As a spotlighted nonlocal image representation model, group sparse representation (GSR) has demonstrated a great potential in diverse image restoration tasks. Most of the existing …
Recent works on structural sparse representation (SSR), which exploit image nonlocal self- similarity (NSS) prior by grouping similar patches for processing, have demonstrated …
J Zhang, D Zhao, W Gao - IEEE transactions on image …, 2014 - ieeexplore.ieee.org
Traditional patch-based sparse representation modeling of natural images usually suffer from two problems. First, it has to solve a large-scale optimization problem with high …
Image nonlocal self-similarity (NSS) property has been widely exploited via various sparsity models such as joint sparsity (JS) and group sparse coding (GSC). However, the existing …
Group sparse representation (GSR) has made great strides in image restoration producing superior performance, realized through employing a powerful mechanism to integrate the …
Sparse representation models code an image patch as a linear combination of a few atoms chosen out from an over-complete dictionary, and they have shown promising results in …
Sparse representation has achieved great success in various image processing and computer vision tasks. For image processing, typical patch-based sparse representation …
W Dong, G Shi, X Li - IEEE transactions on image processing, 2012 - ieeexplore.ieee.org
Simultaneous sparse coding (SSC) or nonlocal image representation has shown great potential in various low-level vision tasks, leading to several state-of-the-art image …
A nonlocal kernel regression (NL-KR) model is presented in this paper for various image and video restoration tasks. The proposed method exploits both the nonlocal self-similarity …