scispace - formally typeset
Search or ask a question
Topic

Noise reduction

About: Noise reduction is a research topic. Over the lifetime, 25121 publications have been published within this topic receiving 300815 citations. The topic is also known as: denoising & noise removal.


Papers
More filters
Journal ArticleDOI
TL;DR: In this article, the authors investigated the operating conditions for modulation bandwidth enhancement, noise reduction, and stable locking to simultaneously fulfill in a semiconductor laser subject to strong optical injection and showed that the optimum detuning of the injection frequency exists as a tradeoff between bandwidth enhancement and noise reduction.
Abstract: Operating conditions for modulation bandwidth enhancement, noise reduction, and stable locking to be simultaneously fulfilled in a semiconductor laser subject to strong optical injection are investigated. When the strength of the injection signal is fixed, the optimum detuning of the injection frequency exists as a tradeoff between bandwidth enhancement and noise reduction. When the laser is injection-locked at a given value of frequency detuning in the stable locking region, both bandwidth enhancement and noise reduction are improved as the injection parameter is increased over a wide range.

148 citations

Journal ArticleDOI
TL;DR: A simple and effective unsupervised approach based on the combined difference image and k-means clustering is proposed for the synthetic aperture radar (SAR) image change detection task, and local consistency and edge information of the difference image are considered.
Abstract: In this letter, a simple and effective unsupervised approach based on the combined difference image and k-means clustering is proposed for the synthetic aperture radar (SAR) image change detection task. First, we use one of the most popular denoising methods, the probabilistic-patch-based algorithm, for speckle noise reduction of the two multitemporal SAR images, and the subtraction operator and the log ratio operator are applied to generate two kinds of simple change maps. Then, the mean filter and the median filter are used to the two change maps, respectively, where the mean filter focuses on making the change map smooth and the local area consistent, and the median filter is used to preserve the edge information. Second, a simple combination framework which uses the maps obtained by the mean filter and the median filter is proposed to generate a better change map. Finally, the k-means clustering algorithm with k = 2 is used to cluster it into two classes, changed area and unchanged area. Local consistency and edge information of the difference image are considered in this method. Experimental results obtained on four real SAR image data sets confirm the effectiveness of the proposed approach.

148 citations

Journal ArticleDOI
TL;DR: In this paper, an attractor is reconstructed from the data using the time-delay embedding method, which produces a new, slightly altered time series which is more consistent with the dynamics on the corresponding phase-space attractor.
Abstract: A method is described for reducing noise levels in certain experimental time series. An attractor is reconstructed from the data using the time-delay embedding method. The method produces a new, slightly altered time series which is more consistent with the dynamics on the corresponding phase-space attractor. Numerical experiments with the two-dimensional Ikeda laser map and power spectra from weakly turbulent Couette-Taylor flow suggest that the method can reduce noise levels up to a factor of 10.

148 citations

Journal ArticleDOI
TL;DR: The performance evaluation supports the theoretical analysis and demonstrates the tradeoff between speech dereverberation and noise reduction, and shows that maximum noise reduction is achieved when the MVDR beamformer is used for noise reduction only.
Abstract: The minimum variance distortionless response (MVDR) beamformer, also known as Capon's beamformer, is widely studied in the area of speech enhancement. The MVDR beamformer can be used for both speech dereverberation and noise reduction. This paper provides new insights into the MVDR beamformer. Specifically, the local and global behavior of the MVDR beamformer is analyzed and novel forms of the MVDR filter are derived and discussed. In earlier works it was observed that there is a tradeoff between the amount of speech dereverberation and noise reduction when the MVDR beamformer is used. Here, the tradeoff between speech dereverberation and noise reduction is analyzed thoroughly. The local and global behavior, as well as the tradeoff, is analyzed for different noise fields such as, for example, a mixture of coherent and non-coherent noise fields, entirely non-coherent noise fields and diffuse noise fields. It is shown that maximum noise reduction is achieved when the MVDR beamformer is used for noise reduction only. The amount of noise reduction that is sacrificed when complete dereverberation is required depends on the direct-to-reverberation ratio of the acoustic impulse response between the source and the reference microphone. The performance evaluation supports the theoretical analysis and demonstrates the tradeoff between speech dereverberation and noise reduction. When desiring both speech dereverberation and noise reduction, the results also demonstrate that the amount of noise reduction that is sacrificed decreases when the number of microphones increases.

147 citations

Proceedings ArticleDOI
09 Jun 2011
TL;DR: This work develops optimal forward and inverse variance-stabilizing transformations for the Rice distribution in order to approach the problem of magnetic resonance (MR) image filtering by means of standard denoising algorithms designed for homoskedastic observations.
Abstract: We develop optimal forward and inverse variance-stabilizing transformations for the Rice distribution, in order to approach the problem of magnetic resonance (MR) image filtering by means of standard denoising algorithms designed for homoskedastic observations.

147 citations


Network Information
Related Topics (5)
Image processing
229.9K papers, 3.5M citations
90% related
Feature extraction
111.8K papers, 2.1M citations
89% related
Image segmentation
79.6K papers, 1.8M citations
88% related
Convolutional neural network
74.7K papers, 2M citations
88% related
Support vector machine
73.6K papers, 1.7M citations
88% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20231,511
20222,974
20211,123
20201,488
20191,702
20181,631