A JND DATASET BASED ON VVC COMPRESSED IMAGES

Xuelin Shen, Zhangkai Ni, Wenhan Yang, Xinfeng Zhang, Shiqi Wang, Sam Kwong

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

19 Citations (Scopus)

Abstract

In this paper, we establish a just noticeable distortion (JND) dataset based on the next generation video coding standard Versatile Video Coding (VVC). The dataset consists of 202 images which cover a wide range of content with resolution 1920×1080. Each image is encoded by VTM 5.0 intra coding with the quantization parameter (QP) ranging from 13 to 51. The details regarding dataset construction, subjective testing and data post-processing are described in this paper. Finally, the significance of the dataset towards future video coding research is envisioned. All source images as well as the testing data have been made available to the public.
Original languageEnglish
Title of host publication2020 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)
PublisherIEEE
Number of pages6
ISBN (Electronic)978-1-7281-1485-9
ISBN (Print)978-1-7281-1486-6
DOIs
Publication statusPublished - Jul 2020
Event2020 IEEE International Conference on Multimedia and Expo (ICME 2020) - Virtual, London, United Kingdom
Duration: 6 Jul 202010 Jul 2020
https://www.2020.ieeeicme.org/

Publication series

NameIEEE International Conference on Multimedia and Expo Workshops, ICMEW

Conference

Conference2020 IEEE International Conference on Multimedia and Expo (ICME 2020)
PlaceUnited Kingdom
CityLondon
Period6/07/2010/07/20
Internet address

Research Keywords

  • Just noticeable distortion
  • visual perception

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