Fast fractal image compression using pyramids

Lin, H; Venetsanopoulos, AN

dc.contributor.author	Lin, H	en
dc.contributor.author	Venetsanopoulos, AN	en
dc.date.accessioned	2014-03-01T01:47:12Z
dc.date.available	2014-03-01T01:47:12Z
dc.date.issued	1998	en
dc.identifier.issn	00913286	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/25172
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-1542781320&partnerID=40&md5=bc54f93ccc64a689b80420231e37c647	en
dc.subject	Compression	en
dc.subject	Fast algorithm	en
dc.subject	Fractal coding	en
dc.subject	Pyramid	en
dc.title	Fast fractal image compression using pyramids	en
heal.type	journalArticle	en
heal.publicationDate	1998	en
heal.abstract	Fractal image compression is based on the self-similarity search of the image. The encoding process is computationally intensive. We present a fast fractal image encoding algorithm that is based on a refinement of the fractal code from an initial coarse level of a pyramid. Assuming that the distribution of the matching error is described by an independent, identically distributed (i.i.d.) Laplacian random process, we derive the threshold sequence for the objective function in each pyramidal level. The algorithm is quasi-optimal in terms of minimizing the mean square error. Computational efficiency depends on the depth of the pyramid and the search step size, and could be improved by up to two orders of magnitude over the computational effort required for a full search of the original image. © 1998 Society of Photo-Optical Instrumentation Engineers.	en
heal.journalName	Optical Engineering	en
dc.identifier.volume	37	en
dc.identifier.issue	6	en
dc.identifier.spage	1720	en
dc.identifier.epage	1731	en