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http://dx.doi.org/10.18419/opus-2978
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DC Element | Wert | Sprache |
---|---|---|
dc.contributor.author | Hijazi, Haytham W. | de |
dc.date.accessioned | 2012-12-10 | de |
dc.date.accessioned | 2016-03-31T08:00:04Z | - |
dc.date.available | 2012-12-10 | de |
dc.date.available | 2016-03-31T08:00:04Z | - |
dc.date.issued | 2012 | de |
dc.identifier.other | 377258997 | de |
dc.identifier.uri | http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-80061 | de |
dc.identifier.uri | http://elib.uni-stuttgart.de/handle/11682/2995 | - |
dc.identifier.uri | http://dx.doi.org/10.18419/opus-2978 | - |
dc.description.abstract | Image compression is a well-established and extensively researched field. The huge interest in it has been aroused by the rapid enhancements introduced in imaging techniques and the various applications that use high-resolution images (e.g. medical, astronomical, Internet applications). The image compression algorithms should not only give state-of-art performance, they should also provide other features and functionalities such as progressive transmission. Often, a rough approximation (thumbnail) of an image is sufficient for the user to decide whether to continue the image transmission or to abort; which accordingly helps to reduce time and bandwidth. That in turn necessitated the development of multi-resolution image compression schemes. The existed multi-resolution schemes (e.g., Multi-Level Progressive method) have shown high computational efficiency, but with a lack of the compression performance, in general. In this thesis, a LOw Complexity Multi-resolution Image Compression (LOCMIC) based on the Hierarchical INTerpolation (HINT) framework is presented. Moreover, a novel integration of the Just Noticeable Distortion (JND) for perceptual coding with the HINT framework to achieve a visual-lossless multi-resolution scheme has been proposed. In addition, various prediction formulas, a context-based prediction correction model and a multi-level Golomb parameter adaption approach have been investigated. The proposed LOCMIC (the lossless and the visual lossless) has contributed to the compression performance. The lossless LOCMIC has achieved a 3% reduced bit rate over LOCO-I, about 1% over JPEG2000, 3% over SPIHT, and 2% over CALIC. The Perceptual LOCMIC has been better in terms of bit rate than near-lossless JPEG-LS (at NEAR=2) with about 4.7%. Moreover, the decorrelation efficiency of the LOCMIC in terms of entropy has shown an advance of 2.8%, 4.5% than the MED and the conventional HINT respectively. | en |
dc.language.iso | en | de |
dc.rights | info:eu-repo/semantics/openAccess | de |
dc.subject.ddc | 004 | de |
dc.title | LOCMIC:LOw Complexity Multi-resolution Image Compression | en |
dc.type | masterThesis | de |
ubs.fakultaet | Fakultät Informatik, Elektrotechnik und Informationstechnik | de |
ubs.institut | Institut für Parallele und Verteilte Systeme | de |
ubs.opusid | 8006 | de |
ubs.publikation.typ | Abschlussarbeit (Master) | de |
Enthalten in den Sammlungen: | 05 Fakultät Informatik, Elektrotechnik und Informationstechnik |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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MSTR_3359.pdf | 2,09 MB | Adobe PDF | Öffnen/Anzeigen |
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