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Reference TypeConference Paper (Conference Proceedings)
Last Update2013: (UTC) administrator
Metadata Last Update2013: (UTC) administrator
Citation KeyAnguhMart:1994:FaMeCo
TitleFaster methods for computing slant haar transforms of digital images
FormatImpresso, On-line.
Access Date2021, Dec. 03
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Author1 Anguh, Maurence M.
2 Martin, Ralph R.
Affiliation1 Department of Electrical Engineering of Centro Tecnológia of Federal University of Maranhão (UFMA)
2 Department of Computing Mathematics (UWCC)
EditorFreitas, Carla dal Sasso
Geus, Klaus de
Scheer, Sérgio
Conference NameSimpósio Brasileiro de Computação Gráfica e Processamento de Imagens, 7 (SIBGRAPI)
Conference LocationCuritiba
Date9 - 11 nov. 1994
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleAnais
Tertiary TypeArtigo
History (UTC)2013-01-23 01:20:34 :: -> administrator ::
2013-02-02 13:16:04 :: administrator -> :: 1994
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Is the master or a copy?is the master
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KeywordsTruncation Slant Haar Transform
Slant Haar Transform
Fast Slant Haar Transform
digital images
faster methods for computing
AbstractA phenomenon characteristic of digital images is the presence of approximately constant or uniformly changing gray levels over a considerable distance or area. A novel method, the Truncation Slant Haar Transform (TSHT) method for computing the Slant Haar Transform (SHT) of digital images is presented which exploits this phenomenon to advantage. The TSHT method utilizes a hierarchical tree to segment and aggregate uniform image data and a matrix factorization to eliminate transform matrix redundancies. This simultaneous exploitation of inter-pixel relationships and the elimination of transform matrix redundancies produces an efficient method for computing the SHT of digital images. In one dimension with an array of N=2n data values, the TSHT method takes time between O (N) and (N log2 N), thus degenerating to the performance of the standard Fast Slant Haar Transform (FSHT) method. In two dimensions with an array of size N x N, the performance of the TSHT method is between O (N2) and O (N2 log2 N), again degenerating to that of the FSHT method in its worst case. Since coherence is a fundamental characteristic of digital images, the TSHT method is therefore superior to the FSHT method when used to compute the SHT of coherent digital images. Experimental results are presented to justify this assertion.
TypeProcessamento de Imagens II
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