Wavelet domain denoising by using the universal hidden Markov tree model
Feng Li, Donald J. Fraser, Xiuping Jia, Andrew J. Lambert · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2008
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.