Towards scalable and efficient full-reference omnidirectional image quality assessment

Yan, Jiebin, Liu, Zhiyong, Wang, Zhihua, Fang, Yuming and Liu, Hantao ORCID: https://orcid.org/0000-0003-4544-3481 2025. Towards scalable and efficient full-reference omnidirectional image quality assessment. IEEE Signal Processing Letters 10.1109/lsp.2025.3569458

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Abstract

Full-Reference (FR) image quality assessment (IQA) (FR-IQA) has achieved notable success due to its irreplaceable role in algorithm and system optimization; however, it has less been investigated in omnidirectional image quality assessment (OIQA). In this paper, we make an attempt to FR-OIQA considering the constraint of the computation budget, in which this issue is formulated as “quality perception from patch to sequence”, i.e., Intra-Patch Sequence degradation modeling and Inter-Patch Sequence similarity calculation (denoted by IPS2). Specifically, IPS2 directly accepts local patches from the omnidirectional image (OI) in the format of Equirectangular Projection as input, avoiding other preprocessing operations, such as scan-path prediction and projection transformation. Subsequently, IPS2 uses a deep feature extractor to capture patch quality and then sends the patch- wise quality maps to the cross-patch similarity (CPS) module, which explicitly models intra-patch sequence degradation and inter-patch sequence similarity via self-attention. Finally, a quality regressor is used to aggregate these features of the CPS module and predict the global quality of the OI. The experimental results on a large-scale OIQA database show that the proposed IPS2 outperforms most state-of-the-art methods in quality prediction accuracy while offering substantial reductions in computational cost and model size.

Item Type:	Article
Date Type:	Published Online
Status:	In Press
Schools:	Schools > Computer Science & Informatics
Additional Information:	License information from Publisher: LICENSE 1: URL: https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html, Start Date: 2025-01-01
Publisher:	Institute of Electrical and Electronics Engineers
ISSN:	1070-9908
Last Modified:	03 Jun 2025 12:15
URI:	https://orca.cardiff.ac.uk/id/eprint/178714

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