Problem
Research questions and friction points this paper is trying to address.
Stereoscopic Omnidirectional Images
Quality Assessment
Human Visual System
Blind Stereoscopic Omnidirectional Image Quality Assessment Using Predictive Coding Hierarchy
🤖 AI Summary
本文针对立体全景图像质量评估难题，提出基于预测编码层次的PCH方法，结合局部和全局感知模块及视觉质量回归器，实现高效准确的质量评价。
📝 Abstract
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 proposed PCH includes a local cyclopean perception module, a global predictive perception module, and a visual quality regressor. First, observers browse different spherical sceneries from viewports, and aggregate the local visual information to infer the perceptual quality of SOIs. Therefore, we extract various viewports, followed by cyclopean conversion and saliency detection to approach the perception and attention of the human brain. After the local aggregation, viewers then infer the global scene in their minds. Based on the binocular mechanism, we fuse left and right views to perform predictive coding hierarchy modelling. Finally, the visual quality regressor is exploited to obtain the ultimate quality score related to both local and global perceptual cues. Extensive experiments demonstrate that the proposed PCH achieves competitive and consistently improved performance compared with state-of-the-art quality assessment methods.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Predictive Coding Hierarchy
Stereoscopic Omnidirectional Images
Human Visual System
No-Reference Quality Assessment
🔎 Similar Papers
No similar papers found.
