Persistent Link:
http://hdl.handle.net/10150/186365
Title:
Low bit-rate transform and wavelet image coding.
Author:
Sriram, Parthasarathy.
Issue Date:
1993
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
In this dissertation, adaptive wavelet and transform coding techniques are presented for low bit-rate monochrome and color image coding. The proposed encoders are based on trellis coded quantization. Trellis coded quantization (TCQ) is an effective scheme for quantizing memoryless sources with low to moderate complexity. The TCQ approach to data compression has led to some of the most effective source codes found to date for memoryless sources. For the transform coder, TCQ is used to encode transform coefficients resulting from applying a 16 x 16 discrete cosine transform (DCT) to 8-bit gray level and 24-bit color images. For the color images, the red, green, and the blue planes were transformed into NTSC transmission primaries (Y, I, and Q) before the DCT is applied. Both fixed-rate and entropy-constrained systems are considered. The discrete wavelet transform has recently emerged as a powerful technique for decomposing images into various multi-resolution approximations. We investigate the use of entropy-constrained trellis coded quantization for encoding the wavelet coefficients of both monochrome and color images. The lowest resolution sub-image is encoded using a 4 x 4 2-D DCT encoder. An integer programming algorithm is employed to allocate the available bit-rate optimally among the subbands. The objective performance results of our wavelet and transform coders are comparable to or surpass all previous results reported in the literature. The subjective quality of the encoded images is also excellent. In particular, the encoded monochrome images at 0.5 bits/pixel (a compression ratio of 16:1) obtained using our adaptive wavelet coder is almost indistinguishable from the original even when viewed on a high-resolution monitor.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Dissertations, Academic.; Electrical engineering.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Electrical and Computer Engineering; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Marcellin, Michael W.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleLow bit-rate transform and wavelet image coding.en_US
dc.creatorSriram, Parthasarathy.en_US
dc.contributor.authorSriram, Parthasarathy.en_US
dc.date.issued1993en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractIn this dissertation, adaptive wavelet and transform coding techniques are presented for low bit-rate monochrome and color image coding. The proposed encoders are based on trellis coded quantization. Trellis coded quantization (TCQ) is an effective scheme for quantizing memoryless sources with low to moderate complexity. The TCQ approach to data compression has led to some of the most effective source codes found to date for memoryless sources. For the transform coder, TCQ is used to encode transform coefficients resulting from applying a 16 x 16 discrete cosine transform (DCT) to 8-bit gray level and 24-bit color images. For the color images, the red, green, and the blue planes were transformed into NTSC transmission primaries (Y, I, and Q) before the DCT is applied. Both fixed-rate and entropy-constrained systems are considered. The discrete wavelet transform has recently emerged as a powerful technique for decomposing images into various multi-resolution approximations. We investigate the use of entropy-constrained trellis coded quantization for encoding the wavelet coefficients of both monochrome and color images. The lowest resolution sub-image is encoded using a 4 x 4 2-D DCT encoder. An integer programming algorithm is employed to allocate the available bit-rate optimally among the subbands. The objective performance results of our wavelet and transform coders are comparable to or surpass all previous results reported in the literature. The subjective quality of the encoded images is also excellent. In particular, the encoded monochrome images at 0.5 bits/pixel (a compression ratio of 16:1) obtained using our adaptive wavelet coder is almost indistinguishable from the original even when viewed on a high-resolution monitor.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectDissertations, Academic.en_US
dc.subjectElectrical engineering.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineElectrical and Computer Engineeringen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairMarcellin, Michael W.en_US
dc.contributor.committeememberStrickland, Robin N.en_US
dc.contributor.committeememberRodriguez, Jeffrey J.en_US
dc.identifier.proquest9408397en_US
dc.identifier.oclc720404077en_US
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