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* Demo Codes For Image Super-resolution via Sparse *Representation          
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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]

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Demo_SR.m: demo code for image super-resolution via sparse recovery 

1. 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".

2. 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.

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Demo_Dictionary_Training.m: demo code for training the dictionary

1. If you want to train your own dictionary, replace the training images in subfolder "Data/Training" by yours.

2. You need to inspect the statistics of your sampled patches to prune those smooth patches.