Evaluation of a combined preprocessing and H.264compression scheme for 3D integral images To provide sufficient 3Ddepth fidelity, integral imaging (II) requires an increase in spatial resolution of several orders of magnitude from todayu0027s 2D images. We have recently proposed a preprocessing and compression scheme for still IIframes based on forming a pseudo video sequence (PVS) from sub images (SI), which is later coded using the H.264MPEG4 AVC video coding standard. The scheme has shown good performance on a set of reference images. In this paper we first investigate and present how five different ways to select the SIs when forming the PVS affect the schemes compression efficiency. We also study how the IIframe structure relates to the performance of a PVS coding scheme. Finally we examine the nature of the coding artifacts which are specific to the evaluated PVSschemes. We can conclude that for all except the most complex reference image, all evaluated SI selection orders significantly outperforms JPEG 2000 where compression ratios of up to 342:1, while still keeping PSNR u003e 30 dB, is achieved. We can also confirm that when selecting PVSscheme, the scheme which results in a higher PVSpicture resolution should be preferred to maximize compression efficiency. Our study of the coded IIframes also indicates that the SIbased PVS, contrary to other PVS schemes, tends to distribute its coding artifacts more homogenously over all 3Dscene depths.

A Novel Randomize Hierarchical Extension of MVHEVC for Improved Light Field Compression This paper presents a novel scheme for light field compression based on a randomize hierarchical multiview extension of high efficiency video coding (dubbed as RHMVHEVC). Specifically, a light field data are arranged as a multiple pseudotemporal video sequences which are efficiently compressed with MVHEVC encoder, following an integrated random coding technique and hierarchical prediction scheme. The critical advantage of proposed RHMVHEVC scheme is that it utilizes not just a temporal and interview prediction, but efficiently exploits the strong intrinsic similarities within each subaperture image and among neighboring subaperture images in both horizontal and vertical directions. Experimental results consistently outperform the stateoftheart compression methods on benchmark ICME 2016 and ICIP 2017 grand challenge data sets. It achieves an average up to 33.803% BDrate reduction and 1.7978 dB BDPSNR improvement compared with an advanced JEM video encoder, and an average 20.4156% BDrate reduction and 2.0644 dB BDPSNR improvement compared with a latest imagebased JEManchor coding scheme.