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Proceedings Paper

Adaptive polarimetric change detection and interpretation based on supervised ground-cover classification using SAR and optical imagery
Author(s): Mohsen Ghazel; Jennifer Busler; Vinay Kotamraju; Corey Froese; Guy Aubé
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Paper Abstract

In this paper, we propose and illustrate a methodology for classifying the change detection results generated from repeatpass polarimetric RADARSAT-2 images and segmenting only the changes of interest to a given user while suppressing all other changes. The detected changes are first classified based on generated supervised ground-cover classification of the polarimetric SAR images between which changes were detected. In the absence of reliable ground truth needed for generating supervised classification training sets, we rely on the use of periodically acquired high-resolution, multispectral optical imagery in order to classify the manually selected training sets before computing their classes' statistics from the SAR images. The classified detected changes can then be segmented to isolate the changes of interest, as specified by the user and suppress all other changes. The proposed polarimetric change detection, classification and segmentation method overcomes some of the challenges encountered when visualizing and interpreting typical raw change results. Often these non-classified change detection results tend to be too crowded, as they show all the changes including those of interest to the user as well as other non-relevant changes. Also, some of the changes are difficult to interpret, especially those which are attributed to a mixture of the backscatters. We shall illustrate how to generate, classify and segment polarimetric change detection results from two SAR images over a selected region of interest.

Paper Details

Date Published: 17 May 2012
PDF: 8 pages
Proc. SPIE 8392, Signal Processing, Sensor Fusion, and Target Recognition XXI, 83921G (17 May 2012); doi: 10.1117/12.918811
Show Author Affiliations
Mohsen Ghazel, MDA Systems Ltd. (Canada)
Jennifer Busler, MDA Systems Ltd. (Canada)
Vinay Kotamraju, MDA Systems Ltd. (Canada)
Corey Froese, Alberta Geological Survey (Canada)
Guy Aubé, Canadian Space Agency (Canada)

Published in SPIE Proceedings Vol. 8392:
Signal Processing, Sensor Fusion, and Target Recognition XXI
Ivan Kadar, Editor(s)

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