Blocking effect reduction of compressed images using classification-based constrained optimization

In this paper we propose an adaptive image restoration algorithm using block-based edge-classi"cation for reducing block artifacts in compressed images. In order to e$ciently reduce block artifacts, edge direction of each block is classi"ed by using model-"tting criterion, and the constrained least-squares (CLS) "lter with corresponding direction is used for restoring the block. The proposed restoration "lter is derived based on the observation that the quantization operation in a series of coding processes 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 implementation, the proposed restoration "lter can be realized in the form of a truncated FIR "lter, which is suitable for postprocessing reconstructed images in digital TV, video conferencing systems, etc. ( 2000 Elsevier Science B.V. All rights reserved.