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\( \chi^2\) test for total variation regularization parameter selection. (English) Zbl 1448.65028
The author designs a \(\chi^2\) test for TV regularization parameter selection assuming the blurring matrix is full rank. They derive an approach based on the regularized residual, which does not require training data. Numerical experiments are also presented for three different noisy images.
65F22 Ill-posedness and regularization problems in numerical linear algebra
62J07 Ridge regression; shrinkage estimators (Lasso)
94A08 Image processing (compression, reconstruction, etc.) in information and communication theory
68U10 Computing methodologies for image processing
65D18 Numerical aspects of computer graphics, image analysis, and computational geometry
Full Text: DOI
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