Adaptive wavelet filter design for digital signal processing systems

Simple item page
dc.creatorKustov, Vadim Michailovich
dc.date.accessioned2016-11-14T23:08:53Z
dc.date.available2011-02-18T23:16:41Z
dc.date.available2016-11-14T23:08:53Z
dc.date.issued2000-12
dc.degree.departmentElectrical and Computer Engineeringen_US
dc.description.abstractDiscrete wavelet transform has been used in many image/signal processing applications in recent years. However, the design of optimized and adaptive wavelet filter banks is still a significant research topic, specifically in image/signal compression. A number of wavelet-based advanced lossy compression algorithms provide high-fidelity reconstmction of input images at computationally intensive costs. The present work investigates the potential and the limitations of optimized adaptive design of two-channel perfect reconstmction filters when the signal in a channel is subjected to coarse quantization during the encoding process of such advanced compression algorithms. A real-time optimal two-channel perfect reconstmction filter bank design algorithm has been developed and implemented in a digital signal processor. The algorithm has been used in a newly developed execution time reduction method to reduce the computational costs and data storage requirement of image compression algorithms. A reduction of execution time by two to three times has been achieved without adding appreciable distortion to the reconstmcted image.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/2346/19718en_US
dc.language.isoeng
dc.publisherTexas Tech Universityen_US
dc.rights.availabilityUnrestricted.
dc.subjectSignal processingen_US
dc.subjectAdaptive signal processingen_US
dc.subjectImage processingen_US
dc.subjectImage compressionen_US
dc.subjectAdaptive filtersen_US
dc.titleAdaptive wavelet filter design for digital signal processing systems
dc.typeDissertation

Files

Collections

Texas Tech University