Wavelet-Based Single Image Super-Resolution With An Overall Enhancement Procedure

Abstract

Single image super resolution is vital with a specific end goal to make high resolution picture from given low-resolution. K-SVD/OMP is the method in which there will be sparse representation process in which we obtain lower computational complexity. This method extracts diverse kinds of features in low-resolution image and high-resolution images to create the mapping relation. A single low resolution (LR) is degraded into different sub bands using operators DWT.The initiation of DWT has given a major stimulus to many techniques based on achieving super resolution starting with a single low-resolutionimage. The higher recurrence sub-bandsbesides the inadequate added LR picture are consolidated to give a high determination (HR) picture utilizing opposite discrete wavelet change (IDWT). We proposed a method local Lipschitz regularity constraint for enhancement and structure-keeping constraint to percept the optimization problem in SR. Here we will use same kind of feature for mapping relation. It is reviewed that the higher PSNR is obtained for the proposed technique than the existing methods.