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An Adaptive Gradient-Projection Image Restoration using Spatial Local Constraints and Estimated Noise  

Hong, Min-Cheol (숭실대학교 정보통신전자공학부)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.32, no.10C, 2007 , pp. 975-981 More about this Journal
Abstract
In this paper, we propose a spatially adaptive image restoration algorithm using local and statistics and estimated noise. The ratio of local mean, variance, and maximum values with different window size is used to constrain the solution space, and these parameters are computed at each iteration step using partially restored image. In addition, the additive noise estimated from partially restored image and the local constraints are used to determine a parameter for controlling the degree of local smoothness on the solution. The resulting iterative algorithm exhibits increased convergence speed when compared to the non-adaptive algorithm. In addition, a smooth solution with a controlled degree of smoothness is obtained without a prior knowledge about the noise. Experimental results demonstrate that the proposed algorithm requires the similar iteration number to converge, but there is the improvement of SNR more than 0.2 dB comparing to the previous approach.
Keywords
Gradient-Projection;
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