Blind Image Quality Assessment Based on Visuo-Spatial Series Statistics

Abstract

Existing blind image quality assessment (BIQA) methods based on statistics attach limited attention to the relative position of pixels. Features in these BIQA methods are too flimsy to characterize quite a few distortions with strong locality or complexity. However, psychological studies have shown that according to the relative position within visual field, the cognitive system generates visuo-spatial serial memory used for cognitive tasks, e.g., subjective image quality assessment. Inspired by the visuo-spatial series generated by human visual system (HVS), we propose a BIQA method based on imitation Visuo-spatial Series Statistics (VSS). The proposed method simulates visual system to construct visuo-spatial series based on the relative position of pixels, and use statistical features of visuo-spatial series to predict image quality. Extensive experiments demonstrate the proposed method has a superior performance compared to the state-of-the-art BIQA methods.