SIFT-based adaptive prediction structure for light field compression

Wei Zhang, Dong Liu, Zhiwei Xiong, Jizheng Xu

Abstract: A light field consists of multiple views of a scene, which can be arranged and encoded like a pseudo sequence. Since the correlations between views are not equal and indeed content dependent, a well-constructed coding order and adaptive prediction structure will improve performance. In this paper, we propose an adaptive prediction structure for light field compression. While the coding order is inherited from the 2-D hierarchical coding order, the prediction structure is determined by the differences between scale-invariant feature transform (SIFT) descriptors of the views. Experimental results show that the proposed method leads to on average 5.71% BD-rate reduction compared with fixed prediction structure.