Nov 12, 2018 · Abstract: It is well known that the super-resolution reconstruction method based on sparse representation has a superior research value.
Jan 1, 2018 · It is well known that the super-resolution reconstruction method based on sparse representation has a superior research value.
Abstract—This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests ...
Missing: Self- Conformal
Using these similarity patches with the same scale equate to using multiple LR images; different scales patches provide correspondence between different ...
We propose a novel HS image super-resolution method via a self-similarity constrained sparse representation. ... Gong, “ Nonlinear learning using local coordinate ...
Experimental results show that the proposed method outperforms several conventional SR algorithms based on self-similarity and is applied to the new ...
Oct 22, 2024 · This paper presents a new approach to single-image superresolution, based upon sparse signal representation.
... image super-resolution method via a self-similarity constrained sparse representation. We explore the similar patch structures across the whole image and ...
This paper proposes a non-local balanced low rank matrix restoration model (NB-LRM) to improve the performance of SR which will overcome the drawbacks of ...
Many image processing and computer vision tasks can be considered as a cross-style image synthesis problem, such as image super-resolution. [12, 15, 29, 21], ...