Image De-noising : comparative study

Abstract EN

The need for efficient image restoration methods has grown with the massive production of digital images and movies of all kinds have often been taken in poor conditions.

No matter how good cameras are, an image improvement is always desirable to extend their range of action.

The search for efficient image de-noising methods still is a valid challenge, at the crossing of functional analysis and statistics.

In spite of the sophistication of the recently proposed methods, most algorithms have not yet attained a desirable level of applicability.

The main focus of this paper is to analyses, examines and compares various filters and de-noising methods such as morphology de-noising, singular value decomposition (SVD) de-noising, median and Gaussian filters, in addition to hybrid methods which combine two method.

The aim of this paper is to embark on the study of four types of noises such as Gaussian, Salt and Pepper, Poisson, and Speckle noise.

The resulted images after de-noising are evaluated visually and by using some performance evaluation methods such as PSNR.