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

• Published in: Signal processing. Image communication Vol. 15; no. 10; pp. 869 - 877
• Main Authors: Kim, Tae Keun, Paik, Joon Ki, Won, Chee Sun, Choe, Yoonsik, Jeong, Jechang, Nam, Jae Yeal
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 2000; Elsevier
• Subjects: Applied sciences; Blocking effect; Constrained optimization; Exact sciences and technology; Image processing; Image restoration; Information, signal and communications theory; Signal processing; Telecommunications and information theory; Blocking effect; Image restoration; Constrained optimization; Adaptive algorithm; Image processing; Video signal; Digital image; Experimental study; Modeling; Adaptive method; Image reconstruction; Model matching; Television; Coding; Least squares method; Classification; Finite impulse response filter; Edge detection
• ISSN: 0923-5965; 1879-2677
• DOI: 10.1016/S0923-5965(99)00033-8

In this paper we propose an adaptive image restoration algorithm using block-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 model-fitting criterion, and the constrained least-squares (CLS) filter with corresponding direction is used for restoring the block. The proposed restoration filter 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 filter can be realized in the form of a truncated FIR filter, which is suitable for postprocessing reconstructed images in digital TV, video conferencing systems, etc.