Image super resolution via spare representation of multi-class sequential and joint dictionaries
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Jan 9, 2018
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Feb 5, 2015
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Feb 5, 2015
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Abstract
A method of developing an image training library includes receiving, at a processor, a set of high resolution image samples at a first resolution, generating a set of low resolution image samples having a second resolution from the set of high resolution images, wherein the second resolution is lower than the first resolution, clustering the low resolution image samples using features in the low resolution images, generating a low resolution dictionary for each cluster, generating sparse coefficients for each sample, and using the sparse coefficients to generate a high resolution dictionary for each cluster.
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