Topic
Impulse noise
About: Impulse noise is a research topic. Over the lifetime, 4816 publications have been published within this topic receiving 63970 citations.
Papers published on a yearly basis
Papers
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TL;DR: In this article, the amplitudes of electromagnetic vehicle ignition noise were made in Ottawa at six fixed frequencies in the range from 150 to 500 MHz using a 10 kHz bandwidth, and statistical analyses were performed of both the amplitude and temporal characteristics of the impulsive noise.
Abstract: Temporal sweeps of the amplitudes of electromagnetic vehicle ignition noise were made in Ottawa at six fixed frequencies in the range from 150 to 500 MHz using a 10 kHz bandwidth. Statistical analyses were performed of both the amplitude and temporal characteristics of the impulsive noise. The amplitudes approximately followed a lognormal distribution. The pulse spacings were uniformly distributed between about 5 and 15 ms and the pulse durations were about 150 /spl mu/s long.
36 citations
TL;DR: In this article, the authors proposed a method for real-time high density impulse noise suppression from images by applying an impulse detector to identify the corrupted pixels and then employing an innovative weighted-average filter to restore them.
Abstract: In this letter, we propose a method for real-time high density impulse noise suppression from images. In our method, we first apply an impulse detector to identify the corrupted pixels and then employ an innovative weighted-average filter to restore them. The filter takes the nearest neighboring interpolated image as the initial image and computes the weights according to the relative positions of the corrupted and uncorrupted pixels. Experimental results show that the proposed method outperforms the best existing methods in both PSNR measure and visual quality and is quite suitable for real-time applications.
36 citations
TL;DR: A new spatiotemporal filtering scheme is described for noise reduction in video sequences by minimizing the kurtosis of error instead of mean squared error and showing marked improvement in visual quality and SNRI measures cost.
Abstract: In this paper, a new spatiotemporal filtering scheme is described for noise reduction in video sequences. For this purpose, the scheme processes each group of three consecutive sequence frames in two steps: 1) estimate motion between frames and 2) use motion vectors to get the final denoised current frame. A family of adaptive spatiotemporal L-filters is applied. A recursive implementation of these filters is used and compared with its nonrecursive counterpart. The motion trajectories are obtained recursively by a region-recursive estimation method. Both motion parameters and filter weights are computed by minimizing the kurtosis of error instead of mean squared error. Using the kurtosis in the algorithms adaptation is appropriate in the presence of mixed and impulsive noises. The filter performance is evaluated by considering different types of video sequences. Simulations show marked improvement in visual quality and SNRI measures cost as well as compared to those reported in literature.
36 citations
25 Mar 2012
TL;DR: The computational performance of the proposed algorithm greatly exceeds that of the state of the art algorithms within the TV framework, and its reconstruction quality performance is competitive for high noise levels, for both grayscale and vector-valued images.
Abstract: Several Total Variation (TV) regularization methods have recently been proposed to address denoising under mixed Gaussian and impulse noise While achieving high-quality denoising results, these new methods are based on complicated cost functionals that are difficult to optimize, which negatively affects their computational performance In this paper we propose a simple cost functional consisting of a TV regularization term and l 2 and l 1 data fidelity terms, for Gaussian and impulse noise respectively, with local regularization parameters selected by an impulse noise detector The computational performance of the proposed algorithm greatly exceeds that of the state of the art algorithms within the TV framework, and its reconstruction quality performance is competitive for high noise levels, for both grayscale and vector-valued images
36 citations
TL;DR: A robust Viterbi algorithm to handle short impulsive noises with unknown characteristics by means of joint decoding and detection during the ViterBI search is proposed and an approach to efficiently estimate the number of corruptions is proposed.
Abstract: The Viterbi algorithm has been successfully applied to different pattern recognition and communication tasks. However, if some observations are corrupted by unknown impulsives noise which are not accounted for by the distortion measures, recognition performance can degrade significantly. In this paper, we propose a robust Viterbi algorithm to handle short impulsive noises with unknown characteristics by means of joint decoding and detection during the Viterbi search. To make the algorithm applicable to different noisy conditions with varying amounts of impulsive noise, we further proposed an approach to efficiently estimate the number of corruptions. We demonstrate the effectiveness of the proposed robust algorithms using spoken digit recognition experiments under two different impulsive noise environments. Under random Gaussian replacement noise, the proposed algorithm reduced digit error by more than 65%. Under the GSM network environment in which lost frames are replaced by interpolated neighboring frames, the robust algorithm reduced digit error by 20%. Furthermore, the proposed algorithm does not degrade performance when impulsive noise is not present
36 citations