Fast Image Restoration for Reducing Block Artifacts Based on Adaptive Constrained Optimization

In this paper we propose a fast adaptive image restoration filter using DCT-based edge-classification for reducing block artifacts in compressed images. In order to efficiently reduce block artifacts, edge direction of each block is classified by using the DCT coefficients, and an adaptive constrained least squares (CLS) filter along the edge direction is used for filtering the corresponding block. The proposed research is based on the observation that degradation due to block artifacts is a nonlinear and many-to-one mapping operator. Then, we propose an approximated version of a constrained optimization technique as a restoration process for removing the nonlinear and space-varying degradation operator. For real-time application, the proposed restoration filter is implemented in the form of a truncated FIR filter, which is suitable for postprocessing the images in real-time video systems such as HDTV or video conferencing systems.