A new switching median filter is proposed for denoising of gray-scale images, extremely corrupted by salt-and-pepper noise. The proposed model for noise removal is a multiscale detection based adaptive median filter. This method consists of mainly two parts, namely, the thresholding based multiscale noise detection and the filtering. The detection of impulse noise is carried out in two stages. ...

In this paper, a new robust adaptive FIR filter algorithm with variable forgetting factor for time-varying parameters estimation in the presence of impulsive noise is discussed. The proposed algorithm is based on the robust recursive least square and parallel adaptation recursive least square algorithms combination. A scalar parameter controls the switching process between these two algorithms,...

Weighted Median (WM) filters have attracted a growing number of interest in the past few years. They inherent the robustness and edge preserving capability of the classical median filter and resemble linear FIR filters in certain properties. Furthermore, WM filters belong to the broad class of nonlinear filters called stack filters. This enables the use of the tools developed for the latter cla...

A new filtering approach designed to eliminate impulsive noise in color images, while preserving fine image details is presented in this paper. The computational complexity of the new filter is significantly lower than that of the Vector Median Filter. The comparison shows that the new filter outperforms the VMF, as well as other standard procedures used in color image processing, when the impu...

This Paper presents an efficient algorithm for median filtering with a 3x3 filter kernel with only about 9 comparisons per pixel using spatial coherence between neighbouring filter computations. The basic algorithm calculates two medians in one step and reuses sorted slices of three vertical neighbouring pixels. An extension of this algorithm for 2D spatial coherence is also examined, which cal...

This paper proposes a novel adaptive neuro-fuzzy inference system (ANFIS) based impulse detection method for the restoration of images corrupted by impulse noise (IN). After the corrupted pixels detected by proposed detector, the Median filtering is performed for only these pixels. The performance of the proposed neuro-fuzzy detector based median filter (NFDMF) is evaluated on different test im...

An Impulse noise detection & removal with adaptive filtering approach is proposed to restore images corrupted by salt & pepper noise. The proposed algorithm works well for suppressing impulse noise with noise density from 5 to 60% while preserving image details. The difference of current central pixel with median of local neighborhood pixels is used to classify the central pixel as noisy or noi...

Removal of random value impulse noise is essential to help successive process like image segmentation, analysis, pattern recognition etc. To remove uniform/randomvalued impulse noise without compromising the image detail information such as sharp edges, Modified Directional Weighted Median Filter (MDWMF) is proposed. The proposed filter utilizes the second order difference (SOD) along with a th...

Median filter is widely used to remove impulse noise without blurring sharp edges. However, when noise level increased, or with thin edges, median filter may work poorly. This paper proposes a new filter, which will detect edges along four possible directions, and then replace noise corrupted pixel with estimated noise-free edge median value. Simulations show that the proposed multi-stage direc...

We have compared the performance of two different penalty choices for a penalized-likelihood sinogram-restoration strategy we have been developing. One is a quadratic penalty we have employed previously and the other is a new median-based penalty. We compared the approaches to a noniterative adaptive filter that loosely but not explicitly models data statistics. We found that the two approaches...