An improved edge detection algorithm using a modified discrete wavelet transform based on morphological thinner for noisy medical images

Author(s):  
Shilpi Gupta ◽  
Ramesh Kumar Sunkaria
2012 ◽  
Vol 214 ◽  
pp. 375-380 ◽  
Author(s):  
Tie Yun Li

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.


2011 ◽  
Vol 204-210 ◽  
pp. 1386-1389
Author(s):  
Deng Yin Zhang ◽  
Li Xiao ◽  
Shun Rong Bo

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.


2009 ◽  
Author(s):  
Xiaowei Fu ◽  
Mingyue Ding ◽  
Yangguang Sun ◽  
Shaobin Chen

2015 ◽  
Vol 22 (9) ◽  
pp. 50-54 ◽  
Author(s):  
文 涛 WEN Tao ◽  
左东广 ZUO Dong guang ◽  
李站良 LI Zhan liang ◽  
卫宾华 WEI Bin hua

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