An efficient compression scheme for the multi-camera light field image
Current light field compression techniques lack robustness to handle both rate-distortion optimized motion compensation as well as latency during the encoding and decoding process. This paper focuses on a contribution approach that uses advanced frame prediction with affine and translational motion models and optimized view prediction structures. This method allows a significant compression performance gain over the current state of art of hierarchical temporal coding by 13.9%. The proposed method introduces an optimized encoding order that takes advantage of each group of pictures structure in order to leverage the dense perspective model of light field imagery. Both a global perspective model and a local affine model can be combined to show substantial distortion reduction at low processor costs. This contribution approach leads to an efficient and robust compression scheme for light field datasets.