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.

Date Published: 21 November 1995
PDF: 7 pages
Proc. SPIE 2584, Synthetic Aperture Radar and Passive Microwave Sensing, (21 November 1995); doi: 10.1117/12.227132

Published in SPIE Proceedings Vol. 2584:
Synthetic Aperture Radar and Passive Microwave Sensing
Giorgio Franceschetti; Christopher John Oliver; James C. Shiue; Shahram Tajbakhsh, Editor(s)