Removal of compression artifacts using projections onto convex sets and line process modeling

被引:89
作者
Yang, YY
Galatsanos, NP
机构
[1] Electrical and Computer Engineering Department, Illinois Institute of Technology, Chicago
关键词
compression artifacts; postprocessing; projections onto convex sets;
D O I
10.1109/83.624945
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this Paper,,ve present a new image recovery algorithm to remove,in addition to blocking, ringing artifacts from compressed images and video. This new algorithm is based on the theory of projections onto convex sells (POCS). A new family of directional smoothness constraint sets is defined based on line processes modeling of the image edge structure. The definition of these smoothness, sets also takes into account the fact that the visibility of compression artifacts in an image is spatially varying. To overcome the numerical difficulty in computing the projections onto these sets, a divide-and-conquer (DAC) strategy is introduced. According to this strategy, new smoothness sets are derived such that their projections are easier to compute. The effectiveness of the proposed algorithm is demonstrated through numerical experiments using Motion Picture Expert Group based (MPEG-based) coders-decoders (codecs).
引用
收藏
页码:1345 / 1357
页数:13
相关论文
共 28 条
[1]   IMAGE-RESTORATION BASED ON A SUBJECTIVE CRITERION [J].
ANDERSON, GL ;
NETRAVALI, AN .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1976, 6 (12) :845-853
[3]  
CHOI M, IN PRESS P ICIP 97
[4]   PARALLEL AND DETERMINISTIC ALGORITHMS FROM MRFS - SURFACE RECONSTRUCTION [J].
GEIGER, D ;
GIROSI, F .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1991, 13 (05) :401-412
[5]   STOCHASTIC RELAXATION, GIBBS DISTRIBUTIONS, AND THE BAYESIAN RESTORATION OF IMAGES [J].
GEMAN, S ;
GEMAN, D .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1984, 6 (06) :721-741
[6]  
Gersho A., 1991, VECTOR QUANTIZATION
[7]  
GERSHO S, 1991, IEEE T PATTERN ANAL
[8]  
*ISO IEC, 1992, 11172 ISO IEC DIS
[9]  
*ISO IEC, 1991, 109181 ISO IEC CD
[10]   COMPOUND GAUSS-MARKOV RANDOM-FIELDS FOR IMAGE ESTIMATION [J].
JENG, FC ;
WOODS, JW .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1991, 39 (03) :683-697