Develop of mean filter for Gaussian image noise removal

Abstract EN

Image can be corrupted during capturing, transmission or storing it.

During this processes images are distorted due to different noises.

There are many methods for reducing noise.

Traditional mean filter considered as a linear filter, that simple, native and appropriates to removing an Additive noise such as Gaussian noise.

Unfortunately, the mean filter suffer from inefficiency of reducing the noise.

This paper proposed a new developed mean filter to speed up and enhance the competence of the traditional mean filter.

The new filter use subset of pixels in the mask to find the new value of the pixel.

The quality of the enhanced images is measured by the statistical quantity measures: Peak Signal-to-Noise Ratio (PSNR) and The Structural Similarity (SSIM) metrics.

A time complexities comparison will be explained between developed and traditional filters