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231223s2007 xx ||||| 00| ||eng c |
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|a DE-627
|b ger
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|e rakwb
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|a eng
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| 100 |
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|a Alani, Dror
|e verfasserin
|4 aut
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|a Image coding with geometric wavelets
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|c 2007
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|a Text
|b txt
|2 rdacontent
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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|a Band
|b nc
|2 rdacarrier
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|a Date Completed 28.02.2007
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|a Date Revised 26.10.2019
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|a published: Print
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|a Citation Status MEDLINE
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|a This paper describes a new and efficient method for low bit-rate image coding which is based on recent development in the theory of multivariate nonlinear piecewise polynomial approximation. It combines a binary space partition scheme with geometric wavelet (GW) tree approximation so as to efficiently capture curve singularities and provide a sparse representation of the image. The GW method successfully competes with state-of-the-art wavelet methods such as the EZW, SPIHT, and EBCOT algorithms. We report a gain of about 0.4 dB over the SPIHT and EBCOT algorithms at the bit-rate 0.0625 bits-per-pixels (bpp). It also outperforms other recent methods that are based on "sparse geometric representation." For example, we report a gain of 0.27 dB over the Bandelets algorithm at 0.1 bpp. Although the algorithm is computationally intensive, its time complexity can be significantely reduced by collecting a "global" GW n-term approximation to the image from a collection of GW trees, each constructed separately over tiles of the image
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|a Journal Article
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|a Averbuch, Amir
|e verfasserin
|4 aut
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| 700 |
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|a Dekel, Shai
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 16(2007), 1 vom: 29. Jan., Seite 69-77
|w (DE-627)NLM09821456X
|x 1941-0042
|7 nnns
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| 773 |
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|g volume:16
|g year:2007
|g number:1
|g day:29
|g month:01
|g pages:69-77
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|d 16
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|h 69-77
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