Please use this identifier to cite or link to this item:
Title: A technique for lossy compression of error-diffused halftones
Authors: Cheung, SM
Chan, YH 
Keywords: Image coding
Matrix algebra
Nyquist diagrams
Signal filtering and prediction
Transfer functions
Vector quantization
Issue Date: 2004
Publisher: IEEE
Source: ICME : 2004 IEEE International Conference Multimedia and Expo : Taipei, Taiwan, June 27-30, 2004, p. 1083-1086 (CD) How to cite?
Abstract: In this paper, a new technique for lossy compression of halftone images is proposed based on the vector quantization technique. A conventional vector quantization encoder is modified such that it embeds a block-based error diffusion process and takes a HVS model into account during the compression. This modification significantly improves the visual performance of encoded images while the compression ratio achieved is identical to that of vector quantization.
ISBN: 0-7803-8603-5
Rights: © 2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Appears in Collections:Conference Paper

Files in This Item:
File Description SizeFormat 
Lossy compression of error-diffused halftones_04.pdf316.07 kBAdobe PDFView/Open
View full-text via PolyU eLinks SFX Query
Show full item record


Last Week
Last month
Citations as of Apr 10, 2016

Page view(s)

Last Week
Last month
Checked on Jul 9, 2017


Checked on Jul 9, 2017

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.