A novel Hypergraph-regularized Sparse coding-based Super Resolution (HG-ScSR) is proposed. This regularization can not only focus on the illuminance information ...
Based on this point, we present two sparse representation algorithms for image super-resolution, one achieves the further improvement in image quality and the ...
Based on this point, we present two sparse representation algorithms for image super-resolution, one achieves the further improvement in image quality and the ...
This paper presents a color super-resolution reconstruction method combining the L 2 / 3 sparse regularization model with color channel constraints that ...
Missing: Hypergraph- | Show results with:Hypergraph-
TL;DR: This paper presents a new approach to single-image superresolution, based upon sparse signal representation, which generates high-resolution images that ...
This paper proposed a novel image reconstruction algorithm based on spatial autoregression regularization and sparse representation. This reconstruction ...
Based on this point, we present two sparse representation algorithms for image super-resolution, one achieves the further improvement in image quality and the ...
A novel regularized K-SVD dictionary learning based medical image super-resolution algorithm · Combining sparse representation and local rank constraint for ...
Jul 13, 2021 · (2010) and Yang et al. (2008) used sparse representation methods to perform image super-resolution which used the concept of compressed sensing.
Manifold regularized sparse coding shows promising performance for various applications. The key issue that must be considered in the application is how to ...