Image super-resolution reconstruction based on sparse representation and residual compensation |
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| Authors: | SHI Jun and WANG Xiao-hua |
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| Affiliation: | School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China |
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| Abstract: | A super-resolution reconstruction algorithm is proposed. The algorithm is based on the idea of the sparse representation of signals, by using the fact that the sparsest representation of a signal is unique as the constraint of the patched-based reconstruction, and compensating residual errors of the reconstruction results both locally and globally to solve the distortion problem in patch-based reconstruction algorithms. Three reconstruction algorithms are compared. The results show that the images reconstructed with the new algorithm have the best quality. |
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| Keywords: | super-resolution reconstruction sparse representation image patch residual compensation |
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