Read e-book online 3D Video Coding for Embedded Devices: Energy Efficient PDF

By Bruno Zatt, Muhammad Shafique, Sergio Bampi, Jörg Henkel (auth.)

ISBN-10: 1461467586

ISBN-13: 9781461467588

ISBN-10: 1461467594

ISBN-13: 9781461467595

This booklet exhibits readers the right way to increase energy-efficient algorithms and architectures to let high-definition 3D video coding on resource-constrained embedded units. clients of the Multiview Video Coding (MVC) typical face the problem of exploiting its 3D video-specific coding instruments for expanding compression potency on the rate of accelerating computational complexity and, for that reason, the power intake. This ebook permits readers to minimize the multiview video coding strength intake via together contemplating the algorithmic and architectural degrees. insurance comprises an creation to 3D movies and an intensive dialogue of the present cutting-edge of 3D video coding, in addition to energy-efficient algorithms for 3D video coding and energy-efficient structure for 3D video coding.

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Extra info for 3D Video Coding for Embedded Devices: Energy Efficient Algorithms and Architectures

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It is important to understand that PSNR is currently the widely most accepted objective video quality metric. 85 × 2(QP −12 )/3. 4) Although the algorithm to find the mode that minimizes the RDCost is not defined by the standard, the MVC reference software JMVC implements an exhaustive search by completely encoding all possible coding modes and selecting the best mode. It is known as rate–distortion optimized mode decision (RDO-MD) also referred as Full RDO or Exhaustive RDO. The RDO-MD guarantees the optimal MB encoding but drastically increases the encoder computational effort and makes the same approach for real-time MVC encoding unfeasible for the current technology.

In order to obtain an accurate evaluation of the available correlation, we have carried out an extensive analysis of multiview videos. For this analysis we have used different multiview video sequences following the MVC test recommendation by Joint Video Team (JVT) (Su et al. 2006). 7. Our analysis, discussed in Sect. 1, constitutes an in-depth exploration of coding mode distribution, video statistics, motion and disparity vectors, coding mode, and RDCost correlation in the so-called 3D-neighborhood (spatial, temporal, and view neighborhood).

According to the prediction and the target bitrate (amount of bits per second used to encode the video), an adequate QP is selected. As QP grows higher, more residual data are quantized (video details lost) and more quality losses are inserted. The actual generated bitrate and the video quality may be used as feedback for the RC unit in order to update the prediction and QP definition. The QP adaptation may be performed in distinct actuation levels. 15. It is possible to combine GOP level and frame level, and based on this observation, for simplicity, they are jointly discussed in this monograph.

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3D Video Coding for Embedded Devices: Energy Efficient Algorithms and Architectures by Bruno Zatt, Muhammad Shafique, Sergio Bampi, Jörg Henkel (auth.)

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