: Interstellar Extinction Near the Cepheus OB3 Molecular Cloud

Science.gov (United States)

Fitzpatrick, Edward L.; Jacklin, S.; Massa, D.

2014-01-01

We present the results of a followup investigation to a study performed by Massa and Savage (1984, ApJ, 279, 310) of the properties of UV interstellar extinction in the region of the Cepheus OB3 molecular cloud. That study was performed using UV photometry and spectro-photometry from the ANS and IUE satellites. We have extended this study into the IR, utilizing the uniform database of IR photometry available from the 2MASS project. This is a part of a larger program whose goal is to study the properties of extinction in localized regions, where we hope to find clues to dust grain growth and destruction processes through spatial correlations of extinction with distinct environmental properties. Similarly to Massa and Savage’s UV results, we find that the IR extinction properties on the Cepheus OB3 region vary systematically with the apparent proximity of the target stars to the molecular cloud. We also find that the UV extinction and the IR extinction are crudely correlated. The methodology leading to these results and their implications are discussed.

Cloud-based Networked Visual Servo Control

DEFF Research Database (Denmark)

Wu, Haiyan; Lu, Lei; Chen, Chih-Chung

2013-01-01

, which integrates networked computational resources for cloud image processing, is considered in this article. The main contributions of this article are i) a real-time transport protocol for transmitting large volume image data on a cloud computing platform, which enables high sampling rate visual...

Infrared polarimetry of the reflection nebula near L 1551 IRS 5

Energy Technology Data Exchange (ETDEWEB)

Nagata, Tetsuya; Yamashita, Takuya; Sato, Shuji; Suzuki, Hiro; Hough, J H; Garden, R; Gatley, I

1986-11-01

The K-band polarization has been measured in the region extending 30 arcsec to the SW of L 1551 IRS5. The degree of polarization is exceptionally high, reaching approx. 67 per cent. The large polarizations and the azimuthal pattern of the position angles are attributed to scattering of infrared radiation from IRS5 by dust grains. The infrared brightness distribution resembles that of the optical nebulosity. It is proposed that infrared scattering occurs at the 'walls' of a cavity formed by the interaction of stellar winds with the ambient cloud.

Absorption of solar radiation in broken clouds

Energy Technology Data Exchange (ETDEWEB)

Zuev, V.E.; Titov, G.A.; Zhuravleva, T.B. [Institute of Atmospheric Optics, Tomsk (Russian Federation)

1996-04-01

It is recognized now that the plane-parallel model unsatisfactorily describes the transfer of radiation through broken clouds and that, consequently, the radiation codes of general circulation models (GCMs) must be refined. However, before any refinement in a GCM code is made, it is necessary to investigate the dependence of radiative characteristics on the effects caused by the random geometry of cloud fields. Such studies for mean fluxes of downwelling and upwelling solar radiation in the visible and near-infrared (IR) spectral range were performed by Zuev et al. In this work, we investigate the mean spectral and integrated absorption of solar radiation by broken clouds (in what follows, the term {open_quotes}mean{close_quotes} will be implied but not used, for convenience). To evaluate the potential effect of stochastic geometry, we will compare the absorption by cumulus (0.5 {le} {gamma} {le} 2) to that by equivalent stratus ({gamma} <<1) clouds; here {gamma} = H/D, H is the cloud layer thickness and D the characteristic horizontal cloud size. The equivalent stratus clouds differ from cumulus only in the aspect ratio {gamma}, all the other parameters coinciding.

OPTICAL AND NEAR-INFRARED SHOCKS IN THE L988 CLOUD COMPLEX

Energy Technology Data Exchange (ETDEWEB)

Walawender, J. [Subaru Telescope, National Astronomical Observatory of Japan, Hilo, HI 96720 (United States); Reipurth, B. [Institute for Astronomy, University of Hawaii at Manoa, Hilo, HI 96720 (United States); Bally, J., E-mail: joshw@naoj.org [Center for Astrophysics and Space Astronomy, University of Colorado, Boulder, CO 80309 (United States)

2013-09-15

We have searched the Lynds 988 dark cloud complex for optical (H{alpha} and [S II]) and near-IR (H{sub 2} 2.12 {mu}m) shocks from protostellar outflows. We find 20 new Herbig-Haro objects and 6 new H{sub 2} shocks (MHO objects), 3 of which are cross detections. Using the morphology in the optical and near-IR, we connect several of these shocks into at least five distinct outflow systems and identify their source protostars from catalogs of infrared sources. Two outflows in the cloud, from IRAS 21014+5001 and IRAS 21007+4951, are in excess of 1 pc in length. The IRAS 21007+4951 outflow has carved a large cavity in the cloud through which background stars can be seen. Also, we have found an optical shock which is the counterflow to the previously discovered ''northwest outflow'' from LkH{alpha} 324SE.

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

Science.gov (United States)

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

2017-07-01

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

Composite multi-lobe descriptor for cross spectral face recognition: matching active IR to visible light images

Science.gov (United States)

Cao, Zhicheng; Schmid, Natalia A.

2015-05-01

Matching facial images across electromagnetic spectrum presents a challenging problem in the field of biometrics and identity management. An example of this problem includes cross spectral matching of active infrared (IR) face images or thermal IR face images against a dataset of visible light images. This paper describes a new operator named Composite Multi-Lobe Descriptor (CMLD) for facial feature extraction in cross spectral matching of near-infrared (NIR) or short-wave infrared (SWIR) against visible light images. The new operator is inspired by the design of ordinal measures. The operator combines Gaussian-based multi-lobe kernel functions, Local Binary Pattern (LBP), generalized LBP (GLBP) and Weber Local Descriptor (WLD) and modifies them into multi-lobe functions with smoothed neighborhoods. The new operator encodes both the magnitude and phase responses of Gabor filters. The combining of LBP and WLD utilizes both the orientation and intensity information of edges. Introduction of multi-lobe functions with smoothed neighborhoods further makes the proposed operator robust against noise and poor image quality. Output templates are transformed into histograms and then compared by means of a symmetric Kullback-Leibler metric resulting in a matching score. The performance of the multi-lobe descriptor is compared with that of other operators such as LBP, Histogram of Oriented Gradients (HOG), ordinal measures, and their combinations. The experimental results show that in many cases the proposed method, CMLD, outperforms the other operators and their combinations. In addition to different infrared spectra, various standoff distances from close-up (1.5 m) to intermediate (50 m) and long (106 m) are also investigated in this paper. Performance of CMLD is evaluated for of each of the three cases of distances.

Mid-IR Imaging: Upconversion imager improves IR gas sensing

DEFF Research Database (Denmark)

Sahlberg, Anna-Lena; Li, Zhongshan; Høgstedt, Lasse

2014-01-01

A nonlinear upconversion detector shows near-shot-noise-limited performance and compares favorably—while adding additional imaging information—to conventional cryogenic detectors in the measurement of trace-level gases at atmospheric pressure....

High resolution depth reconstruction from monocular images and sparse point clouds using deep convolutional neural network

Science.gov (United States)

Dimitrievski, Martin; Goossens, Bart; Veelaert, Peter; Philips, Wilfried

2017-09-01

Understanding the 3D structure of the environment is advantageous for many tasks in the field of robotics and autonomous vehicles. From the robot's point of view, 3D perception is often formulated as a depth image reconstruction problem. In the literature, dense depth images are often recovered deterministically from stereo image disparities. Other systems use an expensive LiDAR sensor to produce accurate, but semi-sparse depth images. With the advent of deep learning there have also been attempts to estimate depth by only using monocular images. In this paper we combine the best of the two worlds, focusing on a combination of monocular images and low cost LiDAR point clouds. We explore the idea that very sparse depth information accurately captures the global scene structure while variations in image patches can be used to reconstruct local depth to a high resolution. The main contribution of this paper is a supervised learning depth reconstruction system based on a deep convolutional neural network. The network is trained on RGB image patches reinforced with sparse depth information and the output is a depth estimate for each pixel. Using image and point cloud data from the KITTI vision dataset we are able to learn a correspondence between local RGB information and local depth, while at the same time preserving the global scene structure. Our results are evaluated on sequences from the KITTI dataset and our own recordings using a low cost camera and LiDAR setup.

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Mask Environmental Data Record (EDR) from NDE

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains a high quality Environmental Data Record (EDR) of cloud masks from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument onboard...

Identification of 192Ir seeds in localization images using a novel statistical pattern recognition approach and a priori information

International Nuclear Information System (INIS)

Bird, William F.; Chaney, Edward L.; Coggins, James M.

1995-01-01

Purpose / Objective: Manual labeling of individual 192 Ir seeds in localization images for dosimetry of multi-strand low-dose-rate (LDR) implants is labor intensive, tedious and prone to error. The objective of this investigation is to develop computer-based methods that analyze digitized localization images, improve dosimetric efficiency, and reduce labeling errors. Materials and Methods: 192 Ir localization films were digitized with a scanned-laser system and analyzed using Multiscale, Geometric, Statistical Pattern Recognition (MGSPR), a technique that recognizes and classifies pixels in gray-scale images based on their surrounding, neighborhood geometry. To 'teach' MGSPR how to recognize specific objects, a Gaussian-based mathematical filter set is applied to training images containing user-labeled examples of the desired objects. The filters capture a broad range of descriptive geometric information at multiple spatial scales. Principled mathematical analysis is used to determine the linear combination of filters from a large base set that yields the best discrimination between object types. Thus the sensitivity of the filters can be 'tuned' to detect specific objects such as 192 Ir seeds. For a given pixel, the output of the filter is a multi-component feature vector that uniquely describes the pixel's geometric characteristics. Pixels with similar geometric attributes have feature vectors that naturally 'cluster', or group, in the multidimensional space called 'feature space'. After statistically quantifying the training-set clusters in feature space, pixels found in new images are automatically labeled by correlation with the nearest cluster, e.g., the cluster representing 192 Ir seeds. One of the greatest challenges in statistical pattern recognition is to determine which filters result in the best labeling. Good discrimination is achieved when clusters are compact and well isolated from one another in feature space. The filters used in this study are

Multi-Spectral Cloud Retrievals from Moderate Image Spectrometer (MODIS)

Science.gov (United States)

Platnick, Steven

2004-01-01

MODIS observations from the NASA EOS Terra spacecraft (1030 local time equatorial sun-synchronous crossing) launched in December 1999 have provided a unique set of Earth observation data. With the launch of the NASA EOS Aqua spacecraft (1330 local time crossing! in May 2002: two MODIS daytime (sunlit) and nighttime observations are now available in a 24-hour period allowing some measure of diurnal variability. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate modeling, climate change studies, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. An overview of the instrument and cloud algorithms will be presented along with various examples, including an initial analysis of several operational global gridded (Level-3) cloud products from the two platforms. Statistics of cloud optical and microphysical properties as a function of latitude for land and Ocean regions will be shown. Current algorithm research efforts will also be discussed.

NOAA GOES-R Series Advanced Baseline Imager (ABI) Level 2+ Cloud and Moisture Imagery Products (CMIP)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Cloud and Moisture Imagery product contains one or more Earth-view images with pixel values identifying brightness values that are scaled to support visual...

CLASSIFICATION BY USING MULTISPECTRAL POINT CLOUD DATA

Directory of Open Access Journals (Sweden)

C. T. Liao

2012-07-01

Full Text Available Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

Classification by Using Multispectral Point Cloud Data

Science.gov (United States)

Liao, C. T.; Huang, H. H.

2012-07-01

Remote sensing images are generally recorded in two-dimensional format containing multispectral information. Also, the semantic information is clearly visualized, which ground features can be better recognized and classified via supervised or unsupervised classification methods easily. Nevertheless, the shortcomings of multispectral images are highly depending on light conditions, and classification results lack of three-dimensional semantic information. On the other hand, LiDAR has become a main technology for acquiring high accuracy point cloud data. The advantages of LiDAR are high data acquisition rate, independent of light conditions and can directly produce three-dimensional coordinates. However, comparing with multispectral images, the disadvantage is multispectral information shortage, which remains a challenge in ground feature classification through massive point cloud data. Consequently, by combining the advantages of both LiDAR and multispectral images, point cloud data with three-dimensional coordinates and multispectral information can produce a integrate solution for point cloud classification. Therefore, this research acquires visible light and near infrared images, via close range photogrammetry, by matching images automatically through free online service for multispectral point cloud generation. Then, one can use three-dimensional affine coordinate transformation to compare the data increment. At last, the given threshold of height and color information is set as threshold in classification.

