3 edition of SAR image analysis, modeling, and techniques VI found in the catalog.
SAR image analysis, modeling, and techniques VI
Includes bibliographical references and author index.
|Other titles||Synthetic aperature radar image analysis, modeling, and techniques VI|
|Statement||Francesco Posa, chair/editor ; sponsored ... by SPIE--the International Society for Optical Engineering ; cooperating organizations, SEDO--Sociedad Española de Óptica (Spain), NASA--National Aeronautics and Space Administration, [and] EOS--European Optical Society.|
|Series||SPIE proceedings series ;, v. 5236, Proceedings of SPIE--the International Society for Optical Engineering ;, v. 5236.|
|Contributions||Posa, Francesco., Sociedad Española de Õptica (Spain), United States. National Aeronautics and Space Administration., European Optical Society.|
|LC Classifications||TK6592.S95 S26329 2004|
|The Physical Object|
|Pagination||vii, 210 p. :|
|Number of Pages||210|
|LC Control Number||2004301507|
Abstract. This paper presents a numerical tool able to generate realistic SAR images from accurate vessel models for a given orbital sensor. Its capability to extract high resolution radar signatures converts this SAR simulator in a useful tool for vessel classification studies and, furthermore, to define a future constellation of SAR sensors bound for carry on an automatic vessel monitoring. Bio-Inspired Computation and Applications in Image Processing summarizes the latest developments in bio-inspired computation in image processing, focusing on nature-inspired algorithms that are linked with deep learning, such as ant colony optimization, particle swarm optimization, and bat and firefly algorithms that have recently emerged in.
In direct SAR image segmentation, which generally involves the statistical modeling of SAR data, the removal of speckle noise is considered in the segmentation model. In January , an experiment to investigate SAR imaging of vessels was conducted in the East China Sea. Data acquired are used in this paper to test simulation algorithms of moving ship, dynamic ocean wave, and SAR imaging. Reasonable agreement is obtained when comparisons are made between the simulated and real SAR images.
Texture and image analysis The concept of texture is discussed by Laur (). Before describing the specificity of radar image texture, it is necessary to define the concept of textural element, i.e. the texture elementary unit, smallest homogeneous element of the same radiometry constituting the texture. The assumptions of the classical SAR image generation model lead to a Rayleigh distribution model for the histogram of the SAR image. However, some experimental data such as images of urban areas show impulsive characteristics that correspond to underlying heavy-tailed distributions, which are clearly non-Rayleigh.
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Adshelp[at] The ADS is operated by the Smithsonian Astrophysical Observatory under NASA Cooperative Agreement NNX16AC86A. Get this from a library.
SAR image analysis, modeling, and techniques VI: 8 September,Barcelona, Spain. [Francesco Posa; Sociedad Española de Óptica (Spain.
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Get this from a library. SAR image analysis, modeling, and techniques VI: 8 September,Barcelona, Spain. [Francesco Posa; Society of Photo-optical Instrumentation Engineers.; Sociedad Española de Óptica (Spain); United States. National Aeronautics and Space Administration.; European Optical Society.;].
SAR Image Analysis, Modeling, and Techniques XVI: Authors: Notarnicola, Claudia; Paloscia, Simonetta; Pierdicca, Nazzareno; Mitchard, Edward: Affiliation: AA(EURAC research (Italy)), AB(Istituto di SAR image analysis Applicata Nello Carrara (Italy)), AC(Univ.
degli Studi di Roma La Sapienza (Italy)), AD(The Univ of Edinburgh (United Kingdom)) Publication. SAR image analysis and modeling --Poster session. Series Title: Europto series.; Proceedings of SPIE--the International Society for Optical Engineering, v.
Other Titles: Synthetic aperture radar image analysis, modeling, and techniques: Responsibility: Francesco Posa, chair/editor ; sponsored by CNR--National Research Council of Italy.
