Gamma Correction-Based Automatic Unsupervised Change Detection in SAR Images Via FLICM Model

被引：14
|
作者：
Li, Liangliang [1 ]
Ma, Hongbing [1 ]
Jia, Zhenhong [2 ]
机构：
[1] Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China
[2] Xinjiang Univ, Coll Informat Sci & Engn, Urumqi 830046, Peoples R China
来源：
JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING | 2023年 / 51卷 / 05期
关键词：
Synthetic aperture radar; Change detection; Gamma correction; FLICM; Log-ratio operator; FUSION;
D O I：
10.1007/s12524-023-01674-4
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
In order to improve the accuracy of change detection, a novel synthetic aperture radar (SAR) image change detection method based on Gamma correction and fuzzy local information c-means clustering (FLICM) model is proposed in this paper. Firstly, the original SAR images are filtered by speckle reducing anisotropic diffusion filter; secondly, the difference image (DI) is obtained by log-ratio operator; thirdly, the DI is processed by the Gamma correction operation; finally, the FLICM model is used to get the change detection result. Experimental results on four groups of SAR images demonstrate that the proposed algorithm has a good performance than many competitive approaches in terms of SAR image change detection.
引用
收藏
页码：1077 / 1088
页数：12
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