Sparse Representation for Color Image Super-Resolution with Image Quality Difference Evaluation

Super-Resolution Image Reconstruction with Improved Sparse Representation

In this paper, we present a new approach to reconstruct a high resolution (HR) image from a low resolution (LR) input image based on a two dimensional (2D) sparse method. The new method consists of three phases. Firstly, the nonlinear feature of the input LR image is divided into the linear subspace, and then LR-HR dictionaries are learned to reduce the blurred artifacts of the image. Secondly,...

Sparse Spatio-spectral Representation for Hyperspectral Image Super-resolution

Existing hyperspectral imaging systems produce low spatial resolution images due to hardware constraints. We propose a sparse representation based approach for hyperspectral image super-resolution. The proposed approach first extracts distinct reflectance spectra of the scene from the available hyperspectral image. Then, the signal sparsity, non-negativity and the spatial structure in the scene...

Simultaneous image fusion and super-resolution using sparse representation

1566-2535/$ see front matter 2012 Elsevier B.V. A doi:10.1016/j.inffus.2012.01.008 ⇑ Corresponding author. Tel.: +86 731 88822924. E-mail addresses: [email protected] (H. Yin), sh [email protected] (L. Fang). Given multiple source images of the same scene, image fusion integrates the inherent complementary information into one single image, and thus provides a more complete and accurate de...

Selected Paper : Image Super - Resolution via Sparse Representation Authors :

Multi-morphology image super-resolution via sparse representation

A novel multi-morphology image super-resolution algorithm via sparse representation is proposed in this paper. Firstly, the observed low resolution image is decomposed into a linear combination of morphological components by morphological component analysis. Secondly, for effective representation of different components, each dictionary pair is learned from the low resolution component and comp...