Determining ice water content from 2D crystal images in convective cloud systems

Science.gov (United States)

Leroy, Delphine; Coutris, Pierre; Fontaine, Emmanuel; Schwarzenboeck, Alfons; Strapp, J. Walter

2016-04-01

Cloud microphysical in-situ instrumentation measures bulk parameters like total water content (TWC) and/or derives particle size distributions (PSD) (utilizing optical spectrometers and optical array probes (OAP)). The goal of this work is to introduce a comprehensive methodology to compute TWC from OAP measurements, based on the dataset collected during recent HAIC (High Altitude Ice Crystals)/HIWC (High Ice Water Content) field campaigns. Indeed, the HAIC/HIWC field campaigns in Darwin (2014) and Cayenne (2015) provide a unique opportunity to explore the complex relationship between cloud particle mass and size in ice crystal environments. Numerous mesoscale convective systems (MCSs) were sampled with the French Falcon 20 research aircraft at different temperature levels from -10°C up to 50°C. The aircraft instrumentation included an IKP-2 (isokinetic probe) to get reliable measurements of TWC and the optical array probes 2D-S and PIP recording images over the entire ice crystal size range. Based on the known principle relating crystal mass and size with a power law (m=α•Dβ), Fontaine et al. (2014) performed extended 3D crystal simulations and thereby demonstrated that it is possible to estimate the value of the exponent β from OAP data, by analyzing the surface-size relationship for the 2D images as a function of time. Leroy et al. (2015) proposed an extended version of this method that produces estimates of β from the analysis of both the surface-size and perimeter-size relationships. Knowing the value of β, α then is deduced from the simultaneous IKP-2 TWC measurements for the entire HAIC/HIWC dataset. The statistical analysis of α and β values for the HAIC/HIWC dataset firstly shows that α is closely linked to β and that this link changes with temperature. From these trends, a generalized parameterization for α is proposed. Finally, the comparison with the initial IKP-2 measurements demonstrates that the method is able to predict TWC values

Cloud discrimination for ASCENDS Mission Based on Optical Phase Conjugation as a Novel Approach, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — PI at ArkLight proposes a novel scheme for making cloud discrimination in the wavelength ranges of near-IR (1-1.8 m) and mid-IR (3-4 m). This scheme is based on...

Evaluation of Passive Multilayer Cloud Detection Using Preliminary CloudSat and CALIPSO Cloud Profiles

Science.gov (United States)

Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.

2006-12-01

During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water clouds in overlapped conditions.

Modeling the Infrared Reverberation Response of the Circumnuclear Dusty Torus in AGNs: The Effects of Cloud Orientation and Anisotropic Illumination

International Nuclear Information System (INIS)

Almeyda, Triana; Robinson, Andrew; Richmond, Michael; Vazquez, Billy; Nikutta, Robert

2017-01-01

The obscuring circumnuclear torus of dusty molecular gas is one of the major components of active galactic nuclei (AGN). The torus can be studied by analyzing the time response of its infrared (IR) dust emission to variations in the AGN continuum luminosity, a technique known as reverberation mapping. The IR response is the convolution of the AGN ultraviolet/optical light curve with a transfer function that contains information about the size, geometry, and structure of the torus. Here, we describe a new computer model that simulates the reverberation response of a clumpy torus. Given an input optical light curve, the code computes the emission of a 3D ensemble of dust clouds as a function of time at selected IR wavelengths, taking into account light travel delays. We present simulated dust emission responses at 3.6, 4.5, and 30 μ m that explore the effects of various geometrical and structural properties, dust cloud orientation, and anisotropy of the illuminating radiation field. We also briefly explore the effects of cloud shadowing (clouds are shielded from the AGN continuum source). Example synthetic light curves have also been generated, using the observed optical light curve of the Seyfert 1 galaxy NGC 6418 as input. The torus response is strongly wavelength-dependent, due to the gradient in cloud surface temperature within the torus, and because the cloud emission is strongly anisotropic at shorter wavelengths. Anisotropic illumination of the torus also significantly modifies the torus response, reducing the lag between the IR and optical variations.

Modeling the Infrared Reverberation Response of the Circumnuclear Dusty Torus in AGNs: The Effects of Cloud Orientation and Anisotropic Illumination

Energy Technology Data Exchange (ETDEWEB)

Almeyda, Triana; Robinson, Andrew; Richmond, Michael; Vazquez, Billy [School of Physics and Astronomy, Rochester Institute of Technology, Rochester, NY 14623 (United States); Nikutta, Robert, E-mail: tra3595@rit.edu [National Optical Astronomy Observatory, 950 N Cherry Ave, Tucson, AZ 85719 (United States)

2017-07-01

The obscuring circumnuclear torus of dusty molecular gas is one of the major components of active galactic nuclei (AGN). The torus can be studied by analyzing the time response of its infrared (IR) dust emission to variations in the AGN continuum luminosity, a technique known as reverberation mapping. The IR response is the convolution of the AGN ultraviolet/optical light curve with a transfer function that contains information about the size, geometry, and structure of the torus. Here, we describe a new computer model that simulates the reverberation response of a clumpy torus. Given an input optical light curve, the code computes the emission of a 3D ensemble of dust clouds as a function of time at selected IR wavelengths, taking into account light travel delays. We present simulated dust emission responses at 3.6, 4.5, and 30 μ m that explore the effects of various geometrical and structural properties, dust cloud orientation, and anisotropy of the illuminating radiation field. We also briefly explore the effects of cloud shadowing (clouds are shielded from the AGN continuum source). Example synthetic light curves have also been generated, using the observed optical light curve of the Seyfert 1 galaxy NGC 6418 as input. The torus response is strongly wavelength-dependent, due to the gradient in cloud surface temperature within the torus, and because the cloud emission is strongly anisotropic at shorter wavelengths. Anisotropic illumination of the torus also significantly modifies the torus response, reducing the lag between the IR and optical variations.

Cloud Engineering Principles and Technology Enablers for Medical Image Processing-as-a-Service

Science.gov (United States)

Bao, Shunxing; Plassard, Andrew J.; Landman, Bennett A.; Gokhale, Aniruddha

2017-01-01

Traditional in-house, laboratory-based medical imaging studies use hierarchical data structures (e.g., NFS file stores) or databases (e.g., COINS, XNAT) for storage and retrieval. The resulting performance from these approaches is, however, impeded by standard network switches since they can saturate network bandwidth during transfer from storage to processing nodes for even moderate-sized studies. To that end, a cloud-based “medical image processing-as-a-service” offers promise in utilizing the ecosystem of Apache Hadoop, which is a flexible framework providing distributed, scalable, fault tolerant storage and parallel computational modules, and HBase, which is a NoSQL database built atop Hadoop’s distributed file system. Despite this promise, HBase’s load distribution strategy of region split and merge is detrimental to the hierarchical organization of imaging data (e.g., project, subject, session, scan, slice). This paper makes two contributions to address these concerns by describing key cloud engineering principles and technology enhancements we made to the Apache Hadoop ecosystem for medical imaging applications. First, we propose a row-key design for HBase, which is a necessary step that is driven by the hierarchical organization of imaging data. Second, we propose a novel data allocation policy within HBase to strongly enforce collocation of hierarchically related imaging data. The proposed enhancements accelerate data processing by minimizing network usage and localizing processing to machines where the data already exist. Moreover, our approach is amenable to the traditional scan, subject, and project-level analysis procedures, and is compatible with standard command line/scriptable image processing software. Experimental results for an illustrative sample of imaging data reveals that our new HBase policy results in a three-fold time improvement in conversion of classic DICOM to NiFTI file formats when compared with the default HBase region split

Cloud Engineering Principles and Technology Enablers for Medical Image Processing-as-a-Service.

Science.gov (United States)

Bao, Shunxing; Plassard, Andrew J; Landman, Bennett A; Gokhale, Aniruddha

2017-04-01

Traditional in-house, laboratory-based medical imaging studies use hierarchical data structures (e.g., NFS file stores) or databases (e.g., COINS, XNAT) for storage and retrieval. The resulting performance from these approaches is, however, impeded by standard network switches since they can saturate network bandwidth during transfer from storage to processing nodes for even moderate-sized studies. To that end, a cloud-based "medical image processing-as-a-service" offers promise in utilizing the ecosystem of Apache Hadoop, which is a flexible framework providing distributed, scalable, fault tolerant storage and parallel computational modules, and HBase, which is a NoSQL database built atop Hadoop's distributed file system. Despite this promise, HBase's load distribution strategy of region split and merge is detrimental to the hierarchical organization of imaging data (e.g., project, subject, session, scan, slice). This paper makes two contributions to address these concerns by describing key cloud engineering principles and technology enhancements we made to the Apache Hadoop ecosystem for medical imaging applications. First, we propose a row-key design for HBase, which is a necessary step that is driven by the hierarchical organization of imaging data. Second, we propose a novel data allocation policy within HBase to strongly enforce collocation of hierarchically related imaging data. The proposed enhancements accelerate data processing by minimizing network usage and localizing processing to machines where the data already exist. Moreover, our approach is amenable to the traditional scan, subject, and project-level analysis procedures, and is compatible with standard command line/scriptable image processing software. Experimental results for an illustrative sample of imaging data reveals that our new HBase policy results in a three-fold time improvement in conversion of classic DICOM to NiFTI file formats when compared with the default HBase region split policy

Smoke, Clouds and Radiation Brazil NASA ER-2 Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS) Data

Data.gov (United States)

National Aeronautics and Space Administration — SCARB_ER2_MAS data are Smoke, Clouds and Radiation Brazil (SCARB) NASA ER2 Moderate Resolution Imaging Spectrometer (MODIS) Airborne Simulator (MAS)...

The Economic and Social Value of an Image Exchange Network: A Case for the Cloud.

Science.gov (United States)

Mayo, Ray Cody; Pearson, Kathryn L; Avrin, David E; Leung, Jessica W T

2017-01-01

As the health care environment continually changes, radiologists look to the ACR's Imaging 3.0 ® initiative to guide the search for value. By leveraging new technology, a cloud-based image exchange network could provide secure universal access to prior images, which were previously siloed, to facilitate accurate interpretation, improved outcomes, and reduced costs. The breast imaging department represents a viable starting point given the robust data supporting the benefit of access to prior imaging studies, existing infrastructure for image sharing, and the current workflow reliance on prior images. This concept is scalable not only to the remainder of the radiology department but also to the broader medical record. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

FT-IR spectroscopic imaging of reactions in multiphase flow in microfluidic channels.

Science.gov (United States)

Chan, K L Andrew; Kazarian, Sergei G

2012-05-01

Rapid, in situ, and label-free chemical analysis in microfluidic devices is highly desirable. FT-IR spectroscopic imaging has previously been shown to be a powerful tool to visualize the distribution of different chemicals in flows in a microfluidic device at near video rate imaging speed without tracers or dyes. This paper demonstrates the possibility of using this imaging technology to capture the chemical information of all reactants and products at different points in time and space in a two-phase system. Differences in the rates of chemical reactions in laminar flow and segmented flow systems are also compared. Neutralization of benzoic acid in decanol with disodium phosphate in water has been used as the model reaction. Quantitative information, such as concentration profiles of reactant and products, can be extracted from the imaging data. The same feed flow rate was used in both the laminar flow and segmented flow systems. The laminar flow pattern was achieved using a plain wide T-junction, whereas the segmented flow was achieved by introducing a narrowed section and a nozzle at the T-junction. The results show that the reaction rate is limited by diffusion and is much slower with the laminar flow pattern, whereas the reaction is completed more quickly in the segmented flow due to better mixing.

Exploring the Effects of Clouds on Hot Jupiter Atmospheres

Science.gov (United States)

Robinson, Jenna; Line, Michael

2018-01-01

Secondary eclipse spectroscopy of transiting exoplanets allows us to probe the atmospheric properties on the daysides of tidally locked planets. Specifically, eclipse spectra combined with atmospheric retrieval models permit constraints on the molecular abundances and vertical thermal profiles of the planetary dayside. Eclipse spectra from HST WFC3 are typically interpreted assuming that all of the near infrared light is due solely to the thermal emission of the planet. However, recent evidence suggests that reflected stellar light from clouds on the planetary daysides might contaminate the near-IR spectrum. Here, we aim to explore how reflected light from clouds within in a simplified cloud framework will alter the shape of the near infrared spectra and how they will influence our determinations of dayside temperatures and abundances. Specifically, we will use atmospheric retrieval tools to determine the biases in abundances and temperature profiles if reflected light is not taken into account. We will explore the influence of reflected light on interpretation of WFC3 spectra of the well-observed exoplanets, HD209458b and WASP-43b. We will then investigate how reflected light in the near-IR will influence our interpretation of JWST spectra.

