Publication
Title
Joint quantisation and error diffusion of colour images using competitive learning
Author
Abstract
A competitive learning scheme for colour image quantisation is elaborated, in which the dithering process to eliminate contouring effects is embedded in the quantisation process instead of performed a posteriori. Quantisation is performed by clustering in colour space. The dithering process is a simple error diffusion, in which the quantisation error made by one pixel is diffused to its local neighbourhood. An objective function which takes the dithering process into account is optimised by use of a competitive learning approach. In this way, the colour quantisation process is optimally adapted to the dithered image, and the dithering process is optimally adapted to the colour palette. For small colour palettes, this is demonstrated to improve the visual quality of quantised images.
Language
English
Source (journal)
IEE proceedings. Vision, image and signal processing / Institution of Electrical Engineers [London] - Stevenage
Publication
Stevenage : IEE, 1998
ISSN
1350-245X
Volume/pages
145:2(1998), p. 137-140
ISI
000073942500010
Full text (Publisher's DOI)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 01.03.2012
Last edited 04.11.2017
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