Image Super-Resolution Reconstruction Based on Improved K-SVD Dictionary-Learning

doi:10.3969/j.issn.0372-2112.2013.05.026

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ACTA ELECTRONICA SINICA ›› 2013, Vol. 41 ›› Issue (5) : 997-1000. DOI: 10.3969/j.issn.0372-2112.2013.05.026

Image Super-Resolution Reconstruction Based on Improved K-SVD Dictionary-Learning

SHI Jun, WANG Xiao-hua

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Abstract

An improved super-resolution image reconstruction algorithm based on dictionary-learning is studied in order to solve the problem that the dictionary training process is time-consuming in the existing algorithms.The K-SVD dictionary algorithm is combined with the idea that the high and low resolution dictionaries can be co-generated.Then the high and low resolution dictionaries generated are used to the super-resolution reconstruction algorithm via sparse representation.Experiment results show that the algorithm can not only reduce the time of the dictionary training effectively,and also improve the quality of the reconstruction of high-resolution images.

Key words

super-resolution / K-SVD / dictionary-learning / joint dictionary training

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SHI Jun, WANG Xiao-hua. Image Super-Resolution Reconstruction Based on Improved K-SVD Dictionary-Learning[J]. Acta Electronica Sinica, 2013, 41(5): 997-1000. https://doi.org/10.3969/j.issn.0372-2112.2013.05.026

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