A New Blocking Effect Reduction Method

When a high compression ratio is required, the block discrete cosine transform (BDCT) decoded image suffers from the blocking effect: boundaries between adjacent image blocks visible for low bit rates. A blocking effect reduction algorithm based on DCT transform and Markov random field (MRF) is proposed to reduce blocking artifacts as many as possible, while preserving edge information. In this paper, the characteristic of human visual system (HVS) is sufficiently utilized. A visibility function of blocking artifacts is proposed based on the activity masking and brightness masking properties of HVS. The blocks which visibility of the blocking artifacts is less than the threshold do not need any processing. 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 the proposed algorithm can significantly reduce blocking artifacts while preserving edge and texture information