An Adaptive Gradient-Projection Image Restoration Using Local Statistics and Estimated Noise Characteristics

In this paper, we propose an adaptive image restoration algorithm, using the spatially local statistics and estimated noise characteristics. The local variance, mean and maximum value are utilized to constrain the solution space. These parameters are computed at each iteration step using partially restored image. A parameter defined by the user determines the degree of local smoothness imposed on the solution adaptively. The resulting iterative algorithm exhibits increased convergence speed when compared with 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 the capability of the proposed algorithm.