Single image super resolution in spatial and wavelet domain

TL;DR

This paper presents a novel single image super resolution algorithm that combines spatial and wavelet domain techniques, utilizing iterative back projection and wavelet denoising to enhance image resolution and reduce noise.

Contribution

It introduces a combined spatial and wavelet domain super resolution method with iterative back projection and noise removal, improving image quality.

Findings

Enhanced resolution and sharper edges in reconstructed images

Effective noise reduction through wavelet denoising

Improved reconstruction accuracy with iterative back projection

Abstract

Recently single image super resolution is very important research area to generate high resolution image from given low resolution image. Algorithms of single image resolution are mainly based on wavelet domain and spatial domain. Filters support to model the regularity of natural images is exploited in wavelet domain while edges of images get sharp during up sampling in spatial domain. Here single image super resolution algorithm is presented which based on both spatial and wavelet domain and take the advantage of both. Algorithm is iterative and use back projection to minimize reconstruction error. Wavelet based denoising method is also introduced to remove noise.