Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Graph-based transform with weighted self-loops for predictive transform coding based on template matching

Tools
- Tools
+ Tools

Roy, Debaleena, Guha, Tanaya and Sanchez Silva, Victor (2019) Graph-based transform with weighted self-loops for predictive transform coding based on template matching. In: Data Compression Conference (DCC 2019), Snowbird, UT, 26-29 Mar 2019. Published in: 2019 Data Compression Conference (DCC) pp. 329-338. ISBN 9781728106588 . ISSN 1068-0314 . doi:10.1109/DCC.2019.00041

[img]
Preview
PDF
WRAP-graph-based-transform-weighted-self-loops-coding-matching-Roy-2019.pdf - Accepted Version - Requires a PDF viewer.

Download (4Mb) | Preview
Official URL: https://doi.org/10.1109/DCC.2019.00041

Request Changes to record.

Abstract

This paper introduces the GBT-L, a novel class of Graph-based Transform within the con- text of block-based predictive transform coding. The GBT-L is constructed using a 2D graph with unit edge weights and weighted self-loops in every vertex. The weighted self- loops are selected based on the residual values to be transformed. To avoid signalling any additional information required to compute the inverse GBT-L, we also introduce a coding framework that uses a template-based strategy to predict residual blocks in the pixel and residual domains. Evaluation results on several video frames and medical images, in terms of the percentage of preserved energy and mean square error, show that the GBT-L can outperform the DST, DCT and the Graph-based Separable Transform

Item Type: Conference Item (Paper)
Subjects: T Technology > TR Photography
Divisions: Faculty of Science, Engineering and Medicine > Science > Computer Science
Library of Congress Subject Headings (LCSH): Data compression (Computer science), Image compression, Video compression
Journal or Publication Title: 2019 Data Compression Conference (DCC)
Publisher: IEEE
ISBN: 9781728106588
ISSN: 1068-0314
Official Date: 13 May 2019
Dates:
DateEvent
13 May 2019Published
28 December 2018Accepted
Page Range: pp. 329-338
DOI: 10.1109/DCC.2019.00041
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Conference Paper Type: Paper
Title of Event: Data Compression Conference (DCC 2019)
Type of Event: Conference
Location of Event: Snowbird, UT
Date(s) of Event: 26-29 Mar 2019
Related URLs:
  • Organisation
  • Other

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us