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<p>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.</p>
picture processing; image restoration; scalar smoothing parameter; quadratic regularization criteria; filtering and prediction theory; picture processing; statistical analysis
J.W. Kay, D.M. Titterington, J.C. Brown, A.M. Thompson, "A Study of Methods of Choosing the Smoothing Parameter in Image Restoration by Regularization", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 13, no. , pp. 326-339, April 1991, doi:10.1109/34.88568
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