3D Video Coding for Embedded Devices: Energy Efficient by Bruno Zatt, Muhammad Shafique, Sergio Bampi, Jörg Henkel

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

This e-book indicates readers how you can boost energy-efficient algorithms and architectures to let high-definition 3D video coding on resource-constrained embedded units. clients of the Multiview Video Coding (MVC) common face the problem of exploiting its 3D video-specific coding instruments for expanding compression potency on the expense of accelerating computational complexity and, accordingly, the strength intake. This e-book permits readers to lessen the multiview video coding power intake via together contemplating the algorithmic and architectural degrees. insurance contains an creation to 3D movies and an in depth dialogue of the present state of the art 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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This technique is extensively used in the literature and in the solutions proposed along this monograph. 1 Video Memories On-chip memories are becoming dominant part of current systems, mainly for ­signal processing systems. In the scope of video coding, the video memory represents the main on-chip memory component responsible for storing frames used as reference to encode other frames. In the current literature are found solutions specific for video/frame memories or generic solutions for any video/image processing tasks.

For the dependent views (all views except the base one), the inter-view prediction or disparity estimation (DE) is also available (Merkle et al. 2007). 9 Four prediction directions for intra-prediction 16 × 16 extension searches for the best matching candidate in the frames belonging to previous encoded views (left, right, up, or down, depending on the cameras arrangement and view prediction structure). 1. The output of the prediction phase is a large set of prediction candidates. Among all different block sizes for intra-prediction, inter-frame prediction, and inter-view prediction, the best prediction mode must be selected by the mode decision (MD) in order to provide the optimal rate–distortion (RD) trade-off (Richardson 2010).

Additionally, the new disparity estimation adds a set of coding possibilities as large as the motion estimation possibilities. The mode decision (MD) module is the responsible to deal with this large optimization space. a. J cost). The objective is to evaluate the coding modes and to find the one that minimizes the RDCost to obtain the best coding relation between rate and distortion. 3) presents the J function where c and r represent the current original MB and the reconstructed one, MODE is the prediction mode used, and QP is the quantization parameter.

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