SAR image despeckling based on edge detection and nonsubsampled second generation bandelets  

作　　者：Zhang Wenge~(1,2),Liu Fang~(1,2),Jiao Licheng~(2,3)& Gao Xinbo~(2,3) 1.School of Computer Science and Technology,Xidian Univ.,Xi’an 710071,P.R.China 2.Key Lab.of Intelligent Perception and Image Understanding of Ministry of Education of China,Xi’an 710071,P.R.China 3.Inst,of Intelligent Information Processing,Xidian Univ.,Xi’an 710071,P.R.China 

出　　处：《Journal of Systems Engineering and Electronics》2009年第3期519-526,共8页系统工程与电子技术（英文版）

基　　金：supported by the National Natural Science Foundation of China(60673097;60702062);the National HighTechnology Research and Development Program of China(863 Program)(2008AA01Z125;2007AA12Z136);the National ResearchFoundation for the Doctoral Program of Higher Education of China(20060701007);the Program for Cheung Kong Scholarsand Innovative Research Team in University(IRT 0645).

摘　　要：To preserve the sharp features and details of the synthetic aperture radar （SAR） image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform （NSBT） domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges axe detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least square-Gaussian scale mixture （BLS-GSM）.To preserve the sharp features and details of the synthetic aperture radar （SAR） image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform （NSBT） domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges axe detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least square-Gaussian scale mixture （BLS-GSM）.

关 键 词：computer image processing synthetic aperture radar SPECKLE edge detection nonsubsampled second generation bandelet transform Canny operator threshold shrinkage. 

分 类 号：TN958[电子电信—信号与信息处理]