By Bruno Zatt, Muhammