sparseCodingSuperResolution
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- Demo Codes For Image Super-resolution via Sparse *Representation
Reference
J. Yang et al. Image super-resolution as sparse representation of raw image patches. CVPR 2008.
J. Yang et al. Image super-resolution via sparse representation. IEEE Transactions on Image Processing, Vol 19, Issue 11, pp2861-2873, 2010
For any problems, send email to [email protected]
================================================================ Demo_SR.m: demo code for image super-resolution via sparse recovery
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The demo code is for upscaling factor of 2. For larger magnification factors, run the function "ScSR.m" multiple times. Note the code is a little different from what presented in the TIP10 paper. Please find the previous codes and results in folder "Previous".
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Two pre-trained dictionaries are provided in directory "Dictionary". The dictionaries are for zoom factor of 2. You can train your own dictionary based on function "Demo_Dictionary_Training.m" talked below.
================================================================ Demo_Dictionary_Training.m: demo code for training the dictionary
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If you want to train your own dictionary, replace the training images in subfolder "Data/Training" by yours.
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You need to inspect the statistics of your sampled patches to prune those smooth patches.
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