Efficient Computation of Convolution of Huge Images

SVOBODA, David. Efficient Computation of Convolution of Huge Images. In Giuseppe Maino; Gian Luca Foresti. Image Analysis and Processing - ICIAP 2011. LNCS 6978, Part I. Berlin, Heidelberg: Springer-Verlag, 2011, p. 453-462. ISBN 978-3-642-24084-3.

Basic information

Original name

Efficient Computation of Convolution of Huge Images

Authors

SVOBODA, David (203 Czech Republic, guarantor, belonging to the institution)

Edition

LNCS 6978, Part I. Berlin, Heidelberg, Image Analysis and Processing - ICIAP 2011, p. 453-462, 10 pp. 2011

Publisher

Springer-Verlag

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Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

20200 2.2 Electrical engineering, Electronic engineering, Information engineering

Country of publisher

Italy

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

RIV identification code

RIV/00216224:14330/11:00052768

Organization unit

Faculty of Informatics

ISBN

978-3-642-24084-3

UT WoS

000334925300047

Keywords in English

Convolution; Fast Fourier Transform; Divide-et-Impera

Tags

cbia-web

Tags

International impact, Reviewed

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Abstract

V originále

In image processing, convolution is a frequently used operation. It is an important tool for performing basic image enhancement as well as sophisticated analysis. Naturally, due to its necessity and still continually increasing size of processed image data there is a great demand for its efficient implementation. The fact is that the slowest algorithms (that cannot be practically used) implementing the convolution are capable of handling the data of arbitrary dimension and size. On the other hand, the fastest algorithms have huge memory requirements and hence impose image size limits. Regarding the convolution of huge images, which might be the subtask of some more sophisticated algorithm, fast and correct solution is essential. In this paper, we propose a fast algorithm implementing exact computation of the shift invariant convolution over huge multi-dimensional image data.

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Links

LC535, research and development project	Name: Dynamika a organizace chromosomů během buněčného cyklu v normě a patologii Investor: Ministry of Education, Youth and Sports of the CR, Dynamika a organizace chromosomů během buněčného cyklu v normě a patologii
MSM0021622419, plan (intention)	Name: Vysoce paralelní a distribuované výpočetní systémy Investor: Ministry of Education, Youth and Sports of the CR, Highly Parallel and Distributed Computing Systems
2B06052, research and development project	Name: Vytipování markerů, screening a časná diagnostika nádorových onemocnění pomocí vysoce automatizovaného zpracování multidimenzionálních biomedicínských obrazů (Acronym: Biomarker) Investor: Ministry of Education, Youth and Sports of the CR, Determination of markers, screening and early diagnostics of cancer diseases using highly automated processing of multidimensional biomedical images