Title :
Contextual Hidden Markov Tree Model for the Dual-Tree Complex Wavelet Transform
Author :
Lou, Shuai ; Ding, Zhenliang ; Yuan, Feng ; Li, Jing
Author_Institution :
Sch. of Electr. Eng. & Autom., Harbin Inst., Harbin
Abstract :
Multiresolution models such as the wavelet domain hidden Markov tree (HMT) provide a powerful approach for image modeling and processing because of the persistence properties of wavelet coefficients. In this paper, a new HMT model based on the dual-tree complex wavelet transform is proposed. The model is extended from the contextual hidden Markov tree (CHMT) to the complex wavelet transform, which can mitigate the two problems (shift-variance and lack of the clustering property of wavelet coefficients within a scale) of the conventional wavelet domain HMT model simultaneously. We demonstrate the effectiveness of the model for image denoising. Experiments show that this new model achieves better performance than other related HMT-based image denoising algorithms.
Keywords :
hidden Markov models; image denoising; wavelet transforms; contextual hidden Markov tree model; dual-tree complex wavelet transform; image denoising; image modeling; image processing; multiresolution models; Clustering algorithms; Context modeling; Discrete wavelet transforms; Hidden Markov models; Image denoising; Image restoration; Signal resolution; Wavelet coefficients; Wavelet domain; Wavelet transforms; complex wavelet transform; contextual hidden Markov tree; image denoising;
Conference_Titel :
Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3490-9
DOI :
10.1109/PACIIA.2008.189