Automatic local thresholding algorithm for SAR image edge detection

2013 ◽  
Author(s):  
Qian-Ru Wei ◽  
Ming-Dong Yuan ◽  
Da-Zheng Feng
Keyword(s):  
Edge Detection ◽  
Sar Image ◽  
Image Edge Detection ◽  
Local Thresholding ◽  
Image Edge ◽  
Thresholding Algorithm

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.

Study of Image Edge Detection Techniques

2012 ◽  
Vol 505 ◽  
pp. 393-396 ◽  
Author(s):  
Wen Zhong Yan ◽  
Da Zhi Deng
Keyword(s):  
Edge Detection ◽  
Operator Technique ◽  
Iterative Thresholding ◽  
Detection Techniques ◽  
Sobel Operator ◽  
Image Edge Detection ◽  
Noise Impact ◽  
Iterative Thresholding Algorithm ◽  
Image Edge ◽  
Thresholding Algorithm

Edges characterize boundaries. Edge detection is a problem of fundamental importance in image processing. The key of edge detection for image is to detect more edge details, reduce the noise impact to the largest degree. In this paper the comparative analysis of various image edge detection techniques is presented. In order to evaluate these techniques, they are used to detect the edge of chromosome image. Firstly, the iterative thresholding algorithm and morphologic erode algorithm together are applied to enhance both the edges of the chromosomes and the contrast of the image. Then, Sobel operator technique, Roberts technique, Prewitt technique and Canny technique are used respectively to detect the edges of the chromosomes in the image.

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