LFTSP: Traveling salesman problem for HEVCbased lightfield coding We studied a coding scheme where light field (LF) images (dense multiview images) are regarded as a sequence of temporal video frames and encoded with video codecs such as High Efficiency Video Coding (HEVC). An important issue with this scheme is how to determine the frame order of the LF images. We propose a method to find the optimum frame order through a formulation of the traveling salesman problem (TSP). Under the assumption that video codecs are more effective with temporally smooth videos, our method, named LFTSP, defines frametoframe distances for each image pairs in an LF, and attempted to find the shortest route that visits all frames. Experiments showed that our method achieved an overall better ratedistortion performance than several previous methods.

A low complexity WynerZiv coding solution for Light Field image transmission and storage Compressing Light Field (LF) imaging data is a challenging but very important task for both LF image transmission and storage applications. In this paper, we propose a novel coding solution for LF images using the wellknown WynerZiv (WZ) information theorem. First, the LF image is decomposed into a fourthdimensional LF(4DLF) data format. Using a spiral scanning procedure, a pseudosequence of 4DLF is generated. This sequence is then compressed in a distributed coding manner as specified in the WZ theorem. Secondly, a novel adaptive frame skipping algorithm is introduced to further explore the high correlation between 4DLF pseudo sequences. Experimental results show that the proposed LF image compression solution is able to achieve a significant performance improvement with respect to the standard, notably around 54% bitrate saving when compared with the standard High Efficiency Video Coding (HEVC) Intra benchmark while requiring less computational complexity.