Holoscopic 3D imaging and display technology: Camera/ processing/ display

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonHoloscopic 3D imaging “Integral imaging” was first proposed by Lippmann in 1908. It has become an attractive technique for creating full colour 3D scene that exists in space. It promotes a single camera aperture for recording spatial information of a real scene and it uses a regularly spaced microlens arrays to simulate the principle of Fly’s eye technique, which creates physical duplicates of light field “true 3D-imaging technique”. While stereoscopic and multiview 3D imaging systems which simulate human eye technique are widely available in the commercial market, holoscopic 3D imaging technology is still in the research phase. The aim of this research is to investigate spatial resolution of holoscopic 3D imaging and display technology, which includes holoscopic 3D camera, processing and display. Smart microlens array architecture is proposed that doubles spatial resolution of holoscopic 3D camera horizontally by trading horizontal and vertical resolutions. In particular, it overcomes unbalanced pixel aspect ratio of unidirectional holoscopic 3D images. In addition, omnidirectional holoscopic 3D computer graphics rendering techniques are proposed that simplify the rendering complexity and facilitate holoscopic 3D content generation. Holoscopic 3D image stitching algorithm is proposed that widens overall viewing angle of holoscopic 3D camera aperture and pre-processing of holoscopic 3D image filters are proposed for spatial data alignment and 3D image data processing. In addition, Dynamic hyperlinker tool is developed that offers interactive holoscopic 3D video content search-ability and browse-ability. Novel pixel mapping techniques are proposed that improves spatial resolution and visual definition in space. For instance, 4D-DSPM enhances 3D pixels per inch from 44 3D-PPIs to 176 3D-PPIs horizontally and achieves spatial resolution of 1365 × 384 3D-Pixels whereas the traditional spatial resolution is 341 × 1536 3D-Pixels. In addition distributed pixel mapping is proposed that improves quality of holoscopic 3D scene in space by creating RGB-colour channel elemental images

Novel entropy coding and its application of the compression of 3D image and video signals

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe broadcast industry is moving future Digital Television towards Super high resolution TV (4k or 8k) and/or 3D TV. This ultimately will increase the demand on data rate and subsequently the demand for highly efficient codecs. One of the techniques that researchers found it one of the promising technologies in the industry in the next few years is 3D Integral Image and Video due to its simplicity and mimics the reality, independently on viewer aid, one of the challenges of the 3D Integral technology is to improve the compression algorithms to adequate the high resolution and exploit the advantages of the characteristics of this technology. The research scope of this thesis includes designing a novel coding for the 3D Integral image and video compression. Firstly to address the compression of 3D Integral imaging the research proposes novel entropy coding which will be implemented first on 2D traditional images content in order to compare it with the other traditional common standards then will be applied on 3D Integra image and video. This approach seeks to achieve high performance represented by high image quality and low bit rate in association with low computational complexity. Secondly, new algorithm will be proposed in an attempt to improve and develop the transform techniques performance, initially by using a new adaptive 3D-DCT algorithm then by proposing a new hybrid 3D DWT-DCT algorithm via exploiting the advantages of each technique and get rid of the artifact that each technique of them suffers from. Finally, the proposed entropy coding will be further implemented to the 3D integral video in association with another proposed algorithm that based on calculating the motion vector on the average viewpoint for each frame. This approach seeks to minimize the complexity and reduce the speed without affecting the Human Visual System (HVS) performance. Number of block matching techniques will be used to investigate the best block matching technique that is adequate for the new proposed 3D integral video algorithm

Adaptive 3D-DCT based compression algorithms for integral images

This paper proposes a novel mean adaptive 3DDCT algorithm for 3D content to achieve the optimal result by trading of quality and compression of 3D image. The proposed method enables users to adjust the compression rate according to application areas by applying small blocks to the more detailing area (non -stationary regions) and larger blocks to the background or less details area (homogenous regions) [1]. This proposed method “Mean Adaptive 3D-DCT” is applied on Holoscopic 3D images also known as Integral Images. In addition, the experiment results prove the method is applicable to any 3D content

Post-production of holoscopic 3D image

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University LondonHoloscopic 3D imaging also known as “Integral imaging” was first proposed by Lippmann in 1908. It facilitates a promising technique for creating full colour spatial image that exists in space. It promotes a single lens aperture for recording spatial images of a real scene, thus it offers omnidirectional motion parallax and true 3D depth, which is the fundamental feature for digital refocusing. While stereoscopic and multiview 3D imaging systems simulate human eye technique, holoscopic 3D imaging system mimics fly’s eye technique, in which viewpoints are orthographic projection. This system enables true 3D representation of a real scene in space, thus it offers richer spatial cues compared to stereoscopic 3D and multiview 3D systems. Focus has been the greatest challenge since the beginning of photography. It is becoming even more critical in film production where focus pullers are finding it difficult to get the right focus with camera resolution becoming increasingly higher. Holoscopic 3D imaging enables the user to carry out re/focusing in post-production. There have been three main types of digital refocusing methods namely Shift and Integration, full resolution, and full resolution with blind. However, these methods suffer from artifacts and unsatisfactory resolution in the final resulting image. For instance the artifacts are in the form of blocky and blurry pictures, due to unmatched boundaries. An upsampling method is proposed that improves the resolution of the resulting image of shift and integration approach. Sub-pixel adjustment of elemental images including “upsampling technique” with smart filters are proposed to reduce the artifacts, introduced by full resolution with blind method as well as to improve both image quality and resolution of the final rendered image. A novel 3D object extraction method is proposed that takes advantage of disparity, which is also applied to generate stereoscopic 3D images from holoscopic 3D image. Cross correlation matching algorithm is used to obtain the disparity map from the disparity information and the desirable object is then extracted. In addition, 3D image conversion algorithm is proposed for the generation of stereoscopic and multiview 3D images from both unidirectional and omnidirectional holoscopic 3D images, which facilitates 3D content reformation