www.pudn.com > SR.rar > README.dat, change:2011-03-07,size:1413b

* Demo Codes For Image Super-resolution via Sparse Representation           
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 jyang29@uiuc.edu 
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 paper. 
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. 
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.