Statler College of Engineering and Mining Resources
Lane Department of Computer Science and Electrical Engineering
The human visual system (HVS) plays an important role in stereo image quality perception. Therefore, it has aroused many people’s interest in how to take advantage of the knowledge of the visual perception in image quality assessment models. This paper proposes a full-reference metric for quality assessment of stereoscopic images based on the binocular difference channel and binocular summation channel. For a stereo pair, the binocular summation map and binocular difference map are computed first by adding and subtracting the left image and right image. Then the binocular summation is decoupled into two parts, namely additive impairments and detail losses. The quality of binocular summation is obtained as the adaptive combination of the quality of detail losses and additive impairments. The quality of binocular summation is computed by using the Contrast Sensitivity Function (CSF) and weighted multi-scale (MS-SSIM). Finally, the quality of binocular summation and binocular difference is integrated into an overall quality index. The experimental results indicate that compared with existing metrics, the proposed metric is highly consistent with the subjective quality assessment and is a robust measure. The result have also indirectly proved hypothesis of the existence of binocular summation and binocular difference channels.
Digital Commons Citation
Yang, Jiachen; Lin, Yancong; Gao, Zhiqun; Lv, Zhihan; Wei, Wei; and Song, Houbing, "Quality Index for Stereoscopic Images by Separately Evaluating Adding and Subtracting" (2015). Faculty & Staff Scholarship. 2103.
Yang J, Lin Y, Gao Z, Lv Z, Wei W, Song H (2015) Quality Index for Stereoscopic Images by Separately Evaluating Adding and Subtracting. PLoS ONE 10(12): e0145800. https://doi.org/10.1371/journal.pone.0145800