Image Restoration: An Edge Detection Based Regularization
A. Lakshmi, Subrata Rakshit · 2011
We present a new inhomogeneous image restoration model with an edge detection based regularization term, for known linear shift invariant blur kernel. Our regularization term penalizes the noise, but not the edges. Our method is well suited for real world images with texture. The proposed algorithm has two major benefits : It is tuned to decouple edges from noise and it is computationally very simple. Our method is validated qualitatively and quantitatively against state of the art restoration methods with extensive experiments.