Performance analysis on prediction structure for multi-view-based light field video coding

Abstract

Light Field (LF) image/video data provides both spatial and angular information of scene but at the cost of tremendous data volume for their storage and transmission. At the moment, the MPEG Multi-view Video Coding (MVC) is one of promising compression solutions for LF video data, so it deserves much investigation for better prediction structure to effectively reduce the redundancy in LF video data. Several prediction structures have been investigated but only with limited experimental evaluations due to lack of dataset and non-identical testing configurations. This practical problem can be mitigated now by availability of new datasets and common test condition recently proposed by MPEG. As the first step for designing a good compression method for LF video data, in this paper, we evaluate the performance of existing prediction structures for MVC-based LF video coding methods following the MPEG common test condition and its dataset. © 2020 SPIE CCC.