Light Field Transmission Fusing Image Super-Resolution and Selective Quality Patterns

Wei Zheng, Zongyou Yu, Xiaoming Chen, Zeke Zexi Hu, Yuk Ying Chung

Abstract: Light field imaging has notably advanced immersive experiences and virtual reality applications. However, this progress is accompanied by a considerable increase in data volume, posing challenges in storage and transmission efficiency. In this study, we propose a novel framework for light field image storage and transmission. The approach leverages the image super-resolution and pseudo video coding techniques to process LF images as video sequences. Mean-while, a series of selective transmission patterns tailored to human visual perception are developed. The experimental results show that the approach optimizes the transmission efficiency while preserving similar LF image quality.