Varying Weight Trimmed Mean Filter for the Restoration of Impulse Noise Corrupted Images

Abstract

A weight function is introduced to the generalized version of the alpha-trimmed mean filter for the removal of impulse noise from corrupted images. Iterative implementation of the new filter-based switching scheme is proposed as an impulse detector to preserve the noisefree pixels.Numerical simulations show that the proposed filter is quite robust and efficient, and its performance compares favorably with many other wellknown nonlinear filtering algorithms.

Polarity Classification of Arabic Sentiments

“…There are many filtering techniques that used to avoid the possible noise and to restore images to their original status. The following two paragraphs show two well-known filtering techniques (Average filter and Gaussian filter) (Magid, Soldea, & Rivlin, 2007), (Zhang & Kouri, 2005). a. Gaussian Filtering: Gaussian Filtering is considered as type of linear filter, use in blurring of frequency domain to give no overshoot to a step function input while minimizing the rise and fall time, which decrease the group delay (Magid, Soldea, & Rivlin, 2007).…”

“…Average Filtering: This filter removes the noise from an image by computing the average of the neighbourhood pixel values. It is considered as type of nonlinear filter (Zhang & Kouri, 2005).…”