Image denoising based on genetic algorithm

Author(s):  
Claudio F. M. Toledo ◽  
Lucas de Oliveira ◽  
Ricardo Dutra da Silva ◽  
Helio Pedrini
2011 ◽  
Vol 186 ◽  
pp. 337-341
Author(s):  
Shuang Ping Zhao ◽  
Xiang Wei Li ◽  
Jing Hong Xing ◽  
Yan Wen Ye

This paper presents a wavelet image denoising method by Threshold optimal based on wavelet transform and genetic algorithm (GA). First, using wavelet transition to a original signal and selecting a wavelet and a level of wavelet decomposition, Then the optimized thresholds of every level of wavelet decomposition will be obtained by genetic algorithms. The high coefficients at every level will be quantized. At last, inverse transition of the coefficients will be processed and we will get the final signals. An optimal image threshold using Genetic Algorithm is proposed. Compared with traditional threshold methods, the proposed method has advantages that it can implement quickly optimal threshold and have good capability and stabilization. The results show that using the proposed method can obtain satisfactory denoising effect.


2016 ◽  
Vol 46 ◽  
pp. 778-791 ◽  
Author(s):  
Jonatas Lopes de Paiva ◽  
Claudio F.M. Toledo ◽  
Helio Pedrini

Author(s):  
Daniel Fajardo-Delgado ◽  
Maria Guadalupe Sanchez ◽  
Jesus Ezequiel Molinar-Solis ◽  
Jose Alberto Fernandez-Zepeda ◽  
Vicente Vidal ◽  
...  

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