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An image super-resolution reconstruction algorithm is proposed based on adaptive interpolation norm regularization, which can not only preserve more details near image edges than Tikhonov regularization, but also efficiently alleviate the staircasing of total variation regularization on flat regions. Furthermore, we propose the use of regularization functional instead of a constant regularization...
Two fast image super-resolution reconstruction algorithms are proposed based on multigrid (MG) and Krylov subspace accelerative algorithms. After briefly introduction of image super-resolution reconstruction model, MG and Krylov subspace accelerative algorithms, two accelerative MG algorithm named MG-CG and MG-GMRES are proposed to solve the sparse symmetric positive definite and non-symmetric linear...
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