Skip to main navigation Skip to search Skip to main content

The effect of image rotation on UTV decomposition

  • Yodehanan Wongsawat

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Since the singular value decomposition (SVD) consumes high computational complexity on updating its eigenvectors and eigenvalues when new data are included, an alternate rank-revealing orthogonal decomposition that can eliminate this problem such as the UTV decomposition is one of our particular interest. This paper presents a study on directions of principal structures of the images and their effects when the UTV decomposition is employed. The relationship between the UTV decomposition and SVD is also explored. The proposed image denoising algorithm illustrates that the UTV decomposition can efficiently decompose images with vertical/horizontal structures into only a few component as well as the SVD.

Original languageEnglish
Title of host publicationICALIP 2008 - 2008 International Conference on Audio, Language and Image Processing, Proceedings
Pages1467-1470
Number of pages4
DOIs
Publication statusPublished - 2008
EventICALIP 2008 - 2008 International Conference on Audio, Language and Image Processing - Shanghai, China
Duration: 7 Jul 20089 Jul 2008

Publication series

NameICALIP 2008 - 2008 International Conference on Audio, Language and Image Processing, Proceedings

Conference

ConferenceICALIP 2008 - 2008 International Conference on Audio, Language and Image Processing
Country/TerritoryChina
CityShanghai
Period7/07/089/07/08

Fingerprint

Dive into the research topics of 'The effect of image rotation on UTV decomposition'. Together they form a unique fingerprint.

Cite this