Prangnell, Lee and Sanchez Silva, Victor (2021) HVS-based perceptual color compression of image data. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021), Toronto, Ontario, Canada, 6-11 Jun 2021. Published in: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ISSN 2379-190X. doi:10.1109/ICASSP39728.2021.9414773

Preview

PDF WRAP-HVS-based-perceptual-color-compression-image-data-Prangnell-2021.pdf - Accepted Version - Requires a PDF viewer. Download (2016Kb) | Preview

Request Changes to record.

Abstract

In perceptual image coding applications, the main objective is to decrease, as much as possible, Bits Per Pixel (BPP) while avoiding noticeable distortions in the reconstructed image. In this paper, we propose a novel perceptual image coding technique, named Perceptual Color Compression (PCC). PCC is based on a novel model related to Human Visual System (HVS) spectral sensitivity and CIELAB Just Noticeable Color Difference (JNCD). We utilize this modeling to capitalize on the inability of the HVS to perceptually differentiate photons in very similar wavelength bands (e.g., distinguishing very similar shades of a particular color or different colors that look similar). The proposed PCC technique can be used with RGB (4:4:4) image data of various bit depths and spatial resolutions. In the evaluations, we compare the proposed PCC technique with a set of reference methods including Versatile Video Coding (VVC) and High Efficiency Video Coding (HEVC) in addition to two other recently proposed algorithms. Our PCC method attains considerable BPP reductions compared with all four reference techniques including, on average, 52.6% BPP reductions compared with VVC (VVC in All Intra still image coding mode). Regarding image perceptual reconstruction quality, PCC achieves a score of SSIM ≥ 0.99 in all tests in addition to a score of MS-SSIM ≥ 0.99 in all but one test. Moreover, MOS = 5 is attained in 75% of subjective evaluation assessments conducted.

Item Type:	Conference Item (Paper)
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Science > Computer Science
Library of Congress Subject Headings (LCSH):	Image compression, Image processing, Computer vision , Coding theory
Journal or Publication Title:	ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Publisher:	IEEE
ISSN:	2379-190X
Official Date:	13 May 2021
Dates:	Date Event 13 May 2021 Published 29 January 2021 Accepted
DOI:	10.1109/ICASSP39728.2021.9414773
Status:	Peer Reviewed
Publication Status:	Published
Publisher Statement:	© Copyright 2021 IEEE. Published in ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), scheduled for 6-11 June 2021 in Toronto, Ontario, Canada. 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. Contact: Manager, Copyrights and Permissions / IEEE Service Center / 445 Hoes Lane / P.O. Box 1331 / Piscataway, NJ 08855-1331, USA. Telephone: + Intl. 908-562-3966.
Access rights to Published version:	Restricted or Subscription Access
Conference Paper Type:	Paper
Title of Event:	IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021)
Type of Event:	Conference
Location of Event:	Toronto, Ontario, Canada
Date(s) of Event:	6-11 Jun 2021
Related URLs:	Publisher

Request changes or add full text files to a record

Repository staff actions (login required)

View Item

Downloads