Dynamic data updating algorithm for image superresolution reconstruction

A computationally efficient superresolution image reconstruction algorithm

Superresolution reconstruction produces a high-resolution image from a set of low-resolution images. Previous iterative methods for superresolution had not adequately addressed the computational and numerical issues for this ill-conditioned and typically underdetermined large scale problem. We propose efficient block circulant preconditioners for solving the Tikhonov-regularized superresolution...

A computationally eÆcient superresolution image reconstruction algorithm

Superresolution reconstruction produces a high resolution image from a set of low resolution images. Previous iterative methods for superresolution [9, 11, 16, 25, 28] had not adequately addressed the computational and numerical issues for this ill-conditioned and typically underdetermined large scale problem. We propose eÆcient block circulant preconditioners for solving the Tikhonovregularize...

Image Reconstruction from Incomplete Data

Image Reconstruction from Incomplete Data

Superresolution Image Reconstruction Using Fast Inpainting Algorithms

The main aim of this paper is to employ the total variation (TV) inpainting model to superresolution imaging problems. We focus on the problem of reconstructing a highresolution image from several decimated, blurred and noisy low-resolution versions of the high-resolution image. We propose a general framework for multiple shifted and multiple blurred low-resolution image frames which subsumes s...