A New Deblocking Algorithm Based on Wavelet Transform and MRF for DCT-Coded Images

A major problem for the block-based discrete cosine transform (BDCT) techniques is that the decoded images, especially at very low bit rates, exhibit highly noticeable blocking artifacts near the block boundaries. In this paper, a new deblocking algorithm based on wavelet transform and Markov random field (MRF) is proposed. The blocking-artifacts image is firstly processed with a simple and effective wavelet-based deblocking algorithm using the two-scale wavelet scheme. Adaptive operators for different subbands can be computed to suppress blocking effects below the visual scope. It can make the image smoother, which provides advantage for the following MRF-based deblocking method. The proper threshold value for Huber function plays an important role in MRF method. The linear regression is used to adaptively estimate the threshold value. Experimental results show that the new algorithm has low computational cost and achieves improved image quality in both subjective and objective measurement