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Image Denoising Method based on Threshold, Wavelet Transform and Genetic Algorithm

초록

영어

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.

목차

Abstract
 1. Introduction
  (1) Mean Filter Principle
  (2) The Median Filter
  (3) Wavelet Transform
 2 Threshold Determination
  2.1 Wavelet Transform Denoising
  2.2 Threshold Correction
  2.3 New Threshold Functions
  2.4 Modified Threshold Denoising Algorithm
  2.5 Genetic Algorithm in Image Processing
 3. Verification
 4. Conclusion
 Acknowledgment
 References

저자정보

  • Yali Liu Shangluo University

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