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.

On The Implication Of Light Field Compression On PostProcessing Algorithms A Light Field (LF) can be parameterized as an assembly of beams in empty space (e.g. direction and intersection with plane with no starting point). As LFs are a 4D representation of a scene including both color intensity and angular information unlike the conventional 2D images which contain only color information, it is essential to adapt 4D LFs to be handled by file formats designed for assemblies of 2D images. This paper proposes adapting LFs to current production workflows, allowing interoperability between imaging applications and devices. OpenEXR is a standard that provides substantial advantages over conventional multiplexed video files or images, for special effects or in media environment. It can store many data channels, which allows for maximum flexibility in compositing. We have investigated the possibilities to store LFs in this format and also evaluated the different EXR compressions (lossy and lossless). In addition to this, a standard format such as JPEG XT which offers support for high bit depth image representation is also evaluated and compared.