Efficient Deblocking With Coefficient Regularization, Shape-Adaptive Filtering, and Quantization Constraint

We propose an effective deblocking scheme with extremely low computational complexity. The algorithm involves three parts: local ac coefficient regularization (ACR) of shifted blocks in the discrete cosine transform (DCT) domain, block-wise shape adaptive filtering (BSAF) in the spatial domain, and quantization constraint (QC) in the DCT domain. The DCT domain ACR suppresses the grid noise (blockiness) in monotone areas. The spatial-domain BSAF alleviates the staircase noise along the edge, and the ringing near the edge and the corner outliers. The narrow quantization constraint set is imposed to prevent possible oversmoothing and improve PSNR performance. Extensive simulation results and comparative studies are provided to justify the effectiveness and efficiency of the proposed deblocking algorithm.

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