Tharsis Limb Cloud

Science.gov (United States)

2005-01-01

[figure removed for brevity, see original site] Annotated image of Tharsis Limb Cloud 7 September 2005 This composite of red and blue Mars Global Surveyor (MGS) Mars Orbiter Camera (MOC) daily global images acquired on 6 July 2005 shows an isolated water ice cloud extending more than 30 kilometers (more than 18 miles) above the martian surface. Clouds such as this are common in late spring over the terrain located southwest of the Arsia Mons volcano. Arsia Mons is the dark, oval feature near the limb, just to the left of the 'T' in the 'Tharsis Montes' label. The dark, nearly circular feature above the 'S' in 'Tharsis' is the volcano, Pavonis Mons, and the other dark circular feature, above and to the right of 's' in 'Montes,' is Ascraeus Mons. Illumination is from the left/lower left. Season: Northern Autumn/Southern Spring

Dust and gas distribution in molecular clouds: an observational approach

International Nuclear Information System (INIS)

Campeggio, Loretta; Elia, Davide; Maiolo, Berlinda M T; Strafella, Francesco; Cecchi-Pestellini, Cesare

2005-01-01

The interstellar medium (ISM), gas and dust, appears to be arranged in clouds, whose dimensions, masses and densities span a large range of scales: from giant molecular clouds to small isolated globules. The structure of these objects show a high degree of complexity appearing, in the range of the observed scales, as a non-homogeneous ('clumpy') distribution of matter. The arrangement of the ISM is clearly relevant for the study of the fragmentation of the clouds and then of the star formation processes. To quantify observationally the ISM structure, many methods have been developed and our study is focused on some of them, exploiting multiwavelength observations of IS objects. The investigations presented here have been carried out by considering both the dust absorption (in optical and near IR wavelengths) and the gas emission (in the submm-radio spectral range). We present the maps obtained from the reduction of raw data and a first tentative analysis by means of methods as the structure function, the autocorrelation, and the Δ-variance. These are appropriate tools to highlight the complex structure of the ISM with reference to the paradigm given by the supersonic turbulence. Three observational cases are briefly discussed. In order to analyse the structure of objects characterized by different sizes, we applied the above-mentioned algorithms to the extinction map of the dark globule CB 107 and to the CO(J = 1-0) integrated intensity map of Vela Molecular Ridge, D Cloud. Finally we compare the results obtained with synthetic fractal maps known as 'fractional Brownian motion' fBm images

A New Method of Cloud Detection Based on Cascaded AdaBoost

International Nuclear Information System (INIS)

Ma, C; Chen, F; Liu, J; Duan, J

2014-01-01

Cloud detection of remote sensing image is a critical step in the processing of the remote sensing images. How to quickly, accurately and effectively detect cloud on remote sensing images, is still a challenging issue in this area. In order to avoid disadvantages of the current algorithms, the cascaded AdaBoost classifier algorithm is successfully applied to the cloud detection. A new algorithm combined cascaded AdaBoost classifier and multi-features, is proposed in this paper. First, multi-features based on the color, texture and spectral features are extracted from the remote sensing image. Second, the automatic cloud detection model is obtained based on the cascaded AdaBoost algorithm. In this paper, the results show that the new algorithm can determine cloud detection model and threshold values adaptively for different resolution remote sensing training data. The accuracy of cloud detection is improved. So it is a new effective algorithm for the cloud detection of remote sensing images

A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images

Directory of Open Access Journals (Sweden)

Zhiying Song

2017-01-01

Full Text Available The PET and CT fusion image, combining the anatomical and functional information, has important clinical meaning. An effective registration of PET and CT images is the basis of image fusion. This paper presents a multithread registration method based on contour point cloud for 3D whole-body PET and CT images. Firstly, a geometric feature-based segmentation (GFS method and a dynamic threshold denoising (DTD method are creatively proposed to preprocess CT and PET images, respectively. Next, a new automated trunk slices extraction method is presented for extracting feature point clouds. Finally, the multithread Iterative Closet Point is adopted to drive an affine transform. We compare our method with a multiresolution registration method based on Mattes Mutual Information on 13 pairs (246~286 slices per pair of 3D whole-body PET and CT data. Experimental results demonstrate the registration effectiveness of our method with lower negative normalization correlation (NC = −0.933 on feature images and less Euclidean distance error (ED = 2.826 on landmark points, outperforming the source data (NC = −0.496, ED = 25.847 and the compared method (NC = −0.614, ED = 16.085. Moreover, our method is about ten times faster than the compared one.

Opaque cloud detection

Science.gov (United States)

Roskovensky, John K [Albuquerque, NM

2009-01-20

A method of detecting clouds in a digital image comprising, for an area of the digital image, determining a reflectance value in at least three discrete electromagnetic spectrum bands, computing a first ratio of one reflectance value minus another reflectance value and the same two values added together, computing a second ratio of one reflectance value and another reflectance value, choosing one of the reflectance values, and concluding that an opaque cloud exists in the area if the results of each of the two computing steps and the choosing step fall within three corresponding predetermined ranges.

Cloud Detection by Fusing Multi-Scale Convolutional Features

Science.gov (United States)

Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

2018-04-01

Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

Factors influencing the organizational adoption of cloud computing: a survey among cloud workers

Directory of Open Access Journals (Sweden)

Mark Stieninger

2018-01-01

Full Text Available Cloud computing presents an opportunity for organizations to leverage affordable, scalable, and agile technologies. However, even with the demonstrated value of cloud computing, organizations have been hesitant to adopt such technologies. Based on a multi-theoretical research model, this paper provides an empirical study targeted to better understand the adoption of cloud services. An online survey addressing the factors derived from literature for three specific popular cloud application types (cloud storage, cloud mail and cloud office was undertaken. The research model was analyzed by using variance-based structural equation modelling. Results show that the factors of compatibility, relative advantage, security and trust, as well as, a lower level of complexity lead to a more positive attitude towards cloud adoption. Complexity, compatibility, image and security and trust have direct and indirect effects on relative advantage. These factors further explain a large part of the attitude towards cloud adoption but not of its usage.

Relationship between ice water path and downward longwave radiation for clouds optically thin in the infrared: Observations and model calculations

Science.gov (United States)

Uttal, Taneil; Matrosov, Sergey Y.; Snider, Jack B.; Kropfli, Robert A.

1994-01-01

A vertically pointing 3.2-cm radar is used to observe altostratus and cirrus clouds as they pass overhead. Radar reflectivities are used in combination with an empirical Z(sub i)-IWC (ice water content) relationship developed by Sassen (1987) to parameterize IWC, which is then integrated to obtain estimates of ice water path (IWP). The observed dataset is segregated into all-ice and mixed-phase periods using measurements of integrated liquid water paths (LWP) detected by a collocated, dual-channel microwave radiometer. The IWP values for the all ice periods are compared to measurements of infrared (IR) downward fluxes measured by a collocated narrowband (9.95-11.43 microns) IR radiometer, which results in scattergrams representing the observed dependence of IR fluxes on IWP. A two-stream model is used to calculate the infrared fluxes expected from ice clouds with boundary conditions specified by the actual clouds, and similar curves relating IWP and infrared fluxes are obtained. The model and observational results suggest that IWP is one of the primary controls on infrared thermal fluxes for ice clouds.

Identification of {sup 192}Ir seeds in localization images using a novel statistical pattern recognition approach and a priori information

Energy Technology Data Exchange (ETDEWEB)

Bird, William F; Chaney, Edward L; Coggins, James M

1995-07-01

Purpose / Objective: Manual labeling of individual {sup 192}Ir seeds in localization images for dosimetry of multi-strand low-dose-rate (LDR) implants is labor intensive, tedious and prone to error. The objective of this investigation is to develop computer-based methods that analyze digitized localization images, improve dosimetric efficiency, and reduce labeling errors. Materials and Methods: {sup 192}Ir localization films were digitized with a scanned-laser system and analyzed using Multiscale, Geometric, Statistical Pattern Recognition (MGSPR), a technique that recognizes and classifies pixels in gray-scale images based on their surrounding, neighborhood geometry. To 'teach' MGSPR how to recognize specific objects, a Gaussian-based mathematical filter set is applied to training images containing user-labeled examples of the desired objects. The filters capture a broad range of descriptive geometric information at multiple spatial scales. Principled mathematical analysis is used to determine the linear combination of filters from a large base set that yields the best discrimination between object types. Thus the sensitivity of the filters can be 'tuned' to detect specific objects such as{sup 192} Ir seeds. For a given pixel, the output of the filter is a multi-component feature vector that uniquely describes the pixel's geometric characteristics. Pixels with similar geometric attributes have feature vectors that naturally 'cluster', or group, in the multidimensional space called 'feature space'. After statistically quantifying the training-set clusters in feature space, pixels found in new images are automatically labeled by correlation with the nearest cluster, e.g., the cluster representing {sup 192}Ir seeds. One of the greatest challenges in statistical pattern recognition is to determine which filters result in the best labeling. Good discrimination is achieved when clusters are compact and well isolated from one another in feature space. The filters used in

MicrOmega IR: a new infrared hyperspectral imaging microscope or in situ analysis

Science.gov (United States)

Vaitua, Leroi; Bibring, Jean-Pierre; Berthé, Michel

2017-11-01

MicrOmega IR is an ultra miniaturized Near Infrared hyperspectral microscope for in situ analysis of samples. It is designed to be implemented on board space planetary vehicles (lander and/or rovers). It acquires images of samples typically some 5 mm in width with a spatial sampling of 20 μm. On each pixel, MicrOmega acquires the spectrum in the spectral range 0.9 - 2.6 μm, with a possibility to extend the sensibility up to 4 μm. The spectrum will be measured in up to 300 contiguous spectral channels (600 in the extended range): given the diagnostic spectral features present in this domain, it provides the composition of each spatially resolved constituent. MicrOmega has thus the potential to identify: minerals, such as pyroxene and olivine, ferric oxides, hydrated phases such as phyllosilicates, sulfates and carbonates, ices and organics. The composition of the various phases within a given sample is a critical record of its formation and evolution. Coupled to the mapping information, it provides unique clues to describe the history of the parent body. In particular, the capability to identify hydrated grains and to characterize their adjacent phases has a huge potential in the search for potential bio-relics in Martian samples. This purely non destructive characterization enables further analyses (e.g. through mass spectrometry) to be performed, and/or to contribute to sample selection to return to Earth. MicrOmega IR is coupled to a visible microscope: MicrOmega VIS. Thus, the MicrOmega instrument is developed by an international consortium: IAS (Orsay, France), LESIA (Meudon, France), CBM (Orléans, France), University Of Bern (Bern, Switzerland), IKI (Moscow, Russia). This instrument (MicrOmega IR, MicrOmega VIS and the electronics) is selected for the ESA Exomars mission (launch scheduled for 2013). MicrOmega IR will be used in a reduced spectral range (0.9 - 2.6 μm), due to power, mass and thermal constraints: however, most minerals and other

Mesoscale circulation at the upper cloud level at middle latitudes from the imaging by Venus Monitoring Camera onboard Venus Express

Science.gov (United States)

Patsaeva, Marina; Ignatiev, Nikolay; Markiewicz, Wojciech; Khatuntsev, Igor; Titov, Dmitrij; Patsaev, Dmitry

The Venus Monitoring Camera onboard ESA Venus Express spacecraft acquired a great number of UV images (365 nm) allowing us to track the motion of cloud features at the upper cloud layer of Venus. A digital method developed to analyze correlation functions between two UV images provided wind vector fields on the Venus day side (9-16 hours local time) from the equator to high latitudes. Sizes and regions for the correlation were chosen empirically, as a trade-off of sensitivity against noise immunity and vary from 10(°) x7.5(°) to 20(°) x10(°) depending on the grid step, making this method suitable to investigate the mesoscale circulation. Previously, the digital method was used for investigation of the circulation at low latitudes and provided good agreement with manual tracking of the motion of cloud patterns. Here we present first results obtained by this method for middle latitudes (25(°) S-75(°) S) on the basis of 270 orbits. Comparing obtained vector fields with images for certain orbits, we found a relationship between morphological patterns of the cloud cover at middle latitudes and parameters of the circulation. Elongated cloud features, so-called streaks, are typical for middle latitudes, and their orientation varies over wide range. The behavior of the vector field of velocities depends on the angle between the streak and latitude circles. In the middle latitudes the average angle of the flow deviation from the zonal direction is equal to -5.6(°) ± 1(°) (the sign “-“ means the poleward flow, the standard error is given). For certain orbits, this angle varies from -15.6(°) ± 1(°) to 1.4(°) ± 1(°) . In some regions at latitudes above 60(°) S the meridional wind is equatorward in the morning. The relationship between the cloud cover morphology and circulation peculiarity can be attributed to the motion of the Y-feature in the upper cloud layer due to the super-rotation of the atmosphere.

CIMIDx: Prototype for a Cloud-Based System to Support Intelligent Medical Image Diagnosis With Efficiency.

