In this paper we consider the problem of restoration of a image contaminated by a mixture of Gaussian and impulse noises. We propose a new statistic called ROADGI which improves the well-known Rank-Ordered Absolute Differences (ROAD) statistic for detecting points contaminated with the impulse noise in this context. Combining ROADGI statistic with the method of weights optimization we obtain a ...

A new two-step fuzzy filter that adopts a fuzzy logic approach for the enhancement of images corrupted with impulse noise is presented in this paper. The filtering method (entitled as Fuzzy Random Impulse Noise Reduction method (FRINR)) consists of a fuzzy detection mechanism and a fuzzy filtering method to remove (random-valued) impulse noise from corrupted images. Based on the criteria of pea...

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; ...

— 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...

Two main tasks of image processing are noise filtering and image enhancement.During image acquisition and transmission the images are corrupted by noise.these noise will affect the performance of image processing mehods,herefore to improve the performance efficient denoising technique is necessary for image processing methods.In this paper the performance of combined filter in impulse denoising...

-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...