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Author

Bogdan Smolka

Other affiliations: University of Toronto
Bio: Bogdan Smolka is an academic researcher from Silesian University of Technology. The author has contributed to research in topics: Median filter & Noise reduction. The author has an hindex of 24, co-authored 224 publications receiving 3040 citations. Previous affiliations of Bogdan Smolka include University of Toronto.


Papers
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Journal ArticleDOI
TL;DR: The proposed fully automated vector technique can be easily implemented in either hardware or software; and incorporated in any existing microarray image analysis and gene expression tool.
Abstract: Vector processing operations use essential spectral and spatial information to remove noise and localize microarray spots. The proposed fully automated vector technique can be easily implemented in either hardware or software; and incorporated in any existing microarray image analysis and gene expression tool.

348 citations

Journal ArticleDOI
TL;DR: 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.

190 citations

Journal ArticleDOI
TL;DR: Simulation studies reported in this paper indicate that the proposed filter class is computationally attractive, has excellent performance, and is able to preserve fine details while suppressing impulsive noise.

115 citations

Journal ArticleDOI
TL;DR: The results show that the proposed method outperforms most of the basic algorithms for the reduction of impulsive noise in color images.

113 citations

Journal ArticleDOI
TL;DR: A new class of filters for noise attenuation is introduced and its relationship with commonly used filtering techniques is investigated and it is indicated that the new filter outperforms the VMF, as well as other techniques currently used to eliminate impulsive noise in color images.
Abstract: In this paper, we address the problem of impulsive noise reduction in multichannel images. A new class of filters for noise attenuation is introduced and its relationship with commonly used filtering techniques is investigated. The computational complexity of the new filter is lower than that of the vector median filter (VMF). Extensive simulation experiments indicate that the new filter outperforms the VMF, as well as other techniques currently used to eliminate impulsive noise in color images.

112 citations


Cited by
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Journal ArticleDOI
TL;DR: Almost 300 key theoretical and empirical contributions in the current decade related to image retrieval and automatic image annotation are surveyed, and the spawning of related subfields are discussed, to discuss the adaptation of existing image retrieval techniques to build systems that can be useful in the real world.
Abstract: We have witnessed great interest and a wealth of promise in content-based image retrieval as an emerging technology. While the last decade laid foundation to such promise, it also paved the way for a large number of new techniques and systems, got many new people involved, and triggered stronger association of weakly related fields. In this article, we survey almost 300 key theoretical and empirical contributions in the current decade related to image retrieval and automatic image annotation, and in the process discuss the spawning of related subfields. We also discuss significant challenges involved in the adaptation of existing image retrieval techniques to build systems that can be useful in the real world. In retrospect of what has been achieved so far, we also conjecture what the future may hold for image retrieval research.

3,433 citations

01 Jan 2006

3,012 citations

Journal ArticleDOI
TL;DR: This paper attempts to provide a comprehensive survey of the recent technical achievements in high-level semantic-based image retrieval, identifying five major categories of the state-of-the-art techniques in narrowing down the 'semantic gap'.

1,713 citations

Book ChapterDOI
01 Jan 1996
TL;DR: Exploring and identifying structure is even more important for multivariate data than univariate data, given the difficulties in graphically presenting multivariateData and the comparative lack of parametric models to represent it.
Abstract: Exploring and identifying structure is even more important for multivariate data than univariate data, given the difficulties in graphically presenting multivariate data and the comparative lack of parametric models to represent it. Unfortunately, such exploration is also inherently more difficult.

920 citations

Proceedings Article
22 Aug 1999
TL;DR: The accessibility, usability, and, ultimately, acceptability of Information Society Technologies by anyone, anywhere, at anytime, and through any media and device is addressed.
Abstract: ▶ Addresses the accessibility, usability, and, ultimately, acceptability of Information Society Technologies by anyone, anywhere, at anytime, and through any media and device. ▶ Focuses on theoretical, methodological, and empirical research, of both technological and non-technological nature. ▶ Features papers that report on theories, methods, tools, empirical results, reviews, case studies, and best-practice examples.

752 citations