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  • 标题:Image Denoising Method based on Threshold, Wavelet Transform and Genetic Algorithm
  • 本地全文:下载
  • 作者:Yali Liu
  • 期刊名称:International Journal of Signal Processing, Image Processing and Pattern Recognition
  • 印刷版ISSN:2005-4254
  • 出版年度:2015
  • 卷号:8
  • 期号:2
  • 页码:29-40
  • DOI:10.14257/ijsip.2015.8.2.04
  • 出版社:SERSC
  • 摘要:In the process of image acquisition and transmission, noise is always contained inevitably. So it is necessary to image denoising processing to improve the quality of image. Generally speaking, each algorithm has some filtering and threshold parameters. Taking variety kinds of images into account, it is a key problem of how to set these parameters in denoising algorithms under different conditions to achieve better performance. There are many algorithms for the determination of the parameters, and each of them has its application field. Because the wavelet transform has good performance, therefore, it has been widely applied as a kind of signal and image processing tools. In this paper, wavelet transform is used in the image denoising, and the genetic algorithm is used to estimate the denoising results. Experimental results show the validity of the new algorithm
  • 关键词:image denoising; threshold; wavelet transform; genetic algorithm
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