Novel projection schemes for graph-based Light Field coding
This work addresses a domain-specific problem in Light Field compression for applications like 3D imaging and virtual reality, representing an incremental improvement over prior graph-based approaches.
The paper tackles the problem of graph-based Light Field coding's sensitivity to inaccurate disparity information, which causes errors in super-rays projection. The authors introduce two novel projection schemes that reduce disparity errors and computational time, achieving enhanced projection quality and improved rate-distortion performance compared to existing methods.
In Light Field compression, graph-based coding is powerful to exploit signal redundancy along irregular shapes and obtains good energy compaction. However, apart from high time complexity to process high dimensional graphs, their graph construction method is highly sensitive to the accuracy of disparity information between viewpoints. In real world Light Field or synthetic Light Field generated by computer software, the use of disparity information for super-rays projection might suffer from inaccuracy due to vignetting effect and large disparity between views in the two types of Light Fields respectively. This paper introduces two novel projection schemes resulting in less error in disparity information, in which one projection scheme can also significantly reduce time computation for both encoder and decoder. Experimental results show projection quality of super-pixels across views can be considerably enhanced using the proposals, along with rate-distortion performance when compared against original projection scheme and HEVC-based or JPEG Pleno-based coding approaches.