Download Citation | Overview for Statistical Modeling of SAR Images | Statistical modeling of SAR images is one of the basic problems of SAR image interpretation. It involves several fields such.
Digital Processing of SAR Data and Image Analysis Techniques. book are believed to be true and accurate at the date of publication. This book focuses on the monitoring and modeling aspects.
An essential reference on polarimetric Synthetic Aperture Radar (SAR), this book uses scattering theory and radiative transfer theory as a basis for its treatment of topics.
It is organized to include theoretical scattering models and SAR data analysis techniques, and presents cutting-edge research on theoretical modelling of terrain surface.
Modeling and Simulation of SAR Image Texture Article (PDF Available) in IEEE Transactions on Geoscience and Remote Sensing 47(10) - November with. Get this from a library. SAR image analysis, modeling, and techniques V: September,Agia Pelagia, Crete, Greece. [Francesco Posa; Society of Photo-optical Instrumentation Engineers.; International Society for Photogrammetry and Remote Sensing.;].
This book maximizes reader insights into the field of mathematical models and methods for the processing of two-dimensional remote sensing images. It presents a broad analysis of the field, encompassing passive and active sensors, hyperspectral images, synthetic aperture radar (SAR), interferometric SAR, and polarimetric SAR data.
SAR autof ocus methods, and to gain mor e insight into their perf ormance, we pr esent a theor etical analysis of these techniques using simple image models. Speci Þ cally,w e consider the intensity-squar ed metric, and a dominant point-tar gets image model.
SAR Image Analysis, Modeling, and Techniques VI, edited by Francesco Posa, Proceedings of SPIE Vol. (SPIE, Bellingham, WA, ) X/04/$15 doi: / Standard SAR-processing methods are based upon the assumption of a scene at rest.
If targets are moving, their positions in the SAR-image are translated in azimuth and defocusing may occur. In this paper, some methods for the detection and imaging of moving targets and the estimation of their real positions are discussed, such as monopulse and DPCA.
DL model fusion; Advanced ML models for high-resolution RS image segmentation and classification; High-resolution RS data fusion (Optical, SAR, and LiDAR) using ML models; High-resolution RS time-series analysis using ML and DL models.
Alireza Taravat Dr. Naoto Yokoya Prof. Jon Atli Benediktsson Prof. Hongjun Su Prof. Cristina Rubio-Escudero. Digital SAR processing is referred to the correlation process and computer vision approaches to utilize the outcome of the image to identify an object from the image.
Thereby, the SAR signal from the image can be examined to extract the optimum Doppler returns. These are necessary for the successful reconstruction of the return signals into an.
Synthetic aperture radar (SAR) provides all-weather ground imaging, but SAR images are quite different from optical images. This post gives an overview of data analysis methods used with SAR and. ADS Classic is now deprecated.
It will be completely retired in October Please redirect your searches to the new ADS modern form or the classic info can be found on our blog.
Abstract. InfoTerra is an innovative market-derived EO-services concept with end-to-end products and service chains addressing end user information requirements in existing and new markets, with the advantage of a dedicated SAR satellite system TerraSAR.
The Infoterra/TerraSAR initiative started as an industrial concept to provide X- and L-band SAR data products from a pair of spacecraft in Sun-synchronous orbit. The mission was proposed by the BNSC and DLR for implementation as an element of the ESA"s Earth Watch programme.
The X-band element evolved into a German national programme between DLR and Astrium GmbH, whereas the TerraSAR .SAR Image Denoising via Clustering-Based Principal Component Analysis Article (PDF Available) in IEEE Transactions on Geoscience and Remote Sensing 52(11) .The building model in Fig.
1(a) has been chosen as it may resemble basic characteristics pertinent to real urban buildings. It is surrounded by flat terrain and its basic form is composed by flat surfaces. Moreover, it contains regular shapes (window corners) which, in real urban scenes, are often related to dominating point signatures in SAR images.