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

Abstract

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.

Keywords

image quality assessment / gradient / texture / visual saliency

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