A shrinkage learning approach for single image super-resolution with overcomplete representations

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6312 LNCS, Issue PART 2, 2010, Pages 622-635

  Adler, Amir ^a   Hel Or, Yacov ^b   Elad, Michael ^a  

^a TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

^b INTERDISCIPLINARY CENTER   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; LEAST SQUARES APPROXIMATIONS; OPTICAL RESOLVING POWER; SHRINKAGE;

DE-NOISING TECHNIQUES; HIGH RESOLUTION IMAGE; LEAST-SQUARES OPTIMIZATION; OVER-COMPLETE REPRESENTATIONS; SHRINKAGE COEFFICIENTS; SUM OF SQUARED ERRORS; SUPER RESOLUTION RECONSTRUCTION; WAVELET COEFFICIENTS;

IMAGE RECONSTRUCTION;

EID: 78149346504     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15552-9_45     Document Type: Conference Paper

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