An illumination-independent edge detection and fuzzy enhancement algorithm based on wavelet transform for non-uniform weak illumination images

2008 ◽  
Vol 29 (3) ◽  
pp. 192-199 ◽  
Author(s):  
Wanpeng Cao ◽  
Rensheng Che ◽  
Dong Ye
Keyword(s):  
Wavelet Transform ◽  
Edge Detection ◽  
Fuzzy Enhancement ◽  
Independent Edge ◽  
Enhancement Algorithm

A New Method of Fundus Image Enhancement Based on Rough Set and Wavelet Transform

2013 ◽  
Vol 397-400 ◽  
pp. 2205-2208
Author(s):  
Wen Dong Zhao ◽  
You Dong Zhang ◽  
Chun Xia Jin
Keyword(s):  
Wavelet Transform ◽  
Image Enhancement ◽  
Rough Set ◽  
Fundus Images ◽  
Fundus Image ◽  
Visual Effects ◽  
Multi Scale ◽  
Fuzzy Enhancement ◽  
Enhancement Algorithm ◽  
Number Of Iterations

Fundus images are complex images with more details, and on the basis of the inadequate fuzzy enhancement algorithm proposed by Pal et al, this article propose an improved algorithm of rough set for fundus image enhancement. The fundus image will be multi-scale decomposed by wavelet transform firstly, and then the subgraphs are enhanced by using rough set to improve the visual effects; finally the processed sub-images will be reconstructed and generated a new-enhanced image. Compared with the Pal algorithm, the new algorithm not only overcomes its weaknesses that the threshold is set with a fixed value, but also reduces the number of iterations. Experimental results show that the improved enhancement algorithm has a better effect on the fundus image enhancement, and the various details of fundus images can be shown better.

scholarly journals Edge Enhancement Algorithm Based on the Wavelet Transform for Automatic Edge Detection in SAR Images

2011 ◽  
Vol 49 (1) ◽  
pp. 222-235 ◽  
Author(s):  
Mariví Tello Alonso ◽  
Carlos Lopez-Martinez ◽  
Jordi J. Mallorqui ◽  
Philippe Salembier
Keyword(s):  
Wavelet Transform ◽  
Edge Detection ◽  
Edge Enhancement ◽  
Sar Images ◽  
Enhancement Algorithm

Coal Gangue Image Edge Detection Based on Wavelet Transform

2012 ◽  
Vol 214 ◽  
pp. 375-380 ◽  
Author(s):  
Tie Yun Li
Keyword(s):  
Wavelet Transform ◽  
Edge Detection ◽  
Detection Algorithm ◽  
Coal Gangue ◽  
Edge Detection Algorithm ◽  
Image Edge Detection ◽  
Multi Resolution Analysis ◽  
Resolution Analysis ◽  
Image Edge

An edge detection algorithm is developed for coal gangue images, and the method has two advantages compared with traditional ones. Firstly, multi-resolution analysis of wavelet transform can improve the quality of edge detection. Secondly, the algorithm is faster for real time. Since the threshold directly from the coefficients of wavelet transform, the rate of recognition for coal gangue is highly raised. The experiment results show that the method is an efficient edge detection algorithm for extraction edges from the noised images of coal gangues.

A WT-Based Edge Detection with Adaptive Threshold

2011 ◽  
Vol 204-210 ◽  
pp. 1386-1389
Author(s):  
Deng Yin Zhang ◽  
Li Xiao ◽  
Shun Rong Bo
Keyword(s):  
Wavelet Transform ◽  
Edge Detection ◽  
Threshold Value ◽  
Detection Algorithm ◽  
Adaptive Threshold ◽  
Value Iteration ◽  
Edge Detection Algorithm ◽  
Detection Algorithms ◽  
Image Edge ◽  
Threshold Setting

The existing edge detection algorithms with wavelet transform need to artificially set the threshold value and are lack of flexibility.To salve the limitations, in this paper, we propose a WT(wavelet transform)-based edge detection algorithm with adaptive threshold, which uses threshold value iteration method to achieve adaptive threshold setting. Comparison of experiment results for the CT image shows that the method which improve the clarity and continuity of the image edge can effectively distinguish edge and noise, and get more completely information of the edge. It has good application value in the fields of medical clinical diagnosis and image processing.

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