No-reference perceptual sharpness assessment for ultra-high-definition images

Woojae Kim, Haksub Kim, Heeseok Oh, Jongyoo Kim, Sanghoon Lee

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

2 Citations (Scopus)

Abstract

Since ultra-high-definition (UHD) display has larger resolution and various display size, it is necessary to measure image sharpness considering variation in visual resolution caused by diverse viewing geometry. In this paper, we propose a no-reference perceptual sharpness assessment model of UHD images. The proposed model analyzes viewing geometry in terms of display resolution and viewing environment. Then, we measure the local adaptive sharpness score in accordance with the textural motion blur, texture, and edge. In addition, we propose a spatial pooling method associated with foveal regions, which is caused by nonuniform distribution of the photoreceptors on a human retina. Through the rigorous experiments, we demonstrate that the proposed model can measure the sharpness of UHD images more accurately than other image sharpness assessment methods.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PublisherIEEE Computer Society
Pages86-90
Number of pages5
ISBN (Electronic)9781467399616
DOIs
Publication statusPublished - 2016 Aug 3
Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
Duration: 2016 Sep 252016 Sep 28

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2016-August
ISSN (Print)1522-4880

Other

Other23rd IEEE International Conference on Image Processing, ICIP 2016
CountryUnited States
CityPhoenix
Period16/9/2516/9/28

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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  • Cite this

    Kim, W., Kim, H., Oh, H., Kim, J., & Lee, S. (2016). No-reference perceptual sharpness assessment for ultra-high-definition images. In 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings (pp. 86-90). [7532324] (Proceedings - International Conference on Image Processing, ICIP; Vol. 2016-August). IEEE Computer Society. https://doi.org/10.1109/ICIP.2016.7532324