Image coding using adaptive recursive interpolative DPCM with entropy-constrained trellis coded quantization.

Persistent Link:
http://hdl.handle.net/10150/186467
Title:
Image coding using adaptive recursive interpolative DPCM with entropy-constrained trellis coded quantization.
Author:
Gifford, Eric Allan.
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:
The goal of image coding is to represent images with a minimum amount of distortion at a given encoding rate. Image coding algorithms comprise methods for generating uncorrelated sequences and quantizing the uncorrelated sequences. The earliest encoding algorithms, such as Differential Pulse Code Modulation, are prediction based and must be considered primitive when compared to the more recent transform coders, such as Discrete Cosine Transform or Discrete Wavelet Transform. Judged only by SNR performance, the contemporary transform coders are far superior to the predictive coders. However, the computational complexity of the transform coders is much greater than predictive coders. In general, the improvement of hardware has diminished the importance of computational complexity. Thus, little research has been devoted to improving the performance of predictive coders. Furthermore, in a few applications such as remote decoding or real-time video decoding, the complexity of the decoder is still a constraint. In this dissertation, I have developed a predictive image coder having minimal decoder complexity and providing SNR's in the range of the most advanced transform coders. The image coder utilizes the Recursive Interpolative DPCM algorithm as a kernel in conjunction with an adaptive rate allocation scheme and entropy-constrained trellis coded quantization. The Adaptive RIDPCM-ECTCQ image coder is a high performance, low decoder-complexity alternative to contemporary transform coders.
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:
Hunt, Bobby R.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleImage coding using adaptive recursive interpolative DPCM with entropy-constrained trellis coded quantization.en_US
dc.creatorGifford, Eric Allan.en_US
dc.contributor.authorGifford, Eric Allan.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.abstractThe goal of image coding is to represent images with a minimum amount of distortion at a given encoding rate. Image coding algorithms comprise methods for generating uncorrelated sequences and quantizing the uncorrelated sequences. The earliest encoding algorithms, such as Differential Pulse Code Modulation, are prediction based and must be considered primitive when compared to the more recent transform coders, such as Discrete Cosine Transform or Discrete Wavelet Transform. Judged only by SNR performance, the contemporary transform coders are far superior to the predictive coders. However, the computational complexity of the transform coders is much greater than predictive coders. In general, the improvement of hardware has diminished the importance of computational complexity. Thus, little research has been devoted to improving the performance of predictive coders. Furthermore, in a few applications such as remote decoding or real-time video decoding, the complexity of the decoder is still a constraint. In this dissertation, I have developed a predictive image coder having minimal decoder complexity and providing SNR's in the range of the most advanced transform coders. The image coder utilizes the Recursive Interpolative DPCM algorithm as a kernel in conjunction with an adaptive rate allocation scheme and entropy-constrained trellis coded quantization. The Adaptive RIDPCM-ECTCQ image coder is a high performance, low decoder-complexity alternative to contemporary transform coders.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.chairHunt, Bobby R.en_US
dc.contributor.committeememberMarcellin, Michael W.en_US
dc.contributor.committeememberSchowengerdt, Roberten_US
dc.identifier.proquest9410668en_US
dc.identifier.oclc721344932en_US
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