Multiregion Level-Set Partitioning of Synthetic Aperture Radar Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Target detection in SAR images based on a level set approach
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Flow on noisy terrains: an experimental evaluation
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Identification of martian polygonal patterns using the dynamics of watershed contours
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
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The paper describes a new approach to pattern recognition in synthetic aperture radar (SAR) images. A visual analysis of the images provided by NASA's Magellan mission to Venus has revealed a number of zones showing polygonal-shaped faults on the surface of the planet. The goal of the paper is to provide a method to automate the identification of such zones. The high level of noise in SAR images and its multiplicative nature make automated image analysis difficult and conventional edge detectors, like those based on gradient images, inefficient. We present a scheme based on an improved watershed algorithm and a two-scale analysis. The method extracts potential edges in the SAR image, analyzes the patterns obtained, and decides whether or not the image contains a "polygon area". This scheme can also be applied to other SAR or visual images, for instance in observation of Mars and Jupiter's satellite Europa.