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http://dx.doi.org/10.5909/JBE.2019.24.5.827

A New Hybrid Weight Pooling Method for Object Image Quality Assessment with Luminance Adaptation Effect and Visual Saliency Effect  

Shahab Uddin, A.F.M. (Dept. of Computer Science and Engineering, Kyung Hee University)
Kim, Donghyun (Agency for Defense Development)
Choi, Jeung Won (Agency for Defense Development)
Chung, TaeChoong (Dept. of Computer Science and Engineering, Kyung Hee University)
Bae, Sung-Ho (Dept. of Computer Science and Engineering, Kyung Hee University)
Publication Information
Journal of Broadcast Engineering / v.24, no.5, 2019 , pp. 827-835 More about this Journal
Abstract
In the pooling stage of a full reference image quality assessment (FR-IQA) technique, the global perceived quality for any distorted image is usually measured from the quality of its local image patches. But all the image patches do not have equal contribution when estimating the overall visual quality since the degree of degradation on those patches depends on various considerations i.e., types of the patches, types of the distortions, distortion sensitivities of the patches, saliency score of the patches, etc. As a result, weighted pooling strategy comes into account and different weighting mechanisms are used by the existing FR-IQA methods. This paper performs a thorough analysis and proposes a novel weighting function by considering the luminance adaptation as well as the visual saliency effect to offer more appropriate local weights, which can be adopted in the existing FR-IQA frameworks to improve their prediction accuracy. The extended experimental results show the effectiveness of the proposed weighting function.
Keywords
IQA; Hybrid Weight Pooling; Luminance Adaptation; Visual Saliency;
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