A study of methods of choosing the smoothing parameter in image restoration by regularization
Adam Thompson, John C. W. Brown, Jim Kay, D. Michael Titterington · IEEE Transactions on Pattern Analysis and Machine Intelligence · 1991
The method of regularization is portrayed as providing a compromise between fidelity to the data and smoothness, with the tradeoff being determined by a scalar smoothing parameter. Various ways of choosing this parameter are discussed in the case of quadratic regularization criteria. They are compared algebraically, and their statistical properties are comparatively assessed from the results of all extensive simulation study based on simple images.>