A Novel Approach for Single Image Super Resolution by Sparse Signal Representation

A Novel Approach for Single Image Super Resolution by Sparse Signal Representation

This paper presents a new approach to obtain a high resolution image from a single image low resolution by a technique of sparse representation. Sparse representation is a way of representing a signal sparsely i.e. with fewer non zero elements. In this method we find the sparse representation of the input low resolution image patches and then use the coefficient of this representation to genera...

A Deep Model for Super-resolution Enhancement from a Single Image

This study presents a method to reconstruct a high-resolution image using a deep convolution neural network. We propose a deep model, entitled Deep Block Super Resolution (DBSR), by fusing the output features of a deep convolutional network and a shallow convolutional network. In this way, our model benefits from high frequency and low frequency features extracted from deep and shallow networks...

Sparse Representation Based Single Image Dictionary Construction For Image Super Resolution

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...

Single Image Super-Resolution by Non-Linear Sparse Representation and Support Vector Regression

Sparse representations are widely used tools in image super-resolution (SR) tasks. In the sparsity-based SR methods, linear sparse representations are often used for image description. However, the non-linear data distributions in images might not be well represented by linear sparse models. Moreover, many sparsity-based SR methods require the image patch self-similarity assumption; however, th...