Wavelet domain denoising by using the universal hidden Markov tree model

Feng Li; Donald Fraser; Xiuping Jia; Andrew Lambert

doi:10.1117/12.794064

13 September 2008 Wavelet domain denoising by using the universal hidden Markov tree model

Feng Li, Donald Fraser, Xiuping Jia, Andrew Lambert

Proceedings Volume 7073, Applications of Digital Image Processing XXXI; 707304 (2008) https://doi.org/10.1117/12.794064
Event: Optical Engineering + Applications, 2008, San Diego, California, United States

Abstract

In this paper, a new image denoising method which is based on the uHMT(universal Hidden Markov Tree) model in the wavelet domain is proposed. The MAP (Maximum a Posteriori) estimate is adopted to deal with the ill-conditioned problem (such as image denoising) in the wavelet domain. The uHMT model in the wavelet domain is applied to construct a prior model for the MAP estimate. By using the optimization method Conjugate Gradient, the closest approximation to the true result is achieved. The results show that images restored by our method are much better and sharper than other methods not only visually but also quantitatively.

Citation Download Citation

Feng Li, Donald Fraser, Xiuping Jia, and Andrew Lambert "Wavelet domain denoising by using the universal hidden Markov tree model", Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 707304 (13 September 2008); https://doi.org/10.1117/12.794064

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