Visual Preference Prediction for Enhanced Images on Ultra-High-Definition Display

Sewoong Ahn, Woojae Kim, Jinwoo Kim, Jaekyung Kim, Sanghoon Lee

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

1 Citation (Scopus)

Abstract

Due to the evolution of ultra-high-definition (UHD) technologies, viewers can enjoy more realistic contents. Furthermore, in order to maximize visual attraction, post-processing is conducted in commercial devices. In this paper, we propose a new terminology called visual preference to quantify viewer's preferences for sharpness- and contrast- enhanced UHD images in a particular viewing geometry. Visual preferences depend on the spatial characteristics and are affected by the viewing geometry of display like resolution, display size, and viewing distance. Therefore, we propose a method called visual preference assessment model that accounts for content enhancement features and diverse viewing geometry. By rigorous experiments, our proposed model outperforms other state-of-the-art models.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings
PublisherIEEE Computer Society
Pages3548-3552
Number of pages5
ISBN (Electronic)9781479970612
DOIs
Publication statusPublished - 2018 Aug 29
Event25th IEEE International Conference on Image Processing, ICIP 2018 - Athens, Greece
Duration: 2018 Oct 72018 Oct 10

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference25th IEEE International Conference on Image Processing, ICIP 2018
Country/TerritoryGreece
CityAthens
Period18/10/718/10/10

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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