No-reference stereoscopic image quality assessment guided by visual hierarchical structure and binocular effects.

Abstract

Stereoscopic image quality assessment (SIQA) is an essential technique for modern 3D image and video processing systems serving as performance evaluators and monitors. However, the study on SIQA remains immature due to the complexity of the human visual system (HVS) and binocular effects that binocular vision brings about. To overcome the difficulties, a novel method is proposed that extracts and quantifies image quality-aware features related to cortex areas in charge of visual quality perception, rather than attempting to rigorously simulate the biological processing in HVS, so that the predicting accuracy is preserved while the computational complexity remains moderate. Meanwhile, binocular effects including binocular rivalry and visual discomfort are taken into consideration. Moreover, the proposed method can be operated completely without the assistance of reference images, indicating its wide practical usages. Compared to state-of-the-art works, our method shows evident superiority in terms of effectiveness and robustness.