An Image Recovery Method Based on Adaptive Redundant #br#
Dictionaries for Compressed Sensing
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An Image Recovery Method Based on Adaptive Redundant #br#
Dictionaries for Compressed Sensing
Acta Scientiarum Naturalium Universitatis SunYatseniVol. 51, Issue 6, (2012)
作者机构:
佛山科学技术学院电子与信息工程学院,广东,佛山,528000
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Published:2012,
Published Online:25 November 2012,
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JIANG Yewen, YU Xinmei. An Image Recovery Method Based on Adaptive Redundant #br#
Dictionaries for Compressed Sensing. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 51(6).(2012)
DOI:
JIANG Yewen, YU Xinmei. An Image Recovery Method Based on Adaptive Redundant #br#
Dictionaries for Compressed Sensing. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 51(6).(2012)DOI:
An Image Recovery Method Based on Adaptive Redundant #br#
Dictionaries for Compressed Sensing
Signal sparse decomposition of redundant dictionaries is a new theory for signal representation. The theory can adaptively provide a flexible method for signal sparsity extension via using overcomplete redundant function instead of conventional orthonormal-basis function. Based on DCT redundant dictionary and Dirac dictionary
a novel adaptive redundant dictionary is presented by composed Dirac and DCT base.Combining image partition and iterative hard threshold (IHT) algorithm
experiment results show that the adaptive redundant dictionary has higher signal recovery ratio.