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An Adaptive Algorithm for Image Denoising Based on Wavelet Transform

In: 2012 International Conference on Information Technology and Management Science(ICITMS 2012) Proceedings

Author

Listed:
  • Guo Peng

    (Sichuan University of Science & Engineering)

  • Yang Ping-xian

    (Sichuan University of Science & Engineering)

  • Wang Wei

    (Sichuan University of Science & Engineering)

Abstract

In view of the traditional wavelet de-noising edge is easily destroyed, which causes the useful detail information of image drop-out problem, this article proposed one kind of algorithm that based on the wavelet transform image auto-adapted de-noising. Firstly, this algorithm carries on the piecemeal match to the image, constructs each similar block the data set; Secondly, it carries on the wavelet transform to it, and takes the noise variance iteration as the foundation; Finally, it makes auto-adapted de-noising processing separately with the soft and hard threshold function to the high or low frequency coefficient. The experimental result shows that after the improvement method applies in the image de-noising, can retain more detail information well, enhance the image peak signal-to-noise ratio (PSNR) and the visual effect has improved.

Suggested Citation

  • Guo Peng & Yang Ping-xian & Wang Wei, 2013. "An Adaptive Algorithm for Image Denoising Based on Wavelet Transform," Springer Books, in: Bing Xu (ed.), 2012 International Conference on Information Technology and Management Science(ICITMS 2012) Proceedings, edition 127, pages 575-587, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-34910-2_67
    DOI: 10.1007/978-3-642-34910-2_67
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