变更检测
计算机科学
像素
合成孔径雷达
旋光法
人工智能
聚类分析
噪音(视频)
遥感
雷达成像
计算机视觉
目标检测
模式识别(心理学)
雷达
图像(数学)
地质学
物理
光学
散射
电信
作者
Xiuting Zhang,Junjun Yin,Jian Yang,Xianyu Guo
标识
DOI:10.1109/igarss46834.2022.9883475
摘要
Change detection is an important topic for the use of polarimetric synthetic aperture radar (PolSAR) images. In this study, we investigate the change detection method based on regions. First we segment PolSAR images with improved simple linear iterative clustering (SLIC), then take the averaged coherency matrix as the following change detection unit. The performances of three classical test statistics based on regions and pixels are compared, respectively. Three data sets collected over Langqi Island, Fuzhou, China, by RADARSAT-2 are used for evaluation. Experiments show the region-based method can stably improve the performance of change detection and reduce the false alarms than those of the pixel-based method. Further, the optimization of polarimetric contrast enhancement (OPCE) test statistic is not easily affected by spackle noise and provides stable detection results.
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