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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: A novel subspace-based nonlocal low-rank and sparse factorization (SNLRSF) method is proposed to remove the mixture of several types of noise in HSI and outperforms the related state-of-the-art methods in terms of visual quality and quantitative evaluation.
Abstract: Hyperspectral images (HSIs) are unavoidably contaminated by different types of noise during data acquisition and transmission, e.g., Gaussian noise, impulse noise, stripes, and deadlines. A variety of mixed noise reduction approaches are developed for HSI, in which the subspace-based methods have achieved comparable performance. In this paper, a novel subspace-based nonlocal low-rank and sparse factorization (SNLRSF) method is proposed to remove the mixture of several types of noise. The SNLRSF method explores spectral low rank based on the fact that spectral signatures of pixels lie in a low-dimensional subspace and employs the nonlocal low-rank factorization to take the spatial nonlocal self-similarity into consideration. At the same time, the successive singular value decomposition (SVD) low-rank factorization algorithm is used to estimate three-dimensional (3-D) tensor generated by nonlocal similar 3-D patches. Moreover, the well-known augmented Lagrangian method is adopted to solve final denoising model efficiently. The experimental results over simulated and real datasets demonstrate that the proposed approach outperforms the related state-of-the-art methods in terms of visual quality and quantitative evaluation.

56 citations

Journal ArticleDOI
TL;DR: The proposed image denoising framework mainly consists of an impulse noise detector (IND), an edge connection precedure and an adaptive bilateral filter (ABF), which switches between Gaussian and impulse noise depending on the impulse noise detection results.

56 citations

Proceedings ArticleDOI
27 Jun 2004
TL;DR: An adaptive fuzzy switching filter is presented that adopts a fuzzy logic approach for the enhancement of images corrupted by impulse noise that impressively outperforms other techniques in terms of noise suppression and detail preservation.
Abstract: An adaptive fuzzy switching filter is presented that adopts a fuzzy logic approach for the enhancement of images corrupted by impulse noise. In order to achieve optimal detail preservation, we develop the maximum-minimum exclusive median method to estimate the current pixel. Simulation results indicate that the proposed filter impressively outperforms other techniques in terms of noise suppression and detail preservation across a wide range of impulse noise corruption, ranging from 1% to 90%.

56 citations

Proceedings ArticleDOI
12 May 2008
TL;DR: This paper model impulsive noise using Middleton class A and symmetric alpha stable (SaS) models and shows a potential improvement in detection of 25 dB at a bit error rate of 10-5 when using a Bayesian detector instead of a standard correlation receiver.
Abstract: In laptop and desktop computers, clocks and busses generate significant radio frequency interference (RFI) for the embedded wireless data transceivers. RFI is impulsive in nature. When detecting a signal in additive impulsive noise, Spaulding and Middleton showed a potential improvement in detection of 25 dB at a bit error rate of 10-5 when using a Bayesian detector instead of a standard correlation receiver. In this paper, we model impulsive noise using Middleton class A and symmetric alpha stable (SaS) models. The contributions of this paper are to evaluate (1) the performance vs. complexity of parameter estimation algorithms, (2) the closeness of fit of parameter estimation algorithms to measured RFI data from the computer platform, (3) the communication performance vs. computational complexity tradeoffs for the correlation receiver, Wiener filter, and Bayesian detector, and (4) the performance of myriad filtering in combating RFI interference modeled as SaS interference.

56 citations

Journal ArticleDOI
TL;DR: The audiometric and histological findings agree in showing that the superimposed combination of two noise exposures, shown to be safe for the chinchilla, produces traumatic effects that more than exceed the additive effects of either component.
Abstract: Continuous and impulse noises were combined to model more realistic noise environments. Monaural chinchillas were exposed to one of the following conditions: (a) 50 impulses with 40‐μsec. A duration at 158‐dB‐SPL peak pressure, 1/min; (b) 95‐dB‐SPL continuous noise at 2–4 kHz for one hour; (c) superimposed combination of the continuous and impulse noise; (d) 50 impulses with a 40‐μsec. A duration at 175‐dB‐SPL peak pressure, 1/min; (e) interrupted combination of the continuous and impulse noise with the continuous noise off for 2 sec during the impulse delivery. Quiet thresholds were measured before and after exposure using the auditory evoked response and histology was obtained using the surface preparation technique. The audiometric and histological findings agree in showing that the superimposed combination of two noise exposures, shown to be safe for the chinchilla, produces traumatic effects that more than exceed the additive effects of either component. The existing damage risk criteria do not provide guidelines for such noise combinations.

55 citations


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