scholarly journals The topological gradient method for semi-linear problems and application to edge detection and noise removal

2016 ◽  
Vol 10 (1) ◽  
pp. 51-86 ◽  
Author(s):  
Audric Drogoul ◽  
Gilles Aubert
Keyword(s):  
Edge Detection ◽  
Gradient Method ◽  
Noise Removal ◽  
Topological Gradient ◽  
Linear Problems

Non-Subsampled Contourlet Transform-Based Effective Denoising of Medical Images

2019 ◽  
pp. 155-183
Author(s):  
Karthikeyan P. ◽  
Vasuki S. ◽  
Karthik K.
Keyword(s):  
Image Analysis ◽  
Edge Detection ◽  
Image Enhancement ◽  
Image Denoising ◽  
Medical Images ◽  
Noise Removal ◽  
Contourlet Transform ◽  
Nonsubsampled Contourlet Transform ◽  
Shift Invariance ◽  
Image Edges

Noise removal in medical images remains a challenge for the researchers because noise removal introduces artifacts and blurring of the image. Developing medical image denoising algorithm is a difficult operation because a tradeoff between noise reduction and the preservation of actual features of image has to be made in a way that enhances and preserves the diagnostically relevant image content. A special member of the emerging family of multiscale geometric transforms is the contourlet transform which effectively captures the image edges and contours. This overcomes the limitations of the existing method of denoising using wavelet and curvelet. But due to down sampling and up sampling, the contourlet transform is shift-variant. However, shift-invariance is desirable in image analysis applications such as edge detection, contour characterization, and image enhancement. In this chapter, nonsubsampled contourlet transform (shift-invariance transform)-based denoising is presented which more effectively represents edges than contourlet transform.

Impulse noise removal by a nonmonotone adaptive gradient method

2010 ◽  
Vol 90 (10) ◽  
pp. 2891-2897 ◽  
Author(s):  
Gaohang Yu ◽  
Liqun Qi ◽  
Yimin Sun ◽  
Yi Zhou
Keyword(s):  
Gradient Method ◽  
Impulse Noise ◽  
Noise Removal ◽  
Impulse Noise Removal

An edge detection based noise removal algorithm

2014 ◽  
Vol 40 (3) ◽  
pp. 769-784 ◽  
Author(s):  
Ali Ranjbaran ◽  
Anwar Hasni Abu Hassan ◽  
Eng Swee Kheng ◽  
Bahar Ranjbaran
Keyword(s):  
Edge Detection ◽  
Noise Removal

scholarly journals A Novel Algorithm for Impulse Noise Removal and Edge Detection

2012 ◽  
Vol 38 (7) ◽  
pp. 30-34 ◽  
Author(s):  
Akansha Mehrotra ◽  
Krishna Kant Singh ◽  
M. J. Nigam
Keyword(s):  
Edge Detection ◽  
Impulse Noise ◽  
Noise Removal ◽  
Impulse Noise Removal ◽  
Novel Algorithm

A Novel Edge Detection Algorithm of Color Image

2013 ◽  
Vol 446-447 ◽  
pp. 976-980
Author(s):  
De Rui Song ◽  
Dao Yan Xu ◽  
Li Li
Keyword(s):  
Edge Detection ◽  
Impulse Noise ◽  
Color Image ◽  
Peer Group ◽  
Color Space ◽  
Noise Removal ◽  
Detection Algorithm ◽  
Image Edge Detection ◽  
Image Edge ◽  
Image Edges

This paper proposes a novel algorithm of edge detection using LUV color space. Firstly, according to peer group filtering (PGF), a nonlinear algorithm for image smoothing and impulse noise removal in color image is used. Secondly, color image edges in an image are obtained automatically by combining an improved isotropic edge detector and a fast entropy threshold technique. Thirdly, according to color distance between the pixel and its eight neighbor-pixels, color image edges can further be detected. Finally, the experiment demonstrates the outcome of proposed algorithm in color image edge detection.

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