Science.gov (United States)

Bhavani, Selvaraj Rani; Senthilkumar, Jagatheesan; Chilambuchelvan, Arul Gnanaprakasam; Manjula, Dhanabalachandran; Krishnamoorthy, Ramasamy; Kannan, Arputharaj

2015-03-27

The Internet has greatly enhanced health care, helping patients stay up-to-date on medical issues and general knowledge. Many cancer patients use the Internet for cancer diagnosis and related information. Recently, cloud computing has emerged as a new way of delivering health services but currently, there is no generic and fully automated cloud-based self-management intervention for breast cancer patients, as practical guidelines are lacking. We investigated the prevalence and predictors of cloud use for medical diagnosis among women with breast cancer to gain insight into meaningful usage parameters to evaluate the use of generic, fully automated cloud-based self-intervention, by assessing how breast cancer survivors use a generic self-management model. The goal of this study was implemented and evaluated with a new prototype called "CIMIDx", based on representative association rules that support the diagnosis of medical images (mammograms). The proposed Cloud-Based System Support Intelligent Medical Image Diagnosis (CIMIDx) prototype includes two modules. The first is the design and development of the CIMIDx training and test cloud services. Deployed in the cloud, the prototype can be used for diagnosis and screening mammography by assessing the cancers detected, tumor sizes, histology, and stage of classification accuracy. To analyze the prototype's classification accuracy, we conducted an experiment with data provided by clients. Second, by monitoring cloud server requests, the CIMIDx usage statistics were recorded for the cloud-based self-intervention groups. We conducted an evaluation of the CIMIDx cloud service usage, in which browsing functionalities were evaluated from the end-user's perspective. We performed several experiments to validate the CIMIDx prototype for breast health issues. The first set of experiments evaluated the diagnostic performance of the CIMIDx framework. We collected medical information from 150 breast cancer survivors from hospitals

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Daytime Cloud Optical and Microphysical Properties (DCOMP) from NDE

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains a high quality Environmental Data Record (EDR) of daytime cloud optical and microphysical properties (DCOMP) from the Visible Infrared Imaging...

Analysis of co-located MODIS and CALIPSO observations near clouds

Directory of Open Access Journals (Sweden)

T. Várnai

2012-02-01

Full Text Available This paper aims at helping synergistic studies in combining data from different satellites for gaining new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects. In particular, the paper examines the way cloud information from the MODIS (MODerate resolution Imaging Spectroradiometer imager can refine our perceptions based on CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization lidar measurements about the systematic aerosol changes that occur near clouds.

The statistical analysis of a yearlong dataset of co-located global maritime observations from the Aqua and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation satellites reveals that MODIS's multispectral imaging ability can greatly help the interpretation of CALIOP observations. The results show that imagers on Aqua and CALIPSO yield very similar pictures, and that the discrepancies – due mainly to wind drift and differences in view angle – do not significantly hinder aerosol measurements near clouds. By detecting clouds outside the CALIOP track, MODIS reveals that clouds are usually closer to clear areas than CALIOP data alone would suggest. The paper finds statistical relationships between the distances to clouds in MODIS and CALIOP data, and proposes a rescaling approach to statistically account for the impact of clouds outside the CALIOP track even when MODIS cannot reliably detect low clouds, for example at night or over sea ice. Finally, the results show that the typical distance to clouds depends on both cloud coverage and cloud type, and accordingly varies with location and season. In maritime areas perceived cloud free, the global median distance to clouds below 3 km altitude is in the 4–5 km range.

Astronomy In The Cloud: Using Mapreduce For Image Coaddition

Science.gov (United States)

Wiley, Keith; Connolly, A.; Gardner, J.; Krughoff, S.; Balazinska, M.; Howe, B.; Kwon, Y.; Bu, Y.

2011-01-01

In the coming decade, astronomical surveys of the sky will generate tens of terabytes of images and detect hundreds of millions of sources every night. The study of these sources will involve computational challenges such as anomaly detection, classification, and moving object tracking. Since such studies require the highest quality data, methods such as image coaddition, i.e., registration, stacking, and mosaicing, will be critical to scientific investigation. With a requirement that these images be analyzed on a nightly basis to identify moving sources, e.g., asteroids, or transient objects, e.g., supernovae, these datastreams present many computational challenges. Given the quantity of data involved, the computational load of these problems can only be addressed by distributing the workload over a large number of nodes. However, the high data throughput demanded by these applications may present scalability challenges for certain storage architectures. One scalable data-processing method that has emerged in recent years is MapReduce, and in this paper we focus on its popular open-source implementation called Hadoop. In the Hadoop framework, the data is partitioned among storage attached directly to worker nodes, and the processing workload is scheduled in parallel on the nodes that contain the required input data. A further motivation for using Hadoop is that it allows us to exploit cloud computing resources, i.e., platforms where Hadoop is offered as a service. We report on our experience implementing a scalable image-processing pipeline for the SDSS imaging database using Hadoop. This multi-terabyte imaging dataset provides a good testbed for algorithm development since its scope and structure approximate future surveys. First, we describe MapReduce and how we adapted image coaddition to the MapReduce framework. Then we describe a number of optimizations to our basic approach and report experimental results compring their performance. This work is funded by

Sahara Dust Cloud

Science.gov (United States)

2005-01-01

[figure removed for brevity, see original site] Dust Particles Click on the image for Quicktime movie from 7/15-7/24 A continent-sized cloud of hot air and dust originating from the Sahara Desert crossed the Atlantic Ocean and headed towards Florida and the Caribbean. A Saharan Air Layer, or SAL, forms when dry air and dust rise from Africa's west coast and ride the trade winds above the Atlantic Ocean. These dust clouds are not uncommon, especially during the months of July and August. They start when weather patterns called tropical waves pick up dust from the desert in North Africa, carry it a couple of miles into the atmosphere and drift westward. In a sequence of images created by data acquired by the Earth-orbiting Atmospheric Infrared Sounder ranging from July 15 through July 24, we see the distribution of the cloud in the atmosphere as it swirls off of Africa and heads across the ocean to the west. Using the unique silicate spectral signatures of dust in the thermal infrared, AIRS can detect the presence of dust in the atmosphere day or night. This detection works best if there are no clouds present on top of the dust; when clouds are present, they can interfere with the signal, making it much harder to detect dust as in the case of July 24, 2005. In the Quicktime movie, the scale at the bottom of the images shows +1 for dust definitely detected, and ranges down to -1 for no dust detected. The plots are averaged over a number of AIRS observations falling within grid boxes, and so it is possible to obtain fractional numbers. [figure removed for brevity, see original site] Total Water Vapor in the Atmosphere Around the Dust Cloud Click on the image for Quicktime movie The dust cloud is contained within a dry adiabatic layer which originates over the Sahara Desert. This Saharan Air Layer (SAL) advances Westward over the Atlantic Ocean, overriding the cool, moist air nearer the surface. This burst of very dry air is visible in the AIRS retrieved total water

DICOM relay over the cloud.

Science.gov (United States)

Silva, Luís A Bastião; Costa, Carlos; Oliveira, José Luis

2013-05-01

Healthcare institutions worldwide have adopted picture archiving and communication system (PACS) for enterprise access to images, relying on Digital Imaging Communication in Medicine (DICOM) standards for data exchange. However, communication over a wider domain of independent medical institutions is not well standardized. A DICOM-compliant bridge was developed for extending and sharing DICOM services across healthcare institutions without requiring complex network setups or dedicated communication channels. A set of DICOM routers interconnected through a public cloud infrastructure was implemented to support medical image exchange among institutions. Despite the advantages of cloud computing, new challenges were encountered regarding data privacy, particularly when medical data are transmitted over different domains. To address this issue, a solution was introduced by creating a ciphered data channel between the entities sharing DICOM services. Two main DICOM services were implemented in the bridge: Storage and Query/Retrieve. The performance measures demonstrated it is quite simple to exchange information and processes between several institutions. The solution can be integrated with any currently installed PACS-DICOM infrastructure. This method works transparently with well-known cloud service providers. Cloud computing was introduced to augment enterprise PACS by providing standard medical imaging services across different institutions, offering communication privacy and enabling creation of wider PACS scenarios with suitable technical solutions.

Methodology for automatic process of the fired ceramic tile's internal defect using IR images and artificial neural network

OpenAIRE

Andrade, Roberto Márcio de; Eduardo, Alexandre Carlos

2011-01-01

In the ceramic industry, rarely testing systems were employed to on-line detect the presence of defects in ceramic tiles. This paper is concerned with the problem of automatic inspection of ceramic tiles using Infrared Images and Artificial Neural Network (ANN). The performance of the technique has been evaluated theoretically and experimentally from laboratory and on line tile samples. It has been performed system for IR image processing and, utilizing an Artificial Neural Network (ANN), det...

Prior-Based Quantization Bin Matching for Cloud Storage of JPEG Images.

Science.gov (United States)

Liu, Xianming; Cheung, Gene; Lin, Chia-Wen; Zhao, Debin; Gao, Wen

2018-07-01

Millions of user-generated images are uploaded to social media sites like Facebook daily, which translate to a large storage cost. However, there exists an asymmetry in upload and download data: only a fraction of the uploaded images are subsequently retrieved for viewing. In this paper, we propose a cloud storage system that reduces the storage cost of all uploaded JPEG photos, at the expense of a controlled increase in computation mainly during download of requested image subset. Specifically, the system first selectively re-encodes code blocks of uploaded JPEG images using coarser quantization parameters for smaller storage sizes. Then during download, the system exploits known signal priors-sparsity prior and graph-signal smoothness prior-for reverse mapping to recover original fine quantization bin indices, with either deterministic guarantee (lossless mode) or statistical guarantee (near-lossless mode). For fast reverse mapping, we use small dictionaries and sparse graphs that are tailored for specific clusters of similar blocks, which are classified via tree-structured vector quantizer. During image upload, cluster indices identifying the appropriate dictionaries and graphs for the re-quantized blocks are encoded as side information using a differential distributed source coding scheme to facilitate reverse mapping during image download. Experimental results show that our system can reap significant storage savings (up to 12.05%) at roughly the same image PSNR (within 0.18 dB).

Risk and reward in the cloud. Choosing a cloud vendor involves weighing risks versus benefits.

Science.gov (United States)

Degaspari, John

2012-05-01

More hospitals are looking to the cloud as a viable way to store clinical, imaging, and financial data. Experts acknowledge its advantages, but caution it's a step that requires careful planning and vetting of potential cloud vendors.

A Study of Application Layer Paradigm for Lower Layer Energy Saving Potentials in Cloud-Edge Social User Wireless Image Sharing

Directory of Open Access Journals (Sweden)

Wei Wang

2015-08-01

Full Text Available Energy saving becomes critical in modern cloud wireless multimedia and mobile communication systems. In this paper we propose to study a new paradigm named application layer Position-Value diversity for wireless image sharing for cloud-edge communications, which has significant energy saving potentials for modern wireless networking systems. In this new paradigm, saving energy is achieved by looking into application layer imaging traffic, in stead of MAC-PHY protocols at lower layers, and partitioning it into important positions and unimportant values. This paradigm could be integrated to existing wavelet-based tree compression, and truncation of image bit streams could be performed with regards to wireless communication energy budget estimation. Simulation results demonstrated that there are significant potentials of communication energy efficiency gain and Quality of Experience (QoE enhancement in wireless image communication systems.

IR spectral analysis for the diagnostics of crust earthquake precursors

Science.gov (United States)

Umarkhodgaev, R. M.; Liperovsky, V. A.; Mikhailin, V. V.; Meister, C.-V.; Naumov, D. Ju

2012-04-01

In regions of future earthquakes, a few days before the seismic shock, the emanation of radon and hydrogen is being observed, which causes clouds of increased ionisation in the atmosphere. In the present work the possible diagnostics of these clouds using infrared (IR) spectroscopy is considered, which may be important and useful for the general geophysical system of earthquake prediction and the observation of industrial emissions of radioactive materials into the atmosphere. Some possible physical processes are analysed, which cause, under the condition of additional ionisation in a pre-breakdown electrical field, emissions in the IR interval. In doing so, the transparency region of the IR spectrum at wavelengths of 7-15 μm is taken into account. This transparency region corresponds to spectral lines of small atmospheric constituents like CH4, CO2, N2O, NO2, NO, and O3. The possible intensities of the IR emissions observable in laboratories and in nature are estimated. The acceleration process of the electrons in the pre-breakdown electrical field before its adhesion to the molecules is analysed. The laboratory equipment for the investigation of the IR absorption spectrum is constructed for the cases of normal and decreased atmospheric pressures. The syntheses of ozone and nitrous oxides are performed in the barrier discharge. It is studied if the products of the syntheses may be used to model atmospheric processes where these components take part. Spectra of products of the syntheses in the wavelength region of 2-10 μm are observed and analysed. A device is created for the syntheses and accumulation of nitrous oxides. Experiments to observe the IR-spectra of ozone and nitrous oxides during the syntheses and during the further evolution of these molecules are performed. For the earthquake prediction, practically, the investigation of emission spectra is most important, but during the laboratory experiments, the radiation of the excited molecules is shifted by a

Cloud Computing and Its Applications in GIS

Science.gov (United States)

Kang, Cao

2011-12-01

Cloud computing is a novel computing paradigm that offers highly scalable and highly available distributed computing services. The objectives of this research are to: 1. analyze and understand cloud computing and its potential for GIS; 2. discover the feasibilities of migrating truly spatial GIS algorithms to distributed computing infrastructures; 3. explore a solution to host and serve large volumes of raster GIS data efficiently and speedily. These objectives thus form the basis for three professional articles. The first article is entitled "Cloud Computing and Its Applications in GIS". This paper introduces the concept, structure, and features of cloud computing. Features of cloud computing such as scalability, parallelization, and high availability make it a very capable computing paradigm. Unlike High Performance Computing (HPC), cloud computing uses inexpensive commodity computers. The uniform administration systems in cloud computing make it easier to use than GRID computing. Potential advantages of cloud-based GIS systems such as lower barrier to entry are consequently presented. Three cloud-based GIS system architectures are proposed: public cloud- based GIS systems, private cloud-based GIS systems and hybrid cloud-based GIS systems. Public cloud-based GIS systems provide the lowest entry barriers for users among these three architectures, but their advantages are offset by data security and privacy related issues. Private cloud-based GIS systems provide the best data protection, though they have the highest entry barriers. Hybrid cloud-based GIS systems provide a compromise between these extremes. The second article is entitled "A cloud computing algorithm for the calculation of Euclidian distance for raster GIS". Euclidean distance is a truly spatial GIS algorithm. Classical algorithms such as the pushbroom and growth ring techniques require computational propagation through the entire raster image, which makes it incompatible with the distributed nature

First correlated measurements of the shape and scattering properties of cloud particles using the new Particle Habit Imaging and Polar Scattering (PHIPS) probe

Science.gov (United States)

Abdelmonem, A.; Schnaiter, M.; Amsler, P.; Hesse, E.; Meyer, J.; Leisner, T.

