关键词: 变化检测, 合成孔径雷达, 遥感影像, 阈值聚类, 图切, 水平集

Abstract: Change detection in remote sensing imagery is a significant issue to detect the changes happening during a period of time at the same area. The change detection task based on synthetic aperture radar (SAR) imagery has been widely concerned in recent years due to their independence on time or weather condition. This paper first gives out a brief introduction to the classical steps along with some traditional methods, and then puts its emphasis on the summary of the burgeoning methods proposed recently. By improving the traditional methods, these state-of-the-art algorithms aim at generating a difference image and analyzing it by using the threshold, clustering, graph cut and level set methods, obtaining some satisfactory results and making a contribution to an accurate detection. The algorithms are introduced from the elementary to the profound, and their performance is compared theoretically. To demonstrate their effectiveness, two datasets are tested on these algorithms and an objective comparison is made to show the different properties of these algorithms. Finally, several meaningful viewpoints based on the practical problems for the future research of change detection are proposed, throwing light upon some further research directions.

Key words: change detection, synthetic aperture radar (SAR), remote sensing imagery, threshold clustering, graph cut, level set