Image denoising using multiple wavelet representations and local contextual hidden Markov model
Wei Zhang, Ke-tai Wei, Ximei Liu · 2007
Wavelet-domain local contextual hidden Markov model (LCHMM) can exploit both the local statistics and the intrascale dependencies of wavelet coefficients at a low computational complexity. Multiple wavelet representations have excellent performance in image denoising. In this paper, combining the multiple wavelet representations with the LCHMM and using their advantages in image denoising, we propose a new image denoising algorithm, called M-LCHMM. It is simple and effective. Simulation results show that the proposed M-LCHMM can achieve the state-of-the-art image denoising performance at the low computational complexity.