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Impulse noise

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


Papers
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Journal ArticleDOI
TL;DR: In this article, a summary of recent work in weapon noise signal analysis, current knowledge of hearing damage risk criteria, and auditory performance in impulse noise is presented, with a focus on the effects of combined noise exposures from similar or different weapons and continuous background noise.
Abstract: Noise-induced hearing loss resulting from weapon noise exposure has been studied for decades. A summary of recent work in weapon noise signal analysis, current knowledge of hearing damage risk criteria, and auditory performance in impulse noise is presented. Most of the currently used damage risk criteria are based on data that cannot be replicated or verified. There is a need to address the effects of combined noise exposures, from similar or different weapons and continuous background noise, in future noise exposure regulations. Advancements in hearing protection technology have expanded the options available to soldiers. Individual selection of hearing protection devices that are best suited to the type of exposure, the auditory task requirements, and hearing status of the user could help to facilitate their use. However, hearing protection devices affect auditory performance, which in turn affects situational awareness in the field. This includes communication capability and the localization and identification of threats. Laboratory training using high-fidelity weapon noise recordings has the potential to improve the auditory performance of soldiers in the field, providing a low-cost tool to enhance readiness for combat.

16 citations

Journal Article
TL;DR: The proposed filter is Modified Adaptive Center Weighted Median (MACWM) filter with an adjustable central weight obtained by partitioning the observation vector space by fuzzy clustering part for clustering the observed vector of each pixel into one of M mutually exclusive blocks.
Abstract: In this paper, a new switch median filter is presented for suppression of impulsive noise in image. The proposed filter is Modified Adaptive Center Weighted Median (MACWM) filter with an adjustable central weight obtained by partitioning the observation vector space. Dominant points of the proposed approach are partitioning of observation vector space using clustering method, training procedure using LMS algorithm then freezing weights in each block are applied to test image. The proposed method includes fuzzy clustering part for clustering the observed vector of each pixel into one of M mutually exclusive blocks. In the training phase, Least Mean Square (LMS) algorithm use to train center weight in each block then obtained weights used in testing phase. Final results shows better performance in the impulse noise reduction over standard images relative the median (MED) filter, the switching scheme I (SWM-I) filter, the signal dependent rank order mean (SD-ROM) filter, the tristate median (TSM) filter, the fast peer group filter (FPGF), the fuzzy median (FM) filter, the PFM filter and the adaptive center weighted median (ACWM) filter.

16 citations

Book ChapterDOI
01 Jan 2006
TL;DR: A Java Applet is developed and used to compare all the fuzzy inspired filters for noise reduction with each other and the numerical and visual performance of all these filters are illustrated.
Abstract: The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. In addition to all the classical based filters for noise reduction, many fuzzy inspired filters have been developed during the past years [3–26]. However, it is very difficult to judge the quality of all these different filters. For which noise types are they designed? How do they perform compared to each other? Are there some filters that clearly outperform the others? Do the numerical results correspond with the visual results? In this paper we answer these questions for color images that are corrupted with impulse noise. We also have developed a Java Applet (http://www.fuzzy.ugent.be/Dortmund.html). The Java Applet is used to compare all the mentioned filters with each other. It illustrates the numerical and visual performance of all these filters. Users have the possibility to load and corrupt an image from a predefined list.

16 citations

Journal ArticleDOI
TL;DR: There is not really a frequency specificity of impairments due to styrene, and the fact that the tonotopicity of the Styrene-induced damage depends on the associated noise spectrum complicates the diagnosis of styrene-related hearing loss with a tone-frequency audiometric approach.

16 citations

Journal ArticleDOI
Chao Wang1, Lifeng Sun1, Bo Yang1, Yi-Ming liu1, Shiqiang Yang1 
TL;DR: A novel video enhancement system based on an adaptive spatio-temporal connective noise filter and an adaptive piecewise mapping function, aiming to reduce the mixture of the most two common types of noises—Gaussian and impulse noises in spatial and temporal directions.
Abstract: This paper presents a novel video enhancement system based on an adaptive spatio-temporal connective (ASTC) noise filter and an adaptive piecewise mapping function (APMF). For ill-exposed videos or those with much noise, we first introduce a novel local image statistic to identify impulse noise pixels, and then incorporate it into the classical bilateral filter to form ASTC, aiming to reduce the mixture of the most two common types of noises—Gaussian and impulse noises in spatial and temporal directions. After noise removal, we enhance the video contrast with APMF based on the statistical information of frame segmentation results. The experiment results demonstrate that, for diverse low-quality videos corrupted by mixed noise, underexposure, overexposure, or any mixture of the above, the proposed system can automatically produce satisfactory results.

16 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202371
2022168
2021111
2020175
2019206
2018210