Multichannel SAR segmentation: algorithms and applications

Ronald G. Caves; Shaun Quegan

doi:10.1117/12.227132

21 November 1995 Multichannel SAR segmentation: algorithms and applications

Ronald G. Caves, Shaun Quegan

Proceedings Volume 2584, Synthetic Aperture Radar and Passive Microwave Sensing; (1995) https://doi.org/10.1117/12.227132
Event: Satellite Remote Sensing II, 1995, Paris, France

Abstract

Many emerging SAR applications require imagery which is multi-channel either in time, frequency, or polarization. If SAR segmentation algorithms are going to be of genuine utility they must be applicable to such datasets. Two approaches to multi-channel segmentation are considered: segmenting each channel separately and then recombining the results; and segmenting the multi-channel image as a single entity. In both cases segmentation is based on edge detection and segment growing. The utility of multi-channel segmentation for change detection, classification and analyzing the information content of multi-channel data, is discussed. A multi-temporal ERS-1 image, and a multi-polarized, multi-frequency AIRSAR image of the same agricultural scene, are used for case studies.

Citation Download Citation

Ronald G. Caves and Shaun Quegan "Multichannel SAR segmentation: algorithms and applications", Proc. SPIE 2584, Synthetic Aperture Radar and Passive Microwave Sensing, (21 November 1995); https://doi.org/10.1117/12.227132

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