Image restoration by matching gradient distributions

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 34, Issue 4, 2012, Pages 683-694

  Cho, Taeg Sang ^a   Zitnick, Charles L ^b   Joshi, Neel ^b   Kang, Sing Bing ^b   Szeliski, Richard ^b   Freeman, William T ^c  

^a LLP   (United States)

^b MICROSOFT RESEARCH   (United States)

^c MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

image deblurring; image denoising; image prior; Nonblind deconvolution

Indexed keywords

DECONVOLUTION METHOD; DEGRADED IMAGES; GLOBAL CONSTRAINTS; GRADIENT DISTRIBUTIONS; GRADIENT IMAGES; IMAGE DEBLURRING; IMAGE DENOISING; IMAGE PRIOR; INPUT IMAGE; MAP ESTIMATOR; MID-FREQUENCY; NATURAL IMAGES; NOISY IMAGE; PIECEWISE SMOOTH; POSTERIOR PROBABILITY; RECONSTRUCTED IMAGE; TEXTURE SEGMENTS; USER STUDY; VISUAL REALISM;

ALGORITHMS; ESTIMATION; IMAGE ENHANCEMENT; IMAGE MATCHING; IMAGE RECONSTRUCTION; IMAGE SEGMENTATION; PROBABILITY DISTRIBUTIONS; RESTORATION; TEXTURES;

IMAGE TEXTURE;

ALGORITHM; ARTICLE; HUMAN; IMAGE ENHANCEMENT; IMAGE PROCESSING; METHODOLOGY; PHYSIOLOGY; VISION;

ALGORITHMS; HUMANS; IMAGE ENHANCEMENT; IMAGE PROCESSING, COMPUTER-ASSISTED; VISION, OCULAR;

EID: 84857432558     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2011.166     Document Type: Article

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