Methods for choosing the regularization parameter and estimating the noise variance in image restoration and their relation

作者：N.P. Galatsanos, Aggelos K. Katsaggelos · 发表于：IEEE Transactions on Image Processing · 年份：1992 · DOI：10.1109/83.148606 · 被引用次数：495 · 研究领域：Advanced Image Fusion Techniques、Image and Signal Denoising Methods、Numerical methods in inverse problems

The application of regularization to ill-conditioned problems necessitates the choice of a regularization parameter which trades fidelity to the data with smoothness of the solution. The value of the regularization parameter depends on the variance of the noise in the data. The problem of choosing the regularization parameter and estimating the noise variance in image restoration is examined. An error analysis based on an objective mean-square-error (MSE) criterion is used to motivate regularization. Two approaches for choosing the regularization parameter and estimating the noise variance are proposed. The proposed and existing methods are compared and their relationship to linear minimum-mean-square-error filtering is examined. Experiments are presented that verify the theoretical results.