Image decomposition into structure and texture subcomponents with multifrequency modulation constraints

Evangelopoulos, G; Maragos, P

dc.contributor.author	Evangelopoulos, G	en
dc.contributor.author	Maragos, P	en
dc.date.accessioned	2014-03-01T02:45:30Z
dc.date.available	2014-03-01T02:45:30Z
dc.date.issued	2008	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32279
dc.subject	Geometric Structure	en
dc.subject	Image Decomposition	en
dc.subject	Image Modeling	en
dc.subject	Linear Filtering	en
dc.subject	piecewise smooth	en
dc.subject	Front End	en
dc.subject.other	Artificial intelligence	en
dc.subject.other	Computational geometry	en
dc.subject.other	Computer vision	en
dc.subject.other	Decomposition	en
dc.subject.other	Estimation	en
dc.subject.other	Feature extraction	en
dc.subject.other	Frequency response	en
dc.subject.other	Image enhancement	en
dc.subject.other	Image processing	en
dc.subject.other	Modulation	en
dc.subject.other	Pattern recognition	en
dc.subject.other	Separation	en
dc.subject.other	Classification performance	en
dc.subject.other	Decomposition scheme	en
dc.subject.other	Front end	en
dc.subject.other	Geometric structures	en
dc.subject.other	Image decomposition	en
dc.subject.other	Image modeling	en
dc.subject.other	Intensity variations	en
dc.subject.other	Inverse estimation	en
dc.subject.other	Linear filtering	en
dc.subject.other	Macrostructures	en
dc.subject.other	Multi bands	en
dc.subject.other	Multi-frequency	en
dc.subject.other	Texture components	en
dc.subject.other	Texture information	en
dc.subject.other	Texture modeling	en
dc.subject.other	Textures	en
dc.title	Image decomposition into structure and texture subcomponents with multifrequency modulation constraints	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/CVPR.2008.4587649	en
heal.identifier.secondary	http://dx.doi.org/10.1109/CVPR.2008.4587649	en
heal.identifier.secondary	4587649	en
heal.publicationDate	2008	en
heal.abstract	Texture information in images is coupled with geometric macrostructures and piecewise-smooth intensity variations. Decomposing an image f into a geometric structure component u and a texture component v is an inverse estimation problem, essential for understanding and analyzing images depending on their content. In this paper, we present a novel combined approach for simultaneous texture from structure separation and multiband texture modeling. First, we formulate a new, variational decomposition scheme, involving an explicit texture reconstruction constraint (prior) formed by the responses of selected frequency-tuned linear filters. This forms a 'u + Kv' image model of K + 1 components. Subsequent texture modeling is applied to the estimated v component and its consistency is compared to using the complete, initial image f. The decomposition step, functioning as an advanced texture-front end, improves clustering and classification performance, for various multiband features. The proposed method can be generalized to other texture models or applications. ©2008 IEEE.	en
heal.journalName	26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR	en
dc.identifier.doi	10.1109/CVPR.2008.4587649	en