SOURCE-LINKED INTELLIGENCE
Blind Stereoscopic Omnidirectional Image Quality Assessment Using Predictive Coding Hierarchy
Stereoscopic omnidirectional images (SOIs) have provided users with newly immersive quality of experience in virtual reality environments. However, developing efficient and accurate perceptual quality assessment metrics for SOIs remains challenging due to many factors such as freely changeable field of views and binocular vision. In this paper, based on the characteristics of the human visual system (HVS), we propose a Predictive Coding Hierarchy-inspired metric (PCH) for blind/no-reference stereoscopic omnidirectional image quality assessment. Motivated by the viewing process of SOIs, the pro
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-28T19:06:04.000Z
First collected: 2026-09-21T08:02:06.831Z. This is not the publication date.