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dc.contributor.authorWakin, Michael
dc.creatorWakin, Michael 2007-10-31T01:08:40Z 2007-10-31T01:08:40Z 2002-05-20 2002-05-21
dc.description Masters Thesis
dc.description.abstract Edges are of particular interest for image compression, as they communicate important information, contribute large amounts of high-frequency energy, and can generally be described with few parameters. Many of today's most competitive coders rely on wavelets to transform and compress the image, but modeling the joint behavior of wavelet coefficients along an edge presents a distinct challenge. In this thesis, we examine techniques for exploiting the simple geometric structure which captures edge information. Using a multiscale wedgelet decomposition, we present methods for extracting and compressing a cartoon sketch containing the significant edge information, and we discuss practical issues associated with coding the residual textures. Extending these techniques, we propose a rate-distortion optimal framework (based on the Space-Frequency Quantization algorithm) using wedgelets to capture geometric information and wavelets to describe the rest. At low bitrates, this method yields compressed images with sharper edges and lower mean-square error.
dc.language.iso eng
dc.subjectimage compression
geometric edge models
edge cartoon
dc.subject.otherWavelet based Signal/Image Processing
dc.title Image Compression using Multiscale Geometric Edge Models
dc.type Thesis
dc.citation.bibtexName mastersthesis
dc.citation.journalTitle Masters Thesis 2003-07-12
dc.contributor.orgDigital Signal Processing (
dc.subject.keywordimage compression
geometric edge models
edge cartoon Masters
dc.type.dcmi Text
dc.identifier.citation M. Wakin, "Image Compression using Multiscale Geometric Edge Models," Masters Thesis, 2002.

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  • ECE Publications [1074]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students
  • DSP Publications [508]
    Publications by Rice Faculty and graduate students in digital signal processing.

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