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Proceedings ArticleDOI

A new class of median based impulse rejecting filters

Tao Chen, +1 more
- Vol. 1, pp 916-919
TLDR
A novel adaptive filter based on the impulse rejecting mechanism, where detected impulses are filtered and noise-free pixels are left unaltered, which consistently performs well in suppressing both types of impulse noise while still employing a simple structure.
Abstract
This paper proposes a novel adaptive filter based on the impulse rejecting mechanism, where detected impulses are filtered and noise-free pixels are left unaltered. Previous impulse detection strategies based on thresholding operations tend to work well for large, fixed-valued impulses but poorly for random-valued impulse noise, or vice versa. The objective of this work is to utilize the center weighted median (CWM) filters with variable center weights to define a more general operator, which forms estimates according to the differences defined between the outputs of CWM filters and the current pixel in consideration. As compared with existing schemes, the proposed filter consistently performs well in suppressing both types of impulse noise while still employing a simple structure. Better performance has been achieved by the new filter in restoring a variety of images corrupted with different noise ratios.

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Citations
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Journal ArticleDOI

Impulsive noise suppression from images with Jarque-Bera test based median filter

TL;DR: In this paper, a novel impulsive noise eliminator filter, entitled Jarque-Bera test based median filter (JM), which shows a high performance at the restoration of images distorted by IN is proposed.
Journal ArticleDOI

Impulsive noise suppression from images with the noise exclusive filter

TL;DR: Simulation results show that the proposed noise exclusive filter achieves a superior performance compared with the other filters mentioned in this paper in terms of noise suppression and detail preservation, particularly when the noise density is very high.
Journal ArticleDOI

Using an adaptive neuro-fuzzy inference system-based interpolant for impulsive noise suppression from highly distorted images

TL;DR: The extensive simulation results show that the proposed filter achieves a superior performance to the other filters mentioned in this paper in the cases of being effective in noise suppression and detail preservation, especially when the noise density is very high.
Book ChapterDOI

Using an exact radial basis function artificial neural network for impulsive noise suppression from highly distorted image databases

TL;DR: The proposed filter, RM, which is based on exact radial basis function artificial neural networks achieves a superior performance to the other filters mentioned in this paper in the cases of being effective in noise suppression and detail preservation, especially when the noise density is very high.
Book ChapterDOI

Impulsive Noise Suppression from Highly Corrupted Images by Using Resilient Neural Networks

TL;DR: Extensive simulation results show that the proposed filter achieves a superior performance to the other filters mentioned in this paper in the cases of being effective in noise suppression and detail preservation, especially when the noise density is very high.
References
More filters
Journal ArticleDOI

Center weighted median filters and their applications to image enhancement

TL;DR: The center weighted median (CWM) filter as discussed by the authors is a weighted median filter that gives more weight only to the central value of each window, which can preserve image details while suppressing additive white and/or impulsive-type noise.
Book

Fundamentals of nonlinear digital filtering

TL;DR: In this article, statistical analysis and optimization of nonlinear filter methods based on order statistics Stack Filters Multistage and Hybrid Filters Discussion Exercises Bibliography Index Index.
Journal ArticleDOI

Detail-preserving median based filters in image processing

TL;DR: A switching scheme for median filtering which is suitable to be a prefilter before some subsequent processing e.g. edge detection or data compression is presented to remove impulse noises in digital images with small signal distortion.
Journal ArticleDOI

Tri-state median filter for image denoising

TL;DR: A novel nonlinear filter, called tri-state median (TSM) filter, is proposed for preserving image details while effectively suppressing impulse noise by balancing the tradeoff between noise reduction and detail preservation.
Journal ArticleDOI

A generalization of median filtering using linear combinations of order statistics

TL;DR: In this paper, the authors consider a class of nonlinear filters whose output is given by a linear combination of the order statistics of the input sequence, and choose the coefficients in the linear combination to minimize the output MSE for several noise distributions.
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