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    Scalable compression of imagery

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    azu_td_3073194_sip1_m.pdf
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    Author
    Bilgin, Ali
    Issue Date
    2002
    Keywords
    Engineering, Electronics and Electrical.
    Computer Science.
    Advisor
    Marcellin, Michael W.
    
    Metadata
    Show full item record
    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
    Recent image compression technologies value functionality as well as compression efficacy. In this dissertation, several compression methodologies that are both efficient and functional are introduced. The first compression system aims to compress three-dimensional data sets. In this system, existing two-dimensional zerotree coding techniques are extended to three dimensions, and are combined with integer wavelet transforms and context-based arithmetic coding. This system creates a unified framework for both lossless and lossy compression of three-dimensional data sets, and generates a scalable codestream. In our experiments, the system provided an average of 23% decrease in file size for representative three-dimensional data sets, compared to the best available two-dimensional lossless compression techniques. Strategies for transmission of JPEG2000 codestreams over packet-erasure channels are introduced next. These strategies are developed by allowing the channel coder to access information on the structure of the codestream generated by the source coder. Experimental results indicate that a carefully designed packetization strategy can provide significant performance improvement, especially when the channel experiences heavy erasures. Finally, utilization of JPEG2000 to compress scientific data is illustrated. In particular, a JPEG2000-based system that can be used to compress electrocardiogram (ECG) data is presented. Although this system utilizes the JPEG2000 image coding algorithm to compress one-dimensional ECG data, experimental results indicate that it compares favorably with specialized ECG compression methods in the literature.
    Type
    text
    Dissertation-Reproduction (electronic)
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Electrical and Computer Engineering
    Degree Grantor
    University of Arizona
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