Impulse noise

About: Impulse noise is a research topic. Over the lifetime, 4816 publications have been published within this topic receiving 63970 citations.

Performance analysis of OFDM systems for broadband power line communications under impulsive noise and multipath effects

Abstract: The impulsive noise and multipath effects are the main reasons to cause bit errors in power line communications. In this paper, the bit error rate (BER) performance of the orthogonal frequency division multiplexing (OFDM) system under the impulsive noise and multipath effects are theoretically analyzed in terms of closed form formulas. Through the analysis, it is shown that OFDM can mitigate the adverse effect of the impulsive noise and only the heavily disturbed impulsive noise will interfere the BER performance of the OFDM system. It is also shown that the adverse effect of multipath is more serious than that of impulsive noise. In this paper, the guard interval is used to improve the BER performance of the OFDM system. As the longer guard interval is inefficient in using the signal power, the optimum guard interval that can achieve the best BER performance is studied.

A fuzzy filter for images corrupted by impulse noise

Abstract: A new operator is presented which adopts a fuzzy logic approach for the enhancement of images corrupted by impulse noise. The proposed operator is based on two-step fuzzy reasoning, and it is able to perform a very strong noise cancellation while preserving image details very well. The new fuzzy filter is favorably compared with other nonlinear operators in the literature.

A fuzzy impulse noise detection and reduction method

Abstract: Removing or reducing impulse noise is a very active research area in image processing. In this paper we describe a new algorithm that is especially developed for reducing all kinds of impulse noise: fuzzy impulse noise detection and reduction method (FIDRM). It can also be applied to images having a mixture of impulse noise and other types of noise. The result is an image quasi without (or with very little) impulse noise so that other filters can be used afterwards. This nonlinear filtering technique contains two separated steps: an impulse noise detection step and a reduction step that preserves edge sharpness. Based on the concept of fuzzy gradient values, our detection method constructs a fuzzy set impulse noise. This fuzzy set is represented by a membership function that will be used by the filtering method, which is a fuzzy averaging of neighboring pixels. Experimental results show that FIDRM provides a significant improvement on other existing filters. FIDRM is not only very fast, but also very effective for reducing little as well as very high impulse noise.

Advanced impulse Detection Based on pixel-wise MAD

Abstract: A new method for impulse noise removal is presented, where a robust estimator of the variance, MAD (median of the absolute deviations from the median), is modified and used to efficiently separate noisy pixels from the image details. The algorithm is free of varying parameters, requires no previous training or optimization, and successfully removes all types of impulse noise. The pixel-wise MAD concept is straightforward, low in complexity, and achieves high filtering performance.

A Detection Statistic for Random-Valued Impulse Noise

Abstract: This paper proposes an image statistic for detecting random-valued impulse noise. By this statistic, we can identify most of the noisy pixels in the corrupted images. Combining it with an edge-preserving regularization, we obtain a powerful two-stage method for denoising random-valued impulse noise, even for noise levels as high as 60%. Simulation results show that our method is significantly better than a number of existing techniques in terms of image restoration and noise detection