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Video primer: HDR, 3D processing challenges

Posted: 05 Jul 2011 ?? ?Print Version ?Bookmark and Share

Keywords:video processing? 3D? video systems?

3D capture technologies widely employ stereoscopic techniques of obtaining stereo pairs using a two-view setup. Cameras are mounted side by side, with a separation typically equal to the distance between a person's pupils. Exploiting the idea that views from distant objects arrive at each eye along the same line of sight, while those from closer objects arrive at different angles, realistic 3D images can be obtained from the stereoscopic image pair.

In this report
??HDR, 3D challenges
??Compressing HDR, 3D videos
??HDR, 3D video display
??Searching for video content

Multi-view technology, an alternative to stereoscopy, captures 3D scenes by recording several independent video streams using an array of cameras. Additionally, plenoptic cameras, which capture the light field of a scene, can also be used for multiview capture with a single main lens. The resulting views can then either be shown on multiview displays or stored for further processing.

Susanto Rahardja

Susanto Rahardja: Advanced predictive techniques can be used during decompression of videos to preserve high fidelity.

Compressing HDR, 3D videos
Transmitting HDR and 3D videos as they are captured imposes impractical bandwidth requirements on transmission systems. For example, an uncompressed 2-megapixels 2D video captured at 60 frames per second (fps) would require nearly 2Gbpstwice the highest bandwidth currently available on OpenNet. For HDR video, each pixel can be represented by a 96bit floating point number; therefore, an uncompressed 2-megapixels 2D HDR video at 60fps would require nearly 12Gbps. Captured video data must thus be efficiently compressed to ensure practical transmission, as investigated in the field of video coding.

Video compression hinges primarily on two intuitive concepts. First, the notion that successive raw video frames are highly similar implies that a huge amount of redundant information exists between them. Next, redundancies exist even within frames themselves, as depicted by real life scenes in which there is a high likelihood that pixels in the vicinity of one another have similar values. Removal of these redundancies by means of advanced coding techniques give rise to video formats which greatly reduce the amount of data needed for transmission and storage. Moreover, advanced predictive techniques can be used during decompression of videos to preserve high video fidelity despite substantial compression.

Research on improving the compression efficiency of 2D video coding has been extensively conducted in the last few decades. As a measure of performance, the amount of bandwidth required to transmit the same video quality at the same resolution has gradually decreased. Much of this is attributed to the progressive development of video coding standards such as MPEG-1, MPEG-2, MPEG-4 and H.264/AVC, adhered to so that interoperability between different devices is guaranteed. For example, MPEG-2 is used to code videos in the DVD format, ensuring that any DVD can be viewed on any standard-compliant DVD players.

One of the state-of-the-art video coding standards widely used today is H.264/AVC. The development of this standard, which included technical contributions by the Institute for Infocomm Research (I2R), culminated in its endorsement in 2003. Thereafter, the standard quickly gained global acceptance for deployment in numerous consumer devices as well as internet videos. Despite enjoying such achievement, I2R remains devoted in its endeavour to further develop and commercialize even more impactful industry solutions based on this noteworthy contribution.

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