Journal ArticleDOI
Fast detection and impulsive noise removal in color images
Bogdan Smolka,Andrzej Chydzinski +1 more
TLDR
The proposed technique employs the switching scheme based on the impulse detection mechanism using the so-called peer group concept and consistently yields very good results in suppressing both the random and fixed-valued impulsive noise.Abstract:
In this paper, a novel approach to the impulsive noise removal in color images is presented. The proposed technique employs the switching scheme based on the impulse detection mechanism using the so-called peer group concept. Compared to the vector median filter and other commonly used multichannel filters, the proposed technique consistently yields very good results in suppressing both the random and fixed-valued impulsive noise. The main advantage of the proposed noise detection framework is its enormous computational speed, which enables efficient filtering of color images in real-time applications.read more
Citations
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Journal ArticleDOI
Fuzzy Peer Groups for Reducing Mixed Gaussian-Impulse Noise From Color Images
TL;DR: The fuzzy concept is used to design a two-step color image filter cascading a fuzzy rule-based switching impulse noise filter by a fuzzy average filtering over the same fuzzypeer , which leads to computational savings.
Journal ArticleDOI
A new adaptive center weighted median filter for suppressing impulsive noise in images
TL;DR: Experimental results have demonstrated that the proposed filter outperforms many well-accepted median-based filters in terms of both noise suppression and detail preservation and provides excellent robustness at various percentages of impulsive noise.
Journal ArticleDOI
Nonlinear Vector Filtering for Impulsive Noise Removal from Color Images
TL;DR: A comprehensive survey of 48 filters for impulsive noise removal from color images is presented and suggestions are provided on how to choose a filter given certain requirements.
Journal ArticleDOI
A comprehensive survey on impulse and Gaussian denoising filters for digital images
TL;DR: With this extensive review, researchers in image processing will be able to ascertain which of these denoising methods will be best applicable to their research needs and the application domain where such methods are contemplated for implementation.
Journal ArticleDOI
Using Uncorrupted Neighborhoods of the Pixels for Impulsive Noise Suppression With ANFIS
TL;DR: Empirical results indicate that the proposed ABF achieves a better performance than the comparison filters in terms of noise suppression and detail preservation, even when the images are highly corrupted by IN.
References
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Handbook of Image and Video Processing
TL;DR: The Handbook of Image and Video Processing contains a comprehensive and highly accessible presentation of all essential mathematics, techniques, and algorithms for every type of image and video processing used by scientists and engineers.
Journal ArticleDOI
Vector median filters
TL;DR: In this article, two nonlinear algorithms for processing vector-valued signals are introduced, called vector median operations, which are derived from two multidimensional probability density functions using the maximum-likelihood-estimate approach.
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DNA arrays for analysis of gene expression.
TL;DR: The chapter focuses on the application of DNA microarrays to gene expression studies and discusses general principles of whole genome expression monitoring as well as detailing the specific process of making and using spotted DNAmicroarrays.
Book
Color Image Processing and Applications
TL;DR: In this article, the authors present an introductory chapter on colour, followed by four chapters on image processing, or omit them and move directly to the final three chapters that deal with colour image analysis and coding.
Journal ArticleDOI
Digital image smoothing and the sigma filter
TL;DR: The characteristics of this noise smoothing algorithm are analyzed and compared with several other known filtering algorithms by their ability to retain subtle details, preserving edge shapes, sharpening ramp edges, etc, and indicates that the sigma filter is the most computationally efficient filter among those evaluated.