Image Denoising Based on Multiple Wavelet Representations and Universal Hidden Markov Tree
Wei Zhang, Qingmei Sui, Weihua Liu, Qi Jiang · 2007
Wavelet-domain universal hidden Markov tree (uHMT) simplify the hidden Markov tree (HMT) model to specify it with just only mine parameters(independent of the size of the image and the number of wavelet scales) by exploiting the inherent self-similarity of real-world images, but it become less accurate. Multiple wavelet representations have excellent performance in image denoising. In this paper, combining the multiple wavelet representations with the uHMT and using their advantages in image denoising, we propose a new image denoising algorithm, called M-uHMT. It is simple and effective. Simulation results show that the proposed M-uHMT can achieve the state-of-the-art image denoising performance at the low computational complexity.