SAR Image Edge Detection Using Sparse Representation and LS-SVM

2014 ◽  
Vol 11 (11) ◽  
pp. 3941-3947 ◽  
Author(s):  
Shuaiqi Liu
Keyword(s):  
Edge Detection ◽  
Sparse Representation ◽  
Sar Image ◽  
Image Edge Detection ◽  
Image Edge

SAR image edge detection via sparse representation

2017 ◽  
Vol 22 (8) ◽  
pp. 2507-2515 ◽  
Author(s):  
Xiaole Ma ◽  
Shuaiqi Liu ◽  
Shaohai Hu ◽  
Peng Geng ◽  
Ming Liu ◽  
...  
Keyword(s):  
Edge Detection ◽  
Sparse Representation ◽  
Sar Image ◽  
Image Edge Detection ◽  
Image Edge

SAR image edge detection combining radon transform with RDWT

2007 ◽  
Author(s):  
Xinyan Yang ◽  
Licheng Jiao ◽  
Jiajun Wang
Keyword(s):  
Edge Detection ◽  
Radon Transform ◽  
Sar Image ◽  
Image Edge Detection ◽  
Image Edge

SAR image edge detection based on fuzzy theory and information fusion

2015 ◽  
Author(s):  
Lei Jiang Lei Jiang ◽  
Xianqing Ling Xianqing Ling ◽  
Jian Geng Jian Geng ◽  
Yongsheng Cheng Yongsheng Cheng
Keyword(s):  
Edge Detection ◽  
Information Fusion ◽  
Fuzzy Theory ◽  
Sar Image ◽  
Image Edge Detection ◽  
Image Edge

SAR image edge detection using curvelet transform and Duda operator

2010 ◽  
Vol 46 (2) ◽  
pp. 167 ◽  
Author(s):  
G.Y. Zhou ◽  
Y. Cui ◽  
Y.L. Chen ◽  
J. Yang ◽  
H.F. Rashvand
Keyword(s):  
Edge Detection ◽  
Curvelet Transform ◽  
Sar Image ◽  
Image Edge Detection ◽  
Image Edge

A New Method of Denoising by Reserving Edges for SAR Image

2013 ◽  
Vol 291-294 ◽  
pp. 2859-2862
Author(s):  
Lian Fei Duan ◽  
Chuan Ting Wei ◽  
Jing Wang ◽  
Yuan Wen Dai
Keyword(s):  
Edge Detection ◽  
New Method ◽  
Sar Image ◽  
Detection Experiment ◽  
Denoising Method ◽  
Image Edge Detection ◽  
Image Edge ◽  
Image Blur ◽  
Image Edges

Aimed at the problem of image blur while denoising in SAR image, a new denoising method by reserving edges based on MSP-ROA operator is presented after analyzing the image edge detection. The SAR image edges are well reserved while denoising for combining denoising with the edge detection. Experiment results show that the method is feasible and effective.

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