No-Reference Stereoscopic Image Quality Assessment Based on Binocular Visual Saliency Weighting

Xie, Yurui; Chen, Lei; Ben, Xianye; Yang, Mo

doi:10.1145/3582649.3582650

Proceedings of the 2023 6th International Conference on Image and Graphics Processing 2023

DOI: 10.1145/3582649.3582650

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No-Reference Stereoscopic Image Quality Assessment Based on Binocular Visual Saliency Weighting

Yurui Xie

Lei Chen

Xianye Ben

et al.

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2024

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Cited by 1 publication

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Saliency and Depth-Aware Full Reference 360-Degree Image Quality Assessment

Wei,

Huang,

Fang

et al. 2024

Int. J. Patt. Recogn. Artif. Intell.

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With the widespread adoption of virtual reality and 360-degree video, there is a pressing need for objective metrics to assess quality in this immersive panoramic format reliably. However, existing image quality assessment models developed for traditional fixed-viewpoint content do not fully consider the specific perceptual issues involved in 360-degree viewing. This paper proposes a 360-degree image full-reference quality assessment (FR-IQA) methodology based on a multi-channel architecture. The proposed 360-degree FR-IQA method further optimizes and identifies the distorted image quality using two easily obtained useful saliency and depth-aware image features. The convolutional neural network (CNN) is designed for training. Furthermore, the proposed method accounts for predicting user viewing behaviors within 360-degree images, which will further benefit the multi-channel CNN architecture and enable the weighted average pooling of the predicted FR-IQA scores. The performance is evaluated on publicly available databases to demonstrate the advantages brought by the proposed multi-channel model in performance evaluation and cross-database evaluation experiments, where it outperforms other state-of-the-art ones. Moreover, an ablation study exhibits good generalization ability and robustness.

show abstract

Saliency and Depth-Aware Full Reference 360-Degree Image Quality Assessment

Wei,

Huang,

Fang

et al. 2024

Int. J. Patt. Recogn. Artif. Intell.

View full text Add to dashboard Cite

show abstract

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No-Reference Stereoscopic Image Quality Assessment Based on Binocular Visual Saliency Weighting

Cited by 1 publication

References 18 publications

Saliency and Depth-Aware Full Reference 360-Degree Image Quality Assessment

Saliency and Depth-Aware Full Reference 360-Degree Image Quality Assessment

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