Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Electronic and Information Engineering | en_US |
| dc.creator | Chen, Zhengtong | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/6448 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | An improved algorithm for producing scalable color quantized images | en_US |
| dcterms.abstract | Error diffusion has been widely used as an effective halftoning method to produce color-quantized images of high quality for a long time. Along with the rapid expansion in the volume of information transmission, image content occupies a large share of it. To deliver color images efficiently to diverse users of different quality requirements over a heterogeneous network, the images to be delivered should be scalable in a way that their lower quality versions are embedded in their full scale versions such that no extra memory and bandwidth overhead is required to deliver them. Besides, their lower quality versions should be easily extracted from the full scale versions to minimize the extraction complexity. The work presented in this dissertation addresses this issue and proposes a modification to a conventional algorithm to improve the output quality of the produced scalable color-quantized images. | en_US |
| dcterms.extent | ix, 72 leaves : ill. (chiefly col.) ; 30 cm. | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2012 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Image processing -- Digital techniques. | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b24757639.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 2.38 MB | Adobe PDF | View/Open |
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