Choice of Wavelet - Thresholds for Denoising image


The KIPS Transactions:PartB , Vol. 8, No. 6, pp. 693-698, Dec. 2001
10.3745/KIPSTB.2001.8.6.693,   PDF Download:

Abstract

Noisy data are often fitted using a smoothing parameter, controlling the importance of two objectives that are opposite to a certain extent. One of these two is smoothness and the other is closeness to the input data. The optimal value of this parameter minimizes the error of the result. This optimum cannot be found exactly, simply because the exact data are unknown. This paper propose the threshold value for noise reduction based on wavelet-thresholding. In the proposed method PSNR results show that the threshold value performs excellently in comparison with conventional methods without knowing the noise variance and volume of signal.


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Cite this article
[IEEE Style]
H. S. Cho and H. Lee, "Choice of Wavelet - Thresholds for Denoising image," The KIPS Transactions:PartB , vol. 8, no. 6, pp. 693-698, 2001. DOI: 10.3745/KIPSTB.2001.8.6.693.

[ACM Style]
Hyun Sug Cho and Hyoung Lee. 2001. Choice of Wavelet - Thresholds for Denoising image. The KIPS Transactions:PartB , 8, 6, (2001), 693-698. DOI: 10.3745/KIPSTB.2001.8.6.693.