Analysis of wavelet image denoising model in Besov spaces

Qibin Fan; Minkai Jiang; Wenping Xiao

doi:10.1117/12.752714

15 November 2007 Analysis of wavelet image denoising model in Besov spaces

Qibin Fan, Minkai Jiang, Wenping Xiao

Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67862P (2007) https://doi.org/10.1117/12.752714
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

In this paper, we discuss the image denoising model which DeVore et al. had established, in which both distance and smoothness can be measured by the objective function, and analysis the model for wavelet image denoising in the Besov spaces with p = q. In addition, we give the exact thresholds for the model, and prove that for 0 < p <1 the effect of noise removal using our methods is in between hard wavelet shrinkage and soft wavelet shrinkage. For the case 0 < p < 1 and 1 ≤ p ≤ ∞, which refers to the problems on the convergence of the iteration of the equations and on the complexity of computation, we give the simplified algorithms. Comparing the threshold given by this paper with Lorenz threshold, we conclude that the former is more meticulous than the latter for the model.

Citation Download Citation

Qibin Fan, Minkai Jiang, and Wenping Xiao "Analysis of wavelet image denoising model in Besov spaces", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67862P (15 November 2007); https://doi.org/10.1117/12.752714

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