Proceedings ArticleDOI
Building wide area 2-D site models from high resolution fully polarimetric synthetic aperture radar images
S. Kuttikkad,Rama Chellappa +1 more
- pp 389-394
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TLDR
A three stage algorithm-involving detection of possible targets, statistical segmentation of the data into homogeneous regions, and validation of segmentation results-is used for this task.Abstract:
Wide area site models are useful for delineating regions of interest and assisting in tasks like monitoring and change detection They are also useful in registering a newly acquired image to an existing one of the same site, or to a map This paper presents a complete algorithm for building an approximate 2-D wide-area site model from high resolution, polarimetric Synthetic Aperture Radar (SAR) data A three stage algorithm-involving detection of possible targets, statistical segmentation of the data into homogeneous regions, and validation of segmentation results-is used for this task Constant False Alarm Rate (CFAR) detectors are used for target detection, while maximum likelihood labeling is used for initial segmentation Knowledge of the sensor heading and other geometric cues are used to refine the initial segmentation and to extract man-made objects like buildings, and their shadows, as well as roads, from these imagesread more
Citations
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Journal ArticleDOI
Image Analysis and Computer Vision
TL;DR: A bibliography of nearly 1700 references related to computer vision and image analysis, arranged by subject matter is presented, including computational techniques; feature detection and segmentation; image and scene analysis; two-dimensional shape; pattern; color and texture; matching and stereo.
Journal ArticleDOI
Statistical modeling and analysisof high-resolution Synthetic Aperture Radar images
Shyam Kuttikkad,Rama Chellappa +1 more
TL;DR: An overview of popular statistical distributions used to model real, complex, and polarimetric SAR images and two distinct methods of SAR image analysis are focused on: Constant false alarm rate processing for target detection; and pixel classification using statistical models.
Journal ArticleDOI
Knowledge-based control of vision systems
TL;DR: A framework for the development of vision systems that incorporate, along with the executable computer algorithms, the problem-solving knowledge required to obtain optimal performance from them is proposed.
Proceedings ArticleDOI
Target/shadow segmentation and aspect estimation in synthetic aperture radar imagery
TL;DR: Two algorithms are presented for segmenting a target region from background clutter; one based on constant false alarm rate detection, and another histogram based technique that is applied to SAR imagery from the Lincoln Lab ADTS and MSTAR datasets.
Proceedings ArticleDOI
Building 2D wide-area site models from single- and multipass single-polarization SAR data
TL;DR: An algorithm for building a 2D wide area site model from high resolution, single polarization synthetic aperture radar (SAR) data is presented, involving detection of bright pixels, statistical segmentation of the data into homogeneous regions, and labeling/validation of segmentation results.
References
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Book
Introduction to Radar Systems
TL;DR: This chapter discusses Radar Equation, MTI and Pulse Doppler Radar, and Information from Radar Signals, as well as Radar Antenna, Radar Transmitters and Radar Receiver.
Journal ArticleDOI
Radar CFAR Thresholding in Clutter and Multiple Target Situations
TL;DR: A CFAR method is discussed using as the CFAR threshold one single value selected from the so-called ordered statistic, which has some advantages over cell averaging CFAR, especially in cases where more than one target is present within the reference window on which estimation of the local clutter situation is based.
Journal ArticleDOI
K-distribution and polarimetric terrain radar clutter
TL;DR: In this article, a multivariate K-distribution is proposed to model the statistics of fully polarimetric radar data from earth terrain with polarizations HH, HV, VH, and VV.
Journal ArticleDOI
Identification of Terrain Cover Using the Optimum Polarimetric Classifier
TL;DR: In this paper, a systematic approach for the identification of terrain media such as vegetation canopy, forest, and snow-covered fields is developed using the optimum polarimetric classifier.
Proceedings ArticleDOI
Non-Gaussian CFAR techniques for target detection in high resolution SAR images
S. Kuttikkad,Rama Chellappa +1 more
TL;DR: This work uses the Weibull and K distributions to model clutter since they seem to fit observed data better and also include the Rayleigh distribution as a special case in CFAR.