2011-05-01

Studying the radiative impact of cirrus clouds requires the knowledge of the link between their microphysics and the single scattering properties of the cloud particles. Usually, this link is created by modeling the optical scattering properties from in situ measurements of ice crystal size distributions. The measured size distribution and the assumed particle shape might be erroneous in case of non-spherical ice particles. We present here a novel optical sensor (the Particle Habit Imaging and Polar Scattering probe, PHIPS) designed to measure the 3-D morphology and the corresponding optical and microphysical parameters of individual cloud particles, simultaneously. Clouds containing particles ranging in size from a few micrometers to about 800 μm diameter can be systematically characterized with an optical resolution power of 2 μm and polar scattering resolution of 1° for forward scattering directions (from 1° to 10°) and 8° for side and backscattering directions (from 18° to 170°). The maximum acquisition rates for scattering phase functions and images are 262 KHz and 10 Hz, respectively. Some preliminary results collected in two ice cloud campaigns which were conducted in the AIDA cloud simulation chamber are presented. PHIPS showed reliability in operation and produced comparable size distributions and images to those given by other certified cloud particles instruments. A 3-D model of a hexagonal ice plate is constructed and the corresponding scattering phase function is compared to that modeled using the Ray Tracing with Diffraction on Facets (RTDF) program. PHIPS is candidate to be a novel air borne optical sensor for studying the radiative impact of cirrus clouds and correlating the particle habit-scattering properties which will serve as a reference for other single, or multi-independent, measurements instruments.

All your clouds are belong to us - Security analysis of cloud management interfaces

DEFF Research Database (Denmark)

Somorovsky, Juraj; Heiderich, Mario; Jensen, Meiko

2011-01-01

a complete power over the victim's account, with all the stored data included. In this paper, we provide a security analysis pertaining to the control interfaces of a large Public Cloud (Amazon) and a widely used Private Cloud software (Eucalyptus). Our research results are alarming: in regards to the Amazon......Cloud Computing resources are handled through control interfaces. It is through these interfaces that the new machine images can be added, existing ones can be modified, and instances can be started or ceased. Effectively, a successful attack on a Cloud control interface grants the attacker...... discoveries, we additionally describe the countermea-sures against these attacks, as well as introduce a novel "black box" analysis methodology for public Cloud interfaces....

Web-based Data Exploration, Exploitation and Visualization Tools for Satellite Sensor VIS/IR Calibration Applications

Science.gov (United States)

Gopalan, A.; Doelling, D. R.; Scarino, B. R.; Chee, T.; Haney, C.; Bhatt, R.

2016-12-01

The CERES calibration group at NASA/LaRC has developed and deployed a suite of online data exploration and visualization tools targeted towards a range of spaceborne VIS/IR imager calibration applications for the Earth Science community. These web-based tools are driven by the open-source R (Language for Statistical Computing and Visualization) with a web interface for the user to customize the results according to their application. The tool contains a library of geostationary and sun-synchronous imager spectral response functions (SRF), incoming solar spectra, SCIAMACHY and Hyperion Earth reflected visible hyper-spectral data, and IASI IR hyper-spectral data. The suite of six specific web-based tools was designed to provide critical information necessary for sensor cross-calibration. One of the challenges of sensor cross-calibration is accounting for spectral band differences and may introduce biases if not handled properly. The spectral band adjustment factors (SBAF) are a function of the earth target, atmospheric and cloud conditions or scene type and angular conditions, when obtaining sensor radiance pairs. The SBAF will need to be customized for each inter-calibration target and sensor pair. The advantages of having a community open source tool are: 1) only one archive of SCIAMACHY, Hyperion, and IASI datasets needs to be maintained, which is on the order of 50TB. 2) the framework will allow easy incorporation of new satellite SRFs and hyper-spectral datasets and associated coincident atmospheric and cloud properties, such as PW. 3) web tool or SBAF algorithm improvements or suggestions when incorporated can benefit the community at large. 4) The customization effort is on the user rather than on the host. In this paper we discuss each of these tools in detail and explore the variety of advanced options that can be used to constrain the results along with specific use cases to highlight the value-added by these datasets.

CloudGC: Recycling Idle Virtual Machines in the Cloud

OpenAIRE

Zhang , Bo; Al-Dhuraibi , Yahya; Rouvoy , Romain; Paraiso , Fawaz; Seinturier , Lionel

2017-01-01

International audience; Cloud computing conveys the image of a pool of unlimited virtual resources that can be quickly and easily provisioned to accommodate the user requirements. However, this flexibility may require to adjust physical resources at the infrastructure level to keep the pace of user requests. While elasticity can be considered as the de facto solution to support this issue, this elasticity can still be broken by budget requirements or physical limitations of a private cloud. I...

Automated Detection of Cloud and Cloud Shadow in Single-Date Landsat Imagery Using Neural Networks and Spatial Post-Processing

Directory of Open Access Journals (Sweden)

M. Joseph Hughes

2014-05-01

Full Text Available The use of Landsat data to answer ecological questions is greatly increased by the effective removal of cloud and cloud shadow from satellite images. We develop a novel algorithm to identify and classify clouds and cloud shadow, SPARCS: Spatial Procedures for Automated Removal of Cloud and Shadow. The method uses a neural network approach to determine cloud, cloud shadow, water, snow/ice and clear sky classification memberships of each pixel in a Landsat scene. It then applies a series of spatial procedures to resolve pixels with ambiguous membership by using information, such as the membership values of neighboring pixels and an estimate of cloud shadow locations from cloud and solar geometry. In a comparison with FMask, a high-quality cloud and cloud shadow classification algorithm currently available, SPARCS performs favorably, with substantially lower omission errors for cloud shadow (8.0% and 3.2%, only slightly higher omission errors for clouds (0.9% and 1.3%, respectively and fewer errors of commission (2.6% and 0.3%. Additionally, SPARCS provides a measure of uncertainty in its classification that can be exploited by other algorithms that require clear sky pixels. To illustrate this, we present an application that constructs obstruction-free composites of images acquired on different dates in support of a method for vegetation change detection.

Problems of thermal IR-imaging in evaluation of burn wounds

International Nuclear Information System (INIS)

Nowakowski, A.

2009-01-01

Results of the research devoted to application of thermal IR-imaging in diagnostics of burn wounds are discussed. The main aim of the work was to develop an effective method for quantitative evaluation of the depth of a burn wound and for classification of regions for surgical treatment. The criterion of determination the area of the wound to be treated surgically is the time, which should not exceed three weeks for natural healing of a burn wound. Prediction that the healing process may last longer is concluded by immediate surgical intervention. We concentrate on using for this purpose QIRT - NDT TI methods (Quantitative Infra-Red Thermography - Non-Destructive Testing Thermal Imaging); especially - active dynamic thermography - ADT. In this work both, classical thermography using a high quality thermal camera as well as ADT are applied and the results of analysis are joined, allowing multimodality diagnostic approach and improved classification of burns requiring surgical treatment. Now our work in application of thermal imaging in determination of burns is continued for around 10 years, as the first publication showing our methodology was presented in 1999. In 2001, during the Thermosense conference, we have been awarded the Andronicos Kantsios Award for the work on Medical applications of model based dynamic thermography. Important reports of our experience in classical as well as ADT thermography are already published. Now we concentrate on practical aspects of the problem, trying to construct a measuring set to be operative even by not experienced staff and meeting all of necessary requirements for clinical applications. (author)

Benefits of cloud computing for PACS and archiving.

Science.gov (United States)

Koch, Patrick

2012-01-01

The goal of cloud-based services is to provide easy, scalable access to computing resources and IT services. The healthcare industry requires a private cloud that adheres to government mandates designed to ensure privacy and security of patient data while enabling access by authorized users. Cloud-based computing in the imaging market has evolved from a service that provided cost effective disaster recovery for archived data to fully featured PACS and vendor neutral archiving services that can address the needs of healthcare providers of all sizes. Healthcare providers worldwide are now using the cloud to distribute images to remote radiologists while supporting advanced reading tools, deliver radiology reports and imaging studies to referring physicians, and provide redundant data storage. Vendor managed cloud services eliminate large capital investments in equipment and maintenance, as well as staffing for the data center--creating a reduction in total cost of ownership for the healthcare provider.

Integrated cloud-aerosol-radiation product using CERES, MODIS, CALIPSO, and CloudSat data

Science.gov (United States)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave; Stephens, Graeme; Partain, Philip

2007-10-01

This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the Aqua Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-MODIS analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3-dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-MODIS global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

Validation of Cloud Properties From Multiple Satellites Using CALIOP Data

Science.gov (United States)

Yost, Christopher R.; Minnis, Patrick; Bedka, Kristopher M.; Heck, Patrick W.; Palikonda, Rabindra; Sun-Mack, Sunny; Trepte, Qing

2016-01-01

The NASA Langley Satellite ClOud and Radiative Property retrieval System (SatCORPS) is routinely applied to multispectral imagery from several geostationary and polar-orbiting imagers to retrieve cloud properties for weather and climate applications. Validation of the retrievals with independent datasets is continuously ongoing in order to understand differences caused by calibration, spatial resolution, viewing geometry, and other factors. The CALIOP instrument provides a decade of detailed cloud observations which can be used to evaluate passive imager retrievals of cloud boundaries, thermodynamic phase, cloud optical depth, and water path on a global scale. This paper focuses on comparisons of CALIOP retrievals to retrievals from MODIS, VIIRS, AVHRR, GOES, SEVIRI, and MTSAT. CALIOP is particularly skilled at detecting weakly-scattering cirrus clouds with optical depths less than approx. 0.5. These clouds are often undetected by passive imagers and the effect this has on the property retrievals is discussed.

