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SWVFS: a saliency weighted visual feature similarity metric for image quality assessment

机译:SWVFS:用于图像质量评估的显着性加权视觉特征相似性度量

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摘要

In this paper, a saliency weighted visual feature similarity (SWVFS) metric is proposed for full reference image quality assessment (IQA). Instead of traditional spatial pooling strategies, a visual saliency-based approach is employed for better compliance with properties of the human visual system, where the saliency allocation is closely related to the activity of posterior parietal cortex and the pluvial nuclei of the thalamus. Assuming that the saliency map actually represents the contribution of locally computed visual distortions to the overall image quality, the gradient similarity and the textural congruency are merged into the final image quality indicator. The gradient and texture comparison play complementary roles in characterizing the local image distortion. Extensive experiments conducted on seven publicly available image databases show that the performance of SWVFS is competitive with the state-of-the-art IQA algorithms.
机译:在本文中,提出了显着性加权视觉特征相似度(SWVFS)度量标准用于全参考图像质量评估(IQA)。代替传统的空间汇集策略,而是采用基于视觉显着性的方法来更好地符合人类视觉系统的属性,其中显着性分配与后顶叶皮层和丘脑的小核的活动密切相关。假设显着性图实际上代表了本地计算的视觉失真对整体图像质量的贡献,则将梯度相似度和纹理一致性纳入最终的图像质量指标。梯度和纹理比较在表征局部图像失真方面起到补充作用。在七个公开可用的图像数据库上进行的大量实验表明,SWVFS的性能与最新的IQA算法相比具有竞争力。

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