A Comparative Analysis of Edge-Preserving Approaches for Image Filtering

Abstract

Noise removal while sustaining the integrity of important details is a pedantic problem in image enhancement and reclamation. The vital stage to improve image quality which is needed for quantitative imaging study is filtering. Edges preserving filtering techniques are used extensively in computer vision to serve denoising efficiently in prominent research areas for enhancing the quality of low level vision images, medical images, industrial images, geological images, and so on. This review paper is presenting the popular edge-preserving approaches for the enhancement of speckle contaminated images and to enhance peak signal-to-noise ratio (PSNR) of images. Various image quality metrics for proving the worth of these approaches are discussed. The main challenges in these filtering approaches are also covered along with how those challenges are inscribed by researchers. This review contributes to research problems to other fellow researchers who are keen to work in this area.