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

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

doi:10.1109/ICIP.2018.8451330

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

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

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings
Publisher	IEEE Computer Society
Pages	3548-3552
Number of pages	5
ISBN (Electronic)	9781479970612
DOIs	https://doi.org/10.1109/ICIP.2018.8451330
Publication status	Published - 2018 Aug 29
Event	25th IEEE International Conference on Image Processing, ICIP 2018 - Athens, Greece Duration: 2018 Oct 7 → 2018 Oct 10

Publication series

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

Conference

Conference	25th IEEE International Conference on Image Processing, ICIP 2018
Country	Greece
City	Athens
Period	18/10/7 → 18/10/10

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

All Science Journal Classification (ASJC) codes

Software
Computer Vision and Pattern Recognition
Signal Processing

Access to Document

10.1109/ICIP.2018.8451330

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Ahn, S., Kim, W., Kim, J., Kim, J., & Lee, S. (2018). Visual Preference Prediction for Enhanced Images on Ultra-High-Definition Display. In 2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings (pp. 3548-3552). [8451330] (Proceedings - International Conference on Image Processing, ICIP). IEEE Computer Society. https://doi.org/10.1109/ICIP.2018.8451330

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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.",

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Ahn, S, Kim, W, Kim, J, Kim, J & Lee, S 2018, Visual Preference Prediction for Enhanced Images on Ultra-High-Definition Display. in 2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings., 8451330, Proceedings - International Conference on Image Processing, ICIP, IEEE Computer Society, pp. 3548-3552, 25th IEEE International Conference on Image Processing, ICIP 2018, Athens, Greece, 18/10/7. https://doi.org/10.1109/ICIP.2018.8451330

Visual Preference Prediction for Enhanced Images on Ultra-High-Definition Display. / Ahn, Sewoong; Kim, Woojae; Kim, Jinwoo; Kim, Jaekyung; Lee, Sanghoon.

2018 IEEE International Conference on Image Processing, ICIP 2018 - Proceedings. IEEE Computer Society, 2018. p. 3548-3552 8451330 (Proceedings - International Conference on Image Processing, ICIP).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - 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.

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

Abstract

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