A visual discrimination model for JPEG2000 compression

Feng Liu, Yuzhang Lin, Miguel Hernandez-Cabronero, Eze Ahanonu, Michael W Marcellin, Amit Ashok, Ali Bilgin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a visual discrimation model to enable perceptually optimized JPEG200 compression for both near-threshold and supra-threshold regimes. The performance of the proposed approach is validated by comparing it to the conventional Mean Squared Error (MSE)-optimized compression.

Original languageEnglish (US)
Title of host publicationProceedings - DCC 2018
Subtitle of host publication2018 Data Compression Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages1
Volume2018-March
ISBN (Electronic)9781538648834
DOIs
Publication statusPublished - Jul 19 2018
Event2018 Data Compression Conference, DCC 2018 - Snowbird, United States
Duration: Mar 27 2018Mar 30 2018

Other

Other2018 Data Compression Conference, DCC 2018
CountryUnited States
CitySnowbird
Period3/27/183/30/18

Keywords

  • Image Compression
  • JPEG2000
  • Just Noticeable Difference
  • Visibility Threshold
  • Visual Discrimination Model

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Liu, F., Lin, Y., Hernandez-Cabronero, M., Ahanonu, E., Marcellin, M. W., Ashok, A., & Bilgin, A. (2018). A visual discrimination model for JPEG2000 compression. In Proceedings - DCC 2018: 2018 Data Compression Conference (Vol. 2018-March). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DCC.2018.00077