Dual-stream interactive networks for no-reference stereoscopic image quality assessment

Zhou, Wei, Chen, Zhibo and Li, Weiping 2019. Dual-stream interactive networks for no-reference stereoscopic image quality assessment. IEEE Transactions on Image Processing 28 (8) , pp. 3946-3958. 10.1109/TIP.2019.2902831

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Abstract

The goal of objective stereoscopic image quality assessment (SIQA) is to predict the human perceptual quality of stereoscopic/3D images automatically and accurately. Compared with traditional 2D image quality assessment, the quality assessment of stereoscopic images is more challenging because of complex binocular vision mechanisms and multiple quality dimensions. In this paper, inspired by the hierarchical dual-stream interactive nature of the human visual system, we propose a stereoscopic image quality assessment network (StereoQA-Net) for no-reference stereoscopic image quality assessment. The proposed StereoQA-Net is an end-to-end dual-stream interactive network containing left and right view sub-networks, where the interaction of the two sub-networks exists in multiple layers. We evaluate our method on the LIVE stereoscopic image quality databases. The experimental results show that our proposed StereoQA-Net outperforms state-of-the-art algorithms on both symmetrically and asymmetrically distorted stereoscopic image pairs of various distortion types. In a more general case, the proposed StereoQA-Net can effectively predict the perceptual quality of local regions. In addition, cross-dataset experiments also demonstrate the generalization ability of our algorithm.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	Institute of Electrical and Electronics Engineers
ISSN:	1057-7149
Date of Acceptance:	25 February 2019
Last Modified:	23 Aug 2023 15:30
URI:	https://orca.cardiff.ac.uk/id/eprint/161692

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