期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2015
卷号：8
期号：4
页码：191-200
DOI：10.14257/ijsip.2015.8.4.17
出版社：SERSC
摘要：In this paper, we propose a novel game theory based framework for synthetic aperture radar image de-noising and segmentation based change detection. We find out the balance of the two aspects. The Nash game theory helps us find out the balance of segmentation accuracy and overall de-noising performance. In the de-noising part, we adopt the multi-diagonal matrix filter based algorithm to undertake the de-noising mission. Segmentation and change detection are finalized by the state-of-the-art methodologies in which the segmentation procedure transfers the difference map into the change map. As far as time-consuming is concerned, we compare the different methods for generating difference map. Fusion map is selected to be our difference map for image segmentation using fuzzy clustering. The experimental analysis shows the effectiveness and robustness of our propose framework with the comparison of other well-known change detection algorithms under the outer environment of noisy and noise-free. Finally, some potential optimization methods are discussed for future research
