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dc.contributor.authorBalakrishnan, Venkataramanan
dc.contributor.authorMaciejewski, Anthony A.
dc.contributor.authorChang, Chu-Yin
dc.date.accessioned2007-01-03T07:26:30Z
dc.date.available2007-01-03T07:26:30Z
dc.date.issued2000
dc.descriptionIncludes bibliographical references.
dc.description.abstractWe present a computationally efficient algorithm for the eigenspace decomposition of correlated images. Our approach is motivated by the fact that for a planar rotation of a two-dimensional (2-D) image, analytical expressions can be given for the eigendecomposition, based on the theory of circulant matrices. These analytical expressions turn out to be good first approximations of the eigendecomposition, even for three-dimensional (3-D) objects rotated about a single axis. In addition, the theory of circulant matrices yields good approximations to the eigendecomposition for images that result when objects are translated and scaled. We use these observations to automatically determine the dimension of the subspace required to represent an image with a guaranteed user-specified accuracy, as well as to quickly compute a basis for the subspace. Examples show that the algorithm performs very well on a number of test cases ranging from images of 3-D objects rotated about a single axis to arbitrary video sequences.
dc.description.sponsorshipThis work was supported by the Sze Tsao Chang Memorial Engineering Fund, the National Imagery and Mapping Agency under Contract NMA201-00-1-1003, and by the Office of Naval Research under Contract N00014-97-1-0640.
dc.format.mediumborn digital
dc.format.mediumarticles
dc.identifier.bibliographicCitationChang, Chu-Yin, Anthony A. Maciejewski, and Venkataramanan Balakrishnan, Fast Eigenspace Decomposition of Correlated Images, IEEE Transactions on Image Processing 9, no. 11 (November 2000): 1937-1949.
dc.identifier.urihttp://hdl.handle.net/10217/619
dc.languageEnglish
dc.publisherColorado State University. Libraries
dc.publisher.originalIEEE
dc.relation.ispartofFaculty Publications - Department of Electrical and Computer Engineering
dc.rights©2000, IEEE
dc.subjectimage sequences
dc.subjectimage representation
dc.subjecteigenvalues and eigenfunctions
dc.subjectmatrix algebra
dc.subjectvideo signal processing
dc.titleFast eigenspace decomposition of correlated images
dc.typeText


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