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. ...

This paper presents a new two-stage approach to impulse noise removal for medical images based on wavelet network (WN). The first step is noise detection, in which the so-called gray-level difference and average background difference are considered as the inputs of a WN. Wavelet Network is used as a preprocessing for the second stage. The second step is removing impulse noise with a median filt...

Images are often corrupted by impulse noise due to a noisy sensor or channel transmission errors. The goal of impulse noise removal is to suppress the noise by preserving the integrity of edges and detail information. In this paper, a new filter called Switching Weighted Adaptive Median (SWAM) filter is proposed for effective suppression of impulse noise which is used to incorporate the Recursi...

The paper describes methodology of experimental diagnostics examining the influence of small home appliances in operation resulting in the injection of impulse noise into local communication lines. The most important result of practical experiments is a data bank of disturbing impulses that will serve for defining of impulse noise model. Keywords–impulse noise; communication lines; local loop; ...

In the field of digital signal processing, the function of a filter is to remove unwanted parts of the signal such as random noise that is also undesirable. To remove noise from the speech signal transmission or to extract useful parts of the signal such as the components lying within a certain frequency range. Filters are broadly used in signal processing and communication systems in applicati...

Empirical mode decomposition (EMD) is a powerful algorithm that decomposes signals as a set of intrinsic mode function (IMF) based on the signal complexity. In this study, partial reconstruction of IMF acting as a filter was used for noise reduction in ECG. An improved algorithm, ensemble EMD (EEMD), was used for the first time to improve the noise-filtering performance, based on the mode-mixin...

— Image denoising is a key issue in all image processing researches. Generally, the quality of an image could be corrupted by a lot of noise due to the undesired conditions of image acquisition phase or during the transmission. Many approaches to image restoration are aimed at removing either Gaussian or impulse noise. Nevertheless, it is possible to find them operating on the same image, which...

Digital image processing has important in many areas such as digital telecommunication, remote sensing, robotics, graphic printing, and medical imaging, defense and security applications[1]. During the transmission and acquisition, images are corrupted by the different type of noise. Because of the noise, quality of image is reduced and other features like edge sharpness and pattern recognition...

-Impulse noise detection is a critical issue when removing impulse noise and impulse/gaussian mixed noise. The framework combines Robust Outlyingness Ratio (ROR) detection mechanism and Fuzzy C Means (FCM) clustering algorithm and Nonlocal Means (NLM) filter. ROR for measuring how impulse like each pixel is and then all pixels are divided into four clusters according to the ROR values. The dete...