Three-dimensional technology, more commonly referred to as 3D technology, has revolutionised many fields including entertainment, medicine, and communications to name a few. In addition to 3D films, games, and sports channels, 3D perception has made tele-medicine a reality. By the year 2015, 30% of the all HD panels at home will be 3D enabled, predicted by consumer electronics manufacturers. Stereoscopic cameras, a comparatively mature technology compared to other 3D systems, are now being used by ordinary citizens to produce 3D content and share at a click of a button just like they do with the 2D counterparts via sites like YouTube. But technical challenges still exist, including with autostereoscopic multiview displays. 3D content requires many complex considerations--including how to represent it, and deciphering what is the best compression format--when considering transmission or storage, because of its increased amount of data. Any decision must be taken in the light of the available bandwidth or storage capacity, quality and user expectations. Free viewpoint navigation also remains partly unsolved. The most pressing issue getting in the way of widespread uptake of consumer 3D systems is the ability to deliver 3D content to heterogeneous consumer displays over the heterogeneous networks. Optimising 3D video communication solutions must consider the entire pipeline, starting with optimisation at the video source to the end display and transmission optimisation. Multi-view offers the most compelling solution for 3D videos with motion parallax and freedom from wearing headgear for 3D video perception. Optimising multi-view video for delivery and display could increase the demand for true 3D in the consumer market. This thesis focuses on an end-to-end quality optimisation in 3D video communication/transmission, offering solutions for optimisation at the compression, transmission, and decoder levels.

Emerging 3-D applications and 3-D display technologies raise some transmission problems of the next-generation multimedia data. Multi-view Video Coding (MVC) is one of the challenging topics in this area, that is on its road for standardization via ISO MPEG. In this thesis, a 3-D geometry-based MVC approach is proposed and analyzed in terms of its compression performance. For this purpose, the overall study is partitioned into three preceding parts. The first step is dense depth estimation of a view from a fully calibrated multi-view set. The calibration information and smoothness assumptions are utilized for determining dense correspondences via a Markov Random Field (MRF) model, which is solved by Belief Propagation (BP) method. In the second part, the estimated dense depth maps are utilized for generating (predicting) arbitrary (other camera) views of a scene, that is known as novel view generation. A 3-D warping algorithm, which is followed by an occlusion-compatible hole-filling process, is implemented for this aim. In order to suppress the occlusion artifacts, an intermediate novel view generation method, which fuses two novel views generated from different source views, is developed. Finally, for the last part, dense depth estimation and intermediate novel view generation tools are utilized in the proposed H.264-based MVC scheme for the removal of the spatial redundancies between different views. The performance of the proposed approach is compared against the simulcast coding and a recent MVC proposal, which is expected to be the standard recommendation for MPEG in the near future. These results show that the geometric approaches in MVC can still be utilized, especially in certain 3-D applications, in addition to conventional temporal motion compensation techniques, although the rate-distortion performances of geometry-free approaches are quite superior.

In recent years, 3D camera products and prototypes based on Integral imaging (II) technique have gradually emerged and gained broad attention. II is a method that spatially samples the natural light (light field) of a scene, usually using a microlens array or a camera array and records the light field using a high resolution 2D image sensor. The large amount of data generated by II and the redundancy it contains together lead to the need for an efficient compression scheme. During recent years, the compression of 3D integral images has been widely researched. Nevertheless, there have not been many approaches proposed regarding the compression of integral videos (IVs). The objective of the thesis is to investigate efficient coding methods for integral videos. The integral video frames used are captured by the first consumer used light field camera Lytro. One of the coding methods is to encode the video data directly by an H.265/HEVC encoder. In other coding schemes the integral video is first converted to an array of sub-videos with different view perspectives. The sub-videos are then encoded either independently or following a specific reference picture pattern which uses a MVHEVC encoder. In this way the redundancy between the multi-view videos is utilized instead of the original elemental images. Moreover, by varying the pattern of the subvideo input array and the number of inter-layer reference pictures, the coding performance can be further improved. Considering the intrinsic properties of the input video sequences, a QP-per-layer scheme is also proposed in this thesis. Though more studies would be required regarding time and complexity constraints for real-time applications as well as dramatic increase of number of views, the methods proposed inthis thesis prove to be an efficient compression for integral videos.