Results 171 to 178 of about 656,594 (178)

Cognition and Removal of Impulse Noise With Uncertainty

IEEE Transactions on Image Processing, 2012
Uncertainties are the major inherent feature of impulse noise. This fact makes image denoising a difficult task. Understanding the uncertainties can improve the performance of image denoising. This paper presents a novel adaptive detail-preserving filter based on the cloud model (CM) to remove impulse noise. It is called the CM filter.
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Multiplicative Noise Removal via a Learned Dictionary

IEEE Transactions on Image Processing, 2012
Multiplicative noise removal is a challenging image processing problem, and most existing methods are based on the maximum a posteriori formulation and the logarithmic transformation of multiplicative denoising problems into additive denoising problems. Sparse representations of images have shown to be efficient approaches for image recovery. Following
Huang, Yu-Mei, Moisan, Lionel, Ng, Michael, Zeng, Tieyong   +3 more
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Noise removal and contrast enhancement

1998
The objective of noise removal is to detect and remove unwanted noise from a digital image. The difficulty is in determining which features in an image are genuine and which are caused by noise. In general, it is assumed that variations in intensity and colour will be gradual in an image, so points which are significantly different from their ...
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Removal of impulse noise using a FIRE filter

Proceedings of 3rd IEEE International Conference on Image Processing, 2002
FIRE (Fuzzy Inference Ruled by Else-action) operators are a family of nonlinear operators which adopt fuzzy rules to process image data. A new operator, called DS-FIRE filter, is presented in this paper for the enhancement of images corrupted by impulse noise.
RUSSO, FABRIZIO, RAMPONI, GIOVANNI
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A Digital Impulse Noise Removal Filter

Applied Spectroscopy, 1982
Sensitive absorption measurements may be contaminated by the presence of particulates in the sample. Scattering by these particles can generate impulse noise (spikes) on the spectrum. This problem is especially serious in spectroscopy with a focused laser source, since the laser probes a small cross section of the sample.
Kathy J. Dien Hillig, Michael D. Morris
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A Variational Method with a Noise Detector for Impulse Noise Removal

2007
In this paper we propose a combined method for removing impulse noise. In the first phase, we use an efficient detector, called the Statistics of Ordered Difference Detector (SODD) to identify pixels which are likely to be corrupted by impulse noise. The proposed SODD can yield very high noise detection accuracy at high noise density.
Xin Yang, Shoushui Chen
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Models for Multiplicative Noise Removal

2021
Xiangchu Feng, Xiaolong Zhu
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Seismic interference noise removal

SEG Technical Program Expanded Abstracts 2001, 2001
D. Pattberg, N. Gülünay
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