2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

Imaging Without Borders

2021 IEEE International Conference on Image Processing

19-22 September 2021 • Anchorage, Alaska, USA

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Paper Detail

Paper IDSMR-2.4
Paper Title A METRIC FOR QUANTIFYING IMAGE QUALITY INDUCED SALIENCY VARIATION
Authors Pengfei Guo, Zhongkai University of Agriculture and Engineering, China; Xin Zhao, Cardiff University, United Kingdom; Delu Zeng, South China University of Technology, China; Hantao Liu, Cardiff University, United Kingdom
SessionSMR-2: Perception and Quality Models
LocationArea F
Session Time:Wednesday, 22 September, 14:30 - 16:00
Presentation Time:Wednesday, 22 September, 14:30 - 16:00
Presentation Poster
Topic Image and Video Sensing, Modeling, and Representation: Perception and quality models for images & video
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Abstract Saliency plays an important role in the area of image quality assessment. Image distortions cause shift/redistribution of saliency from its original places. There is a need to be able to measure such distortion-included saliency variation (DSV), so that the use of saliency can be optimised for automated image quality assessment. Effort has been made in our previous study to build a benchmark for the measurement of DSV through subjective testing. In this paper, we demonstrate that exiting similarity measures are unhelpful for the quantification of DSV. Thus, we propose a new metric for DSV combining local and global measures using convex optimization. The experimental results show that our proposed metric can accurately quantify saliency variation.