Title :
Noise Adaptive Image Restoration: A Minimum Mean Square Error Approach
Author :
Lakshmi, A. ; Rakshit, Subrata
Abstract :
This paper introduces a novel minimum mean square restoration approach with noise adaptive regularization for linear, space invariant known blur. The restoration filter is designed to de-blur the image while minimizing the noise in the image. The adaptive noise reducing characteristic of the filter is proved analytically. It has been substantiated with empirical study that this restoration approach outperforms state of the art restoration approaches. The proposed method has two major advantage: i) It de-noises the image based on the characteristic of the individual image, ii) It has simple, non-iterative implementation.
Keywords :
image denoising; image restoration; mean square error methods; art restoration approaches; image deblurring; image denoising; minimum mean square error approach; noise adaptive image restoration approach; noise adaptive regularization; restoration filter; space invariant known blur; Correlation; Equations; Image color analysis; Image restoration; Kernel; Noise; TV; Correlation; Filter; Noise; Restoration;
Conference_Titel :
Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), 2011 Third National Conference on
Conference_Location :
Hubli, Karnataka
Print_ISBN :
978-1-4577-2102-1
DOI :
10.1109/NCVPRIPG.2011.63