Journal
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
Volume 7, Issue 8, Pages 3248-3261Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSTARS.2014.2344017
Keywords
Change detection; synthetic aperture radar (SAR); thresholding; unimodal; urban
Categories
Funding
- Swedish National Space Board
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Unsupervised change detection in multitemporal single-polarization synthetic aperture radar (SAR) images often involves thresholding of the image change indicator. If one class, which is usually the unchanged class, comprises a disproportionately large part of the scene, the image change indicator may have a unimodal histogram. Image thresholding of such a change indicator is a challenging task. In this paper, we present an automatic and effective approach to the thresholding of the log-ratio change indicator whose histogram may have one mode or more than one mode. A bimodality test is performed to determine whether the histogram of the log-ratio image is unimodal or not. If it has more than one mode, the generalized Kittler and Illingworth thresholding (GKIT) algorithm based on the generalized Gaussian model (GG-GKIT) is used to detect the optimal threshold values. If it is unimodal, the log-ratio image is divided into small regions and a multiscale region selection process is carried out to select regions which are a balanced mixture of unchanged and changed classes. The selected regions are combined to generate a new histogram. The optimal threshold value obtained from the new histogram is then used to separate unchanged pixels from changed pixels in the log-ratio image. Experimental results obtained on multitemporal SAR images of Toronto and Beijing demonstrate the effectiveness of the proposed approach.
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