On the POCS-based postprocessing technique to reduce the blocking artifacts in transform coded images

In this paper, we propose a novel postprocessing technique, based on the theory of projections onto convex sets (POCS), to reduce the blocking artifacts in transform-coded images. It is assumed, in our approach, that the original image is highly correlated. Thus, the global frequency characteristics in two adjacent blocks are similar to the local ones in each block. We consider the high-frequency components in the global characteristics of a decoded image, which are not found in the local ones, as the results from the blocking artifact. We employ N-point discrete cosine transform (DCT) to obtain the local characteristics, and 2N-point DCT to obtain the global ones, and then derive the relation between N-point and 2N-point DCT coefficients. A careful comparison of N-point with 2N-point DCT coefficients makes it possible to detect the undesired high-frequency components, mainly caused by the blocking artifact. Then, we propose novel convex sets and their projection operators in the DCT domain. The performances of the proposed and conventional techniques are compared on the still images, decoded by JPEG. The results show that, regardless of the content of the input images, the proposed technique yields significantly better performance than the conventional techniques in terms of objective quality, subjective quality, and convergence behavior.