Image Variational Decomposition Based on Modified Wavelet Threshold

Jiang Dong-huan; Song Guo-xiang

doi:10.3724/SP.J.1146.2005.01347

Volume 29 Issue 5

Jan. 2011

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Jiang Dong-huan, Song Guo-xiang. Image Variational Decomposition Based on Modified Wavelet Threshold[J]. Journal of Electronics & Information Technology, 2007, 29(5): 1035-1037. doi: 10.3724/SP.J.1146.2005.01347

Citation:

Jiang Dong-huan, Song Guo-xiang. Image Variational Decomposition Based on Modified Wavelet Threshold[J]. Journal of Electronics & Information Technology, 2007, 29(5): 1035-1037. doi: 10.3724/SP.J.1146.2005.01347

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Image Variational Decomposition Based on Modified Wavelet Threshold

doi: 10.3724/SP.J.1146.2005.01347

Received Date: 2005-10-24
Rev Recd Date: 2006-04-10
Publish Date: 2007-05-19

Abstract

Abstract

The relation of variational image decomposition and wavelet soft threshold was discovered recently by Daubechies and Teschke. A major issue is that thresholded coefficients entail oversmoothing of edges, coefficients set to zero yield Gibbs oscillations in the vicinity of edges, while coefficients remain corrupted generate artifacts. To overcome this problem, piecewise n-degree polynomial threshold and exponential threshold are used to decompose images in this paper, both of which have higher regularity. The near-minimizer of the variational function of image decomposition is obtained. Here, n may be chosen as any positive number and the bigger the degree n is, the better the approximation quality is. Thus, the connection of image variational decomposition and the modified wavelet threshold are obtained. Experimental results demonstrate the effectiveness of the model.

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References

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