In this paper, we present a new approach to single image super-resolution (SR). The basic idea is to learn a dictionary which can capture the high-order ...
ABSTRACT. In this paper, we present a new approach to single image super-resolution (SR). The basic idea is to learn a dictionary.
Jan 22, 2010 · This paper proposes a framework for single-image super-resolution. The underlying idea is to learn a map from input low-resolution images to target high- ...
Missing: KPCA | Show results with:KPCA
Abstract—This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests ...
Missing: KPCA | Show results with:KPCA
A dictionary-based regression model for practical image super-resolution using local self-similar example patches within the image is used, inspired by the ...
Abstract—This paper proposes a framework for single-image super-resolution. The underlying idea is to learn a map from input low-resolution images to target ...
Missing: KPCA | Show results with:KPCA
A list of resources for example-based single image super-resolution, inspired by Awesome-deep-vision and Awesome Computer Vision.
Missing: KPCA | Show results with:KPCA
This paper proposes a framework for single-image super-resolution. The underlying idea is to learn a map from input low-resolution images to target ...
PDF | This paper presents a new approach to single-image superresolution, based upon sparse signal representation. Research on image statistics suggests.
Missing: KPCA | Show results with:KPCA
Feb 22, 2023 · SINGLE IMAGE SUPER RESOLUTION VIA COUPLED SPARSE AND LOW RANK ... regression coefficient. This leads to representative and more accurate ...