Terrestrial laser scanning point clouds time series for the monitoring of slope movements: displacement measurement using image correlation and 3D feature tracking

Science.gov (United States)

Bornemann, Pierrick; Jean-Philippe, Malet; André, Stumpf; Anne, Puissant; Julien, Travelletti

2016-04-01

Dense multi-temporal point clouds acquired with terrestrial laser scanning (TLS) have proved useful for the study of structure and kinematics of slope movements. Most of the existing deformation analysis methods rely on the use of interpolated data. Approaches that use multiscale image correlation provide a precise and robust estimation of the observed movements; however, for non-rigid motion patterns, these methods tend to underestimate all the components of the movement. Further, for rugged surface topography, interpolated data introduce a bias and a loss of information in some local places where the point cloud information is not sufficiently dense. Those limits can be overcome by using deformation analysis exploiting directly the original 3D point clouds assuming some hypotheses on the deformation (e.g. the classic ICP algorithm requires an initial guess by the user of the expected displacement patterns). The objective of this work is therefore to propose a deformation analysis method applied to a series of 20 3D point clouds covering the period October 2007 - October 2015 at the Super-Sauze landslide (South East French Alps). The dense point clouds have been acquired with a terrestrial long-range Optech ILRIS-3D laser scanning device from the same base station. The time series are analyzed using two approaches: 1) a method of correlation of gradient images, and 2) a method of feature tracking in the raw 3D point clouds. The estimated surface displacements are then compared with GNSS surveys on reference targets. Preliminary results tend to show that the image correlation method provides a good estimation of the displacement fields at first order, but shows limitations such as the inability to track some deformation patterns, and the use of a perspective projection that does not maintain original angles and distances in the correlated images. Results obtained with 3D point clouds comparison algorithms (C2C, ICP, M3C2) bring additional information on the

All-sky photogrammetry techniques to georeference a cloud field

Science.gov (United States)

Crispel, Pierre; Roberts, Gregory

2018-01-01

In this study, we present a novel method of identifying and geolocalizing cloud field elements from a portable all-sky camera stereo network based on the ground and oriented towards zenith. The methodology is mainly based on stereophotogrammetry which is a 3-D reconstruction technique based on triangulation from corresponding stereo pixels in rectified images. In cases where clouds are horizontally separated, identifying individual positions is performed with segmentation techniques based on hue filtering and contour detection algorithms. Macroscopic cloud field characteristics such as cloud layer base heights and velocity fields are also deduced. In addition, the methodology is fitted to the context of measurement campaigns which impose simplicity of implementation, auto-calibration, and portability. Camera internal geometry models are achieved a priori in the laboratory and validated to ensure a certain accuracy in the peripheral parts of the all-sky image. Then, stereophotogrammetry with dense 3-D reconstruction is applied with cameras spaced 150 m apart for two validation cases. The first validation case is carried out with cumulus clouds having a cloud base height at 1500 m a.g.l. The second validation case is carried out with two cloud layers: a cumulus fractus layer with a base height at 1000 m a.g.l. and an altocumulus stratiformis layer with a base height of 2300 m a.g.l. Velocity fields at cloud base are computed by tracking image rectangular patterns through successive shots. The height uncertainty is estimated by comparison with a Vaisala CL31 ceilometer located on the site. The uncertainty on the horizontal coordinates and on the velocity field are theoretically quantified by using the experimental uncertainties of the cloud base height and camera orientation. In the first cumulus case, segmentation of the image is performed to identify individuals clouds in the cloud field and determine the horizontal positions of the cloud centers.

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Base Height (CBH) Environmental Data Record (EDR) from IDPS

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of Cloud Base Heights (CBH) from the Visible Infrared Imaging Radiometer Suite...

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Cover Layer (CCL) Environmental Data Record (EDR) from IDPS

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality Environmental Data Record (EDR) of Cloud Cover Layers (CCL) from the Visible Infrared Imaging Radiometer Suite (VIIRS)...

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Optical Thickness (COT) Environmental Data Record (EDR) from IDPS

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of Cloud Optical Thickness (COT) from the Visible Infrared Imaging Radiometer Suite...

Point Cloud Classification of Tesserae from Terrestrial Laser Data Combined with Dense Image Matching for Archaeological Information Extraction

Science.gov (United States)

Poux, F.; Neuville, R.; Billen, R.

2017-08-01

Reasoning from information extraction given by point cloud data mining allows contextual adaptation and fast decision making. However, to achieve this perceptive level, a point cloud must be semantically rich, retaining relevant information for the end user. This paper presents an automatic knowledge-based method for pre-processing multi-sensory data and classifying a hybrid point cloud from both terrestrial laser scanning and dense image matching. Using 18 features including sensor's biased data, each tessera in the high-density point cloud from the 3D captured complex mosaics of Germigny-des-prés (France) is segmented via a colour multi-scale abstraction-based featuring extracting connectivity. A 2D surface and outline polygon of each tessera is generated by a RANSAC plane extraction and convex hull fitting. Knowledge is then used to classify every tesserae based on their size, surface, shape, material properties and their neighbour's class. The detection and semantic enrichment method shows promising results of 94% correct semantization, a first step toward the creation of an archaeological smart point cloud.

Cloud fraction and cloud base measurements from scanning Doppler lidar during WFIP-2

Science.gov (United States)

Bonin, T.; Long, C.; Lantz, K. O.; Choukulkar, A.; Pichugina, Y. L.; McCarty, B.; Banta, R. M.; Brewer, A.; Marquis, M.

2017-12-01

The second Wind Forecast Improvement Project (WFIP-2) consisted of an 18-month field deployment of a variety of instrumentation with the principle objective of validating and improving NWP forecasts for wind energy applications in complex terrain. As a part of the set of instrumentation, several scanning Doppler lidars were installed across the study domain to primarily measure profiles of the mean wind and turbulence at high-resolution within the planetary boundary layer. In addition to these measurements, Doppler lidar observations can be used to directly quantify the cloud fraction and cloud base, since clouds appear as a high backscatter return. These supplementary measurements of clouds can then be used to validate cloud cover and other properties in NWP output. Herein, statistics of the cloud fraction and cloud base height from the duration of WFIP-2 are presented. Additionally, these cloud fraction estimates from Doppler lidar are compared with similar measurements from a Total Sky Imager and Radiative Flux Analysis (RadFlux) retrievals at the Wasco site. During mostly cloudy to overcast conditions, estimates of the cloud radiating temperature from the RadFlux methodology are also compared with Doppler lidar measured cloud base height.

Cirrus Cloud Optical and Microphysical Property Retrievals from eMAS During SEAC4RS Using Bi-Spectral Reflectance Measurements Within the 1.88 micron Water Vapor Absorption Band

Science.gov (United States)

Meyer, K.; Platnick, S.; Arnold, G. T.; Holz, R. E.; Veglio, P.; Yorks, J.; Wang, C.

2016-01-01

Previous bi-spectral imager retrievals of cloud optical thickness (COT) and effective particle radius (CER) based on the Nakajima and King (1990) approach, such as those of the operational MODIS cloud optical property retrieval product (MOD06), have typically paired a non-absorbing visible or near-infrared wavelength, sensitive to COT, with an absorbing shortwave or midwave infrared wavelength sensitive to CER. However, in practice it is only necessary to select two spectral channels that exhibit a strong contrast in cloud particle absorption. Here it is shown, using eMAS observations obtained during NASAs SEAC4RS field campaign, that selecting two absorbing wavelength channels within the broader 1.88 micron water vapor absorption band, namely the 1.83 and 1.93 micron channels that have sufficient differences in ice crystal single scattering albedo, can yield COT and CER retrievals for thin to moderately thick single-layer cirrus that are reasonably consistent with other solar and IR imager-based and lidar-based retrievals. A distinct advantage of this channel selection for cirrus cloud retrievals is that the below cloud water vapor absorption minimizes the surface contribution to measured cloudy TOA reflectance, in particular compared to the solar window channels used in heritage retrievals such as MOD06. This reduces retrieval uncertainty resulting from errors in the surface reflectance assumption, as well as reduces the frequency of retrieval failures for thin cirrus clouds.

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Type and Phase Environmental Data Record (EDR) from NDE

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of cloud type and phase from the Visible Infrared Imaging Radiometer Suite (VIIRS)...

A cloud-based system for automatic glaucoma screening.

Science.gov (United States)

Fengshou Yin; Damon Wing Kee Wong; Ying Quan; Ai Ping Yow; Ngan Meng Tan; Gopalakrishnan, Kavitha; Beng Hai Lee; Yanwu Xu; Zhuo Zhang; Jun Cheng; Jiang Liu

2015-08-01

In recent years, there has been increasing interest in the use of automatic computer-based systems for the detection of eye diseases including glaucoma. However, these systems are usually standalone software with basic functions only, limiting their usage in a large scale. In this paper, we introduce an online cloud-based system for automatic glaucoma screening through the use of medical image-based pattern classification technologies. It is designed in a hybrid cloud pattern to offer both accessibility and enhanced security. Raw data including patient's medical condition and fundus image, and resultant medical reports are collected and distributed through the public cloud tier. In the private cloud tier, automatic analysis and assessment of colour retinal fundus images are performed. The ubiquitous anywhere access nature of the system through the cloud platform facilitates a more efficient and cost-effective means of glaucoma screening, allowing the disease to be detected earlier and enabling early intervention for more efficient intervention and disease management.

First correlated measurements of the shape and light scattering properties of cloud particles using the new Particle Habit Imaging and Polar Scattering (PHIPS probe

Directory of Open Access Journals (Sweden)

A. Abdelmonem

2011-10-01

Full Text Available Studying the radiative impact of cirrus clouds requires knowledge of the relationship between their microphysics and the single scattering properties of cloud particles. Usually, this relationship is obtained by modeling the optical scattering properties from in situ measurements of ice crystal size distributions. The measured size distribution and the assumed particle shape might be erroneous in case of non-spherical ice particles. We present here a novel optical sensor (the Particle Habit Imaging and Polar Scattering probe, PHIPS designed to measure simultaneously the 3-D morphology and the corresponding optical and microphysical parameters of individual cloud particles. Clouds containing particles ranging from a few micrometers to about 800 μm diameter in size can be characterized systematically with an optical resolution power of 2 μm and polar scattering resolution of 1° for forward scattering directions (from 1° to 10° and 8° for side and backscattering directions (from 18° to 170°. The maximum acquisition rates for scattering phase functions and images are 262 KHz and 10 Hz, respectively. Some preliminary results collected in two ice cloud campaigns conducted in the AIDA cloud simulation chamber are presented. PHIPS showed reliability in operation and produced size distributions and images comparable to those given by other certified cloud particles instruments. A 3-D model of a hexagonal ice plate is constructed and the corresponding scattering phase function is compared to that modeled using the Ray Tracing with Diffraction on Facets (RTDF program. PHIPS is a highly promising novel airborne optical sensor for studying the radiative impact of cirrus clouds and correlating the particle habit-scattering properties which will serve as a reference for other single, or multi-independent, measurement instruments.

First correlated measurements of the shape and light scattering properties of cloud particles using the new Particle Habit Imaging and Polar Scattering (PHIPS) probe

Science.gov (United States)

Abdelmonem, A.; Schnaiter, M.; Amsler, P.; Hesse, E.; Meyer, J.; Leisner, T.

2011-10-01

Studying the radiative impact of cirrus clouds requires knowledge of the relationship between their microphysics and the single scattering properties of cloud particles. Usually, this relationship is obtained by modeling the optical scattering properties from in situ measurements of ice crystal size distributions. The measured size distribution and the assumed particle shape might be erroneous in case of non-spherical ice particles. We present here a novel optical sensor (the Particle Habit Imaging and Polar Scattering probe, PHIPS) designed to measure simultaneously the 3-D morphology and the corresponding optical and microphysical parameters of individual cloud particles. Clouds containing particles ranging from a few micrometers to about 800 μm diameter in size can be characterized systematically with an optical resolution power of 2 μm and polar scattering resolution of 1° for forward scattering directions (from 1° to 10°) and 8° for side and backscattering directions (from 18° to 170°). The maximum acquisition rates for scattering phase functions and images are 262 KHz and 10 Hz, respectively. Some preliminary results collected in two ice cloud campaigns conducted in the AIDA cloud simulation chamber are presented. PHIPS showed reliability in operation and produced size distributions and images comparable to those given by other certified cloud particles instruments. A 3-D model of a hexagonal ice plate is constructed and the corresponding scattering phase function is compared to that modeled using the Ray Tracing with Diffraction on Facets (RTDF) program. PHIPS is a highly promising novel airborne optical sensor for studying the radiative impact of cirrus clouds and correlating the particle habit-scattering properties which will serve as a reference for other single, or multi-independent, measurement instruments.

INFRARED DARK CLOUDS IN THE SMALL MAGELLANIC CLOUD?

International Nuclear Information System (INIS)

Lee, Min-Young; Stanimirovic, Snezana; Devine, Kathryn E.; Ott, Juergen; Van Loon, Jacco Th.; Oliveira, Joana M.; Bolatto, Alberto D.; Jones, Paul A.; Cunningham, Maria R.

2009-01-01

We have applied the unsharp-masking technique to the 24 μm image of the Small Magellanic Cloud (SMC), obtained with the Spitzer Space Telescope, to search for high-extinction regions. This technique has been used to locate very dense and cold interstellar clouds in the Galaxy, particularly infrared dark clouds (IRDCs). Fifty-five candidate regions of high extinction, namely, high-contrast regions (HCRs), have been identified from the generated decremental contrast image of the SMC. Most HCRs are located in the southern bar region and mainly distributed in the outskirts of CO clouds, but most likely contain a significant amount of H 2 . HCRs have a peak contrast at 24 μm of 2%-2.5% and a size of 8-14 pc. This corresponds to the size of typical and large Galactic IRDCs, but Galactic IRDCs are 2-3 times darker at 24 μm than our HCRs. To constrain the physical properties of the HCRs, we have performed NH 3 , N 2 H + , HNC, HCO + , and HCN observations toward one of the HCRs, HCR LIRS36-east, using the Australia Telescope Compact Array and the Mopra single-dish radio telescope. We did not detect any molecular line emission, however, our upper limits to the column densities of molecular species suggest that HCRs are most likely moderately dense with n ∼ 10 3 cm -3 . This volume density is in agreement with predictions for the cool atomic phase in low-metallicity environments. We suggest that HCRs may be tracing clouds at the transition from atomic to molecule-dominated medium, and could be a powerful way to study early stages of gas condensation in low-metallicity galaxies. Alternatively, if made up of dense molecular clumps <0.5 pc in size, HCRs could be counterparts of Galactic IRDCs, and/or regions with highly unusual abundance of very small dust grains.

