K-SVD based image denoising using OMP

• By Deepak Kala Vasudevan

A DCT dictionary is trained until it is overcomplete using 3 images by using KSVD to train the dictionary with help of Ortogonal Matching Pursuit, to reduce the error in spare representation of images.

trainingDict.m: Code to Train the dictionary denoisingExample.m : Denoising an image which has zero mean Guassian noise in it.

Helper Functions: KSVD.m : K-means SVD OMP.m : Orthogonal Matching Pursuit denoise.m : Denoising a Noisy Image using the dictionary overDCTdict.m " Creating DCT dictionary

Helper Funtions: stackcol.m reconstr.m makepatch.m Rijmat.m makecell.m denoisingExample.m addnoise.m

I refered to the below paper during my implementation: "Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries" by Michael Elad and Michal Aharon