Measurement of optical blurring in a turbulent cloud chamber

Science.gov (United States)

Packard, Corey D.; Ciochetto, David S.; Cantrell, Will H.; Roggemann, Michael C.; Shaw, Raymond A.

2016-10-01

Earth's atmosphere can significantly impact the propagation of electromagnetic radiation, degrading the performance of imaging systems. Deleterious effects of the atmosphere include turbulence, absorption and scattering by particulates. Turbulence leads to blurring, while absorption attenuates the energy that reaches imaging sensors. The optical properties of aerosols and clouds also impact radiation propagation via scattering, resulting in decorrelation from unscattered light. Models have been proposed for calculating a point spread function (PSF) for aerosol scattering, providing a method for simulating the contrast and spatial detail expected when imaging through atmospheres with significant aerosol optical depth. However, these synthetic images and their predicating theory would benefit from comparison with measurements in a controlled environment. Recently, Michigan Technological University (MTU) has designed a novel laboratory cloud chamber. This multiphase, turbulent "Pi Chamber" is capable of pressures down to 100 hPa and temperatures from -55 to +55°C. Additionally, humidity and aerosol concentrations are controllable. These boundary conditions can be combined to form and sustain clouds in an instrumented laboratory setting for measuring the impact of clouds on radiation propagation. This paper describes an experiment to generate mixing and expansion clouds in supersaturated conditions with salt aerosols, and an example of measured imagery viewed through the generated cloud is shown. Aerosol and cloud droplet distributions measured during the experiment are used to predict scattering PSF and MTF curves, and a methodology for validating existing theory is detailed. Measured atmospheric inputs will be used to simulate aerosol-induced image degradation for comparison with measured imagery taken through actual cloud conditions. The aerosol MTF will be experimentally calculated and compared to theoretical expressions. The key result of this study is the

The Global and Local Characters of Mars Perihelion Cloud Trails

Science.gov (United States)

Clancy, R. T.; Wolff, M. J.; Smith, M. D.; Cantor, B. A.; Spiga, A.

2014-12-01

We present the seasonal and spatial distribution of Mars perihelion cloud trails as mapped from Mars Reconnaissance Orbiter (MRO) MARCI (Mars Color Imager) imaging observations in 2 ultraviolet and 3 visible filters. The extended 2007-2013 period of MARCI daily global image maps reveals the widespread distribution of these high altitude clouds, which are somewhat paradoxically associated with specific surface regions. They appear as longitudinally extended (300-700 km) cloud trails with distinct leading plumes of substantial ice cloud optical depths (0.02-0.2) for such high altitudes of occurrence (40-50 km, from cloud surface shadow measurements). These plumes generate small ice particles (Reff~1 to reflect locally elevated mesospheric water ice formation that may impact the global expression of mesospheric water ice aerosols.

Image transmission in mid-IR using a solid state laser pumped optical parametric oscillator

Science.gov (United States)

Prasad, Narasimha S.; Kratovil, Pat; Magee, James R.

2002-04-01

In this paper, image transmission using a mid-wave IR (MWIR) optical transceiver based free-space data link under low visibility conditions is presented. The all-solid-state MWIR transceiver primarily consisted of a passively Q-switched, short-pulsed Nd:YAG laser pumping a periodically poled lithium niobate (PPLN) based optical parametric oscillator and a Dember effect detector. The MILES transceiver generates pulse position waveforms. The optical data link consisting of transmitter drive electronics, pulse conditioning electronics and a computer generating pulses compatible with the 2400-baud rate RS232 receiver was utilized. Data formatting and RS232 transmission and reception were achieved using a computer. Data formatting transformed an arbitrary image file format compatible with the basic operation of pump laser. Images were transmitted at a date rate of 2400 kbits/sec with 16 bits/pixel. Test images consisting of 50X40 pixels and 100X80 pixels were transmitted through free-space filled with light fog up to 120 ft. Besides optical parametric oscillators, the proposed concept can be extended to optical parametric amplifiers, Raman lasers and other nonlinear optical devices to achieve multi-functionality.

Mapping low- and high-density clouds in astrophysical nebulae by imaging forbidden line emission

Science.gov (United States)

Steiner, J. E.; Menezes, R. B.; Ricci, T. V.; Oliveira, A. S.

2009-06-01

Emission line ratios have been essential for determining physical parameters such as gas temperature and density in astrophysical gaseous nebulae. With the advent of panoramic spectroscopic devices, images of regions with emission lines related to these physical parameters can, in principle, also be produced. We show that, with observations from modern instruments, it is possible to transform images taken from density-sensitive forbidden lines into images of emission from high- and low-density clouds by applying a transformation matrix. In order to achieve this, images of the pairs of density-sensitive lines as well as the adjacent continuum have to be observed and combined. We have computed the critical densities for a series of pairs of lines in the infrared, optical, ultraviolet and X-rays bands, and calculated the pair line intensity ratios in the high- and low-density limit using a four- and five-level atom approximation. In order to illustrate the method, we applied it to Gemini Multi-Object Spectrograph (GMOS) Integral Field Unit (GMOS-IFU) data of two galactic nuclei. We conclude that this method provides new information of astrophysical interest, especially for mapping low- and high-density clouds; for this reason, we call it `the ld/hd imaging method'. Based on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the National Science Foundation on behalf of the Gemini partnership: the National Science Foundation (United States); the Science and Technology Facilities Council (United Kingdom); the National Research Council (Canada), CONICYT (Chile); the Australian Research Council (Australia); Ministério da Ciência e Tecnologia (Brazil) and Secretaria de Ciencia y Tecnologia (Argentina). E-mail: steiner@astro.iag.usp.br

Cloud Spirals and Outflow in Tropical Storm Katrina

Science.gov (United States)

2005-01-01

On Tuesday, August 30, 2005, NASA's Multi-angle Imaging SpectroRadiometer retrieved cloud-top heights and cloud-tracked wind velocities for Tropical Storm Katrina, as the center of the storm was situated over the Tennessee valley. At this time Katrina was weakening and no longer classified as a hurricane, and would soon become an extratropical depression. Measurements such as these can help atmospheric scientists compare results of computer-generated hurricane simulations with observed conditions, ultimately allowing them to better represent and understand physical processes occurring in hurricanes. Because air currents are influenced by the Coriolis force (caused by the rotation of the Earth), Northern Hemisphere hurricanes are characterized by an inward counterclockwise (cyclonic) rotation towards the center. It is less widely known that, at high altitudes, outward-spreading bands of cloud rotate in a clockwise (anticyclonic) direction. The image on the left shows the retrieved cloud-tracked winds as red arrows superimposed across the natural color view from MISR's nadir (vertical-viewing) camera. Both the counter-clockwise motion for the lower-level storm clouds and the clockwise motion for the upper clouds are apparent in these images. The speeds for the clockwise upper level winds have typical values between 40 and 45 m/s (144-162 km/hr). The low level counterclockwise winds have typical values between 7 and 24 m/s (25-86 km/hr), weakening with distance from the storm center. The image on the right displays the cloud-top height retrievals. Areas where cloud heights could not be retrieved are shown in dark gray. Both the wind velocity vectors and the cloud-top height field were produced by automated computer recognition of displacements in spatial features within successive MISR images acquired at different view angles and at slightly different times. The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously, viewing the entire globe

Imaging and mapping the impact of clouds on skyglow with all-sky photometry.

Science.gov (United States)

Jechow, Andreas; Kolláth, Zoltán; Ribas, Salvador J; Spoelstra, Henk; Hölker, Franz; Kyba, Christopher C M

2017-07-27

Artificial skyglow is constantly growing on a global scale, with potential ecological consequences ranging up to affecting biodiversity. To understand these consequences, worldwide mapping of skyglow for all weather conditions is urgently required. In particular, the amplification of skyglow by clouds needs to be studied, as clouds can extend the reach of skyglow into remote areas not affected by light pollution on clear nights. Here we use commercial digital single lens reflex cameras with fisheye lenses for all-sky photometry. We track the reach of skyglow from a peri-urban into a remote area on a clear and a partly cloudy night by performing transects from the Spanish town of Balaguer towards Montsec Astronomical Park. From one single all-sky image, we extract zenith luminance, horizontal and scalar illuminance. While zenith luminance reaches near-natural levels at 5 km distance from the town on the clear night, similar levels are only reached at 27 km on the partly cloudy night. Our results show the dramatic increase of the reach of skyglow even for moderate cloud coverage at this site. The powerful and easy-to-use method promises to be widely applicable for studies of ecological light pollution on a global scale also by non-specialists in photometry.

Strategies for cloud-top phase determination: differentiation between thin cirrus clouds and snow in manual (ground truth) analyses

Science.gov (United States)

Hutchison, Keith D.; Etherton, Brian J.; Topping, Phillip C.

1996-12-01

Quantitative assessments on the performance of automated cloud analysis algorithms require the creation of highly accurate, manual cloud, no cloud (CNC) images from multispectral meteorological satellite data. In general, the methodology to create ground truth analyses for the evaluation of cloud detection algorithms is relatively straightforward. However, when focus shifts toward quantifying the performance of automated cloud classification algorithms, the task of creating ground truth images becomes much more complicated since these CNC analyses must differentiate between water and ice cloud tops while ensuring that inaccuracies in automated cloud detection are not propagated into the results of the cloud classification algorithm. The process of creating these ground truth CNC analyses may become particularly difficult when little or no spectral signature is evident between a cloud and its background, as appears to be the case when thin cirrus is present over snow-covered surfaces. In this paper, procedures are described that enhance the researcher's ability to manually interpret and differentiate between thin cirrus clouds and snow-covered surfaces in daytime AVHRR imagery. The methodology uses data in up to six AVHRR spectral bands, including an additional band derived from the daytime 3.7 micron channel, which has proven invaluable for the manual discrimination between thin cirrus clouds and snow. It is concluded that while the 1.6 micron channel remains essential to differentiate between thin ice clouds and snow. However, this capability that may be lost if the 3.7 micron data switches to a nighttime-only transmission with the launch of future NOAA satellites.

Limb clouds and dust on Mars from images obtained by the Visual Monitoring Camera (VMC) onboard Mars Express

Science.gov (United States)

Sánchez-Lavega, A.; Chen-Chen, H.; Ordoñez-Etxeberria, I.; Hueso, R.; del Río-Gaztelurrutia, T.; Garro, A.; Cardesín-Moinelo, A.; Titov, D.; Wood, S.

2018-01-01

The Visual Monitoring Camera (VMC) onboard the Mars Express (MEx) spacecraft is a simple camera aimed to monitor the release of the Beagle-2 lander on Mars Express and later used for public outreach. Here, we employ VMC as a scientific instrument to study and characterize high altitude aerosols events (dust and condensates) observed at the Martian limb. More than 21,000 images taken between 2007 and 2016 have been examined to detect and characterize elevated layers of dust in the limb, dust storms and clouds. We report a total of 18 events for which we give their main properties (areographic location, maximum altitude, limb projected size, Martian solar longitude and local time of occurrence). The top altitudes of these phenomena ranged from 40 to 85 km and their horizontal extent at the limb ranged from 120 to 2000 km. They mostly occurred at Equatorial and Tropical latitudes (between ∼30°N and 30°S) at morning and afternoon local times in the southern fall and northern winter seasons. None of them are related to the orographic clouds that typically form around volcanoes. Three of these events have been studied in detail using simultaneous images taken by the MARCI instrument onboard Mars Reconnaissance Orbiter (MRO) and studying the properties of the atmosphere using the predictions from the Mars Climate Database (MCD) General Circulation Model. This has allowed us to determine the three-dimensional structure and nature of these events, with one of them being a regional dust storm and the two others water ice clouds. Analyses based on MCD and/or MARCI images for the other cases studied indicate that the rest of the events correspond most probably to water ice clouds.

CONTOURS BASED APPROACH FOR THERMAL IMAGE AND TERRESTRIAL POINT CLOUD REGISTRATION

Directory of Open Access Journals (Sweden)

A. Bennis

2013-07-01

Full Text Available Building energetic performances strongly depend on the thermal insulation. However the performance of the insulation materials tends to decrease over time which necessitates the continuous monitoring of the building in order to detect and repair the anomalous zones. In this paper, it is proposed to couple 2D infrared images representing the surface temperature of the building with 3D point clouds acquired with Terrestrial Laser Scanner (TLS resulting in a semi-automatic approach allowing the texturation of TLS data with infrared image of buildings. A contour-based algorithm is proposed whose main features are : 1 the extraction of high level primitive is not required 2 the use of projective transform allows to handle perspective effects 3 a point matching refinement procedure allows to cope with approximate control point selection. The procedure is applied to test modules aiming at investigating the thermal properties of material.

Active probing of cloud multiple scattering, optical depth, vertical thickness, and liquid water content using wide-angle imaging lidar

Science.gov (United States)

Love, Steven P.; Davis, Anthony B.; Rohde, Charles A.; Tellier, Larry; Ho, Cheng

2002-09-01

At most optical wavelengths, laser light in a cloud lidar experiment is not absorbed but merely scattered out of the beam, eventually escaping the cloud via multiple scattering. There is much information available in this light scattered far from the input beam, information ignored by traditional 'on-beam' lidar. Monitoring these off-beam returns in a fully space- and time-resolved manner is the essence of our unique instrument, Wide Angle Imaging Lidar (WAIL). In effect, WAIL produces wide-field (60-degree full-angle) 'movies' of the scattering process and records the cloud's radiative Green functions. A direct data product of WAIL is the distribution of photon path lengths resulting from multiple scattering in the cloud. Following insights from diffusion theory, we can use the measured Green functions to infer the physical thickness and optical depth of the cloud layer, and, from there, estimate the volume-averaged liquid water content. WAIL is notable in that it is applicable to optically thick clouds, a regime in which traditional lidar is reduced to ceilometry. Here we present recent WAIL data on various clouds and discuss the extension of WAIL to full diurnal monitoring by means of an ultra-narrow magneto-optic atomic line filter for daytime measurements.

Active probing of cloud multiple scattering, optical depth, vertical thickness, and liquid water content using wide-angle imaging LIDAR

International Nuclear Information System (INIS)

Love, Steven P.; Davis, Anthony B.; Rohde, Charles A.; Tellier, Larry L.; Ho, Cheng

2002-01-01

At most optical wavelengths, laser light in a cloud lidar experiment is not absorbed but merely scattered out of the beam, eventually escaping the cloud via multiple scattering. There is much information available in this light scattered far from the input beam, information ignored by traditional 'on-beam' lidar. Monitoring these off-beam returns in a fully space- and time-resolved manner is the essence of our unique instrument, Wide Angle Imaging Lidar (WAIL). In effect, WAIL produces wide-field (60-degree full-angle) 'movies' of the scattering process and records the cloud's radiative Green functions. A direct data product of WAIL is the distribution of photon path lengths resulting from multiple scattering in the cloud. Following insights from diffusion theory, we can use the measured Green functions to infer the physical thickness and optical depth of the cloud layer, and, from there, estimate the volume-averaged liquid water content. WAIL is notable in that it is applicable to optically thick clouds, a regime in which traditional lidar is reduced to ceilometry. Here we present recent WAIL data oti various clouds and discuss the extension of WAIL to full diurnal monitoring by means of an ultra-narrow magneto-optic atomic line filter for daytime measurements.

Automatic registration of iPhone images to laser point clouds of urban structures using shape features

NARCIS (Netherlands)

Sirmacek, B.; Lindenbergh, R.C.; Menenti, M.

2013-01-01

Fusion of 3D airborne laser (LIDAR) data and terrestrial optical imagery can be applied in 3D urban modeling and model up-dating. The most challenging aspect of the fusion procedure is registering the terrestrial optical images on the LIDAR point clouds. In this article, we propose an approach for

A cloud-based multimodality case file for mobile devices.

Science.gov (United States)

Balkman, Jason D; Loehfelm, Thomas W

2014-01-01

Recent improvements in Web and mobile technology, along with the widespread use of handheld devices in radiology education, provide unique opportunities for creating scalable, universally accessible, portable image-rich radiology case files. A cloud database and a Web-based application for radiologic images were developed to create a mobile case file with reasonable usability, download performance, and image quality for teaching purposes. A total of 75 radiology cases related to breast, thoracic, gastrointestinal, musculoskeletal, and neuroimaging subspecialties were included in the database. Breast imaging cases are the focus of this article, as they best demonstrate handheld display capabilities across a wide variety of modalities. This case subset also illustrates methods for adapting radiologic content to cloud platforms and mobile devices. Readers will gain practical knowledge about storage and retrieval of cloud-based imaging data, an awareness of techniques used to adapt scrollable and high-resolution imaging content for the Web, and an appreciation for optimizing images for handheld devices. The evaluation of this software demonstrates the feasibility of adapting images from most imaging modalities to mobile devices, even in cases of full-field digital mammograms, where high resolution is required to represent subtle pathologic features. The cloud platform allows cases to be added and modified in real time by using only a standard Web browser with no application-specific software. Challenges remain in developing efficient ways to generate, modify, and upload radiologic and supplementary teaching content to this cloud-based platform. Online supplemental material is available for this article. ©RSNA, 2014.

Moving image analysis to the cloud: A case study with a genome-scale tomographic study

Energy Technology Data Exchange (ETDEWEB)

Mader, Kevin [4Quant Ltd., Switzerland & Institute for Biomedical Engineering at University and ETH Zurich (Switzerland); Stampanoni, Marco [Institute for Biomedical Engineering at University and ETH Zurich, Switzerland & Swiss Light Source at Paul Scherrer Institut, Villigen (Switzerland)

2016-01-28

Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures.

Moving image analysis to the cloud: A case study with a genome-scale tomographic study

International Nuclear Information System (INIS)

Mader, Kevin; Stampanoni, Marco

2016-01-01

Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures

Exploitation of cloud top characterization from three-channel IR measurements in a physical PMW rain retrieval algorithm

Directory of Open Access Journals (Sweden)

F. Torricella

2006-01-01

Full Text Available Rainfall intensity estimates by passive microwave (PMW measurements from space perform generally better over the sea surface with respect to land, due to the problems in separating true rain signatures from those produced by surfaces having similar spectral behaviour (e.g. snow, ice, desert and semiarid grounds. The screening procedure aimed at recognizing the various surface types and delimit precipitation is based on tests that rely on PMW measurements only and global thresholds. The shortcoming is that the approach tries to discard spurious precipitating features (often detected over the land-sea border thus leading to no-rain conservative tests and thresholds. The TRMM mission, with its long record of simultaneous data from the Visible and Infrared Radiometer System (VIRS, the TRMM Microwave Imager (TMI and rain profiles from the Precipitation Radar (PR allows for unambiguous testing of the usefulness of cloud top characterization in rain detection. An intense precipitation event over the North Africa is analysed exploiting a night microphysical RGB scheme applied to VIRS measurements to classify and characterize the components of the observed scenario and to discriminate the various types of clouds. This classification is compared to the rain intensity maps derived from TMI by means of the Goddard profiling algorithm and to the near-surface rain intensities derived from PR. The comparison allows to quantify the difference between the two rain retrievals and to assess the usefulness of RGB analysis in identifying areas of precipitation.

Neural network cloud top pressure and height for MODIS

Science.gov (United States)

Håkansson, Nina; Adok, Claudia; Thoss, Anke; Scheirer, Ronald; Hörnquist, Sara

2018-06-01

Cloud top height retrieval from imager instruments is important for nowcasting and for satellite climate data records. A neural network approach for cloud top height retrieval from the imager instrument MODIS (Moderate Resolution Imaging Spectroradiometer) is presented. The neural networks are trained using cloud top layer pressure data from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) dataset. Results are compared with two operational reference algorithms for cloud top height: the MODIS Collection 6 Level 2 height product and the cloud top temperature and height algorithm in the 2014 version of the NWC SAF (EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting) PPS (Polar Platform System). All three techniques are evaluated using both CALIOP and CPR (Cloud Profiling Radar for CloudSat (CLOUD SATellite)) height. Instruments like AVHRR (Advanced Very High Resolution Radiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) contain fewer channels useful for cloud top height retrievals than MODIS, therefore several different neural networks are investigated to test how infrared channel selection influences retrieval performance. Also a network with only channels available for the AVHRR1 instrument is trained and evaluated. To examine the contribution of different variables, networks with fewer variables are trained. It is shown that variables containing imager information for neighboring pixels are very important. The error distributions of the involved cloud top height algorithms are found to be non-Gaussian. Different descriptive statistic measures are presented and it is exemplified that bias and SD (standard deviation) can be misleading for non-Gaussian distributions. The median and mode are found to better describe the tendency of the error distributions and IQR (interquartile range) and MAE (mean absolute error) are found

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Effective Particle Size (CEPS) Environmental Data Record (EDR) from IDPS

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of Cloud Effective Particle Size (CEPS) from the Visible Infrared Imaging Radiometer...

Identification and Quantification of Microplastics in Wastewater Using Focal Plane Array-Based Reflectance Micro-FT-IR Imaging.

Science.gov (United States)

Tagg, Alexander S; Sapp, Melanie; Harrison, Jesse P; Ojeda, Jesús J

2015-06-16

Microplastics (microplastics in these matrices has not been investigated. Although efficient methods for the analysis of microplastics in sediment samples and marine organisms have been published, no methods have been developed for detecting these pollutants within organic-rich wastewater samples. In addition, there is no standardized method for analyzing microplastics isolated from environmental samples. In many cases, part of the identification protocol relies on visual selection before analysis, which is open to bias. In order to address this, a new method for the analysis of microplastics in wastewater was developed. A pretreatment step using 30% hydrogen peroxide (H2O2) was employed to remove biogenic material, and focal plane array (FPA)-based reflectance micro-Fourier-transform (FT-IR) imaging was shown to successfully image and identify different microplastic types (polyethylene, polypropylene, nylon-6, polyvinyl chloride, polystyrene). Microplastic-spiked wastewater samples were used to validate the methodology, resulting in a robust protocol which was nonselective and reproducible (the overall success identification rate was 98.33%). The use of FPA-based micro-FT-IR spectroscopy also provides a considerable reduction in analysis time compared with previous methods, since samples that could take several days to be mapped using a single-element detector can now be imaged in less than 9 h (circular filter with a diameter of 47 mm). This method for identifying and quantifying microplastics in wastewater is likely to provide an essential tool for further research into the pathways by which microplastics enter the environment.

Detection and retrieval of multi-layered cloud properties using satellite data

Science.gov (United States)

Minnis, Patrick; Sun-Mack, Sunny; Chen, Yan; Yi, Helen; Huang, Jianping; Nguyen, Louis; Khaiyer, Mandana M.

2005-10-01

Four techniques for detecting multilayered clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. A new technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other methods examined here use atmospheric sounding data (CO2-slicing, CO2), BTD, or microwave data. The CO2 and BTD methods are limited to optically thin cirrus over low clouds, while the MWR methods are limited to ocean areas only. This paper explores the use of the BTD and CO2 methods as applied to Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer EOS (AMSR-E) data taken from the Aqua satellite over ocean surfaces. Cloud properties derived from MODIS data for the Clouds and the Earth's Radiant Energy System (CERES) Project are used to classify cloud phase and optical properties. The preliminary results focus on a MODIS image taken off the Uruguayan coast. The combined MW visible infrared (MVI) method is assumed to be the reference for detecting multilayered ice-over-water clouds. The BTD and CO2 techniques accurately match the MVI classifications in only 51 and 41% of the cases, respectively. Much additional study is need to determine the uncertainties in the MVI method and to analyze many more overlapped cloud scenes.

NOAA JPSS Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Height (Top and Base) Environmental Data Record (EDR) from NDE

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains a high quality operational Environmental Data Record (EDR) of cloud height (top and base) from the Visible Infrared Imaging Radiometer Suite...

An assessment of thin cloud detection by applying bidirectional reflectance distribution function model-based background surface reflectance using Geostationary Ocean Color Imager (GOCI): A case study for South Korea

Science.gov (United States)

Kim, Hye-Won; Yeom, Jong-Min; Shin, Daegeun; Choi, Sungwon; Han, Kyung-Soo; Roujean, Jean-Louis

2017-08-01

In this study, a new assessment of thin cloud detection with the application of bidirectional reflectance distribution function (BRDF) model-based background surface reflectance was undertaken by interpreting surface spectra characterized using the Geostationary Ocean Color Imager (GOCI) over a land surface area. Unlike cloud detection over the ocean, the detection of cloud over land surfaces is difficult due to the complicated surface scattering characteristics, which vary among land surface types. Furthermore, in the case of thin clouds, in which the surface and cloud radiation are mixed, it is difficult to detect the clouds in both land and atmospheric fields. Therefore, to interpret background surface reflectance, especially underneath cloud, the semiempirical BRDF model was used to simulate surface reflectance by reflecting solar angle-dependent geostationary sensor geometry. For quantitative validation, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data were used to make a comparison with the proposed cloud masking result. As a result, the new cloud masking scheme resulted in a high probability of detection (POD = 0.82) compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) (POD = 0.808) for all cloud cases. In particular, the agreement between the CALIPSO cloud product and new GOCI cloud mask was over 94% when detecting thin cloud (e.g., altostratus and cirrus) from January 2014 to June 2015. This result is relatively high in comparison with the result from the MODIS Collection 6 cloud mask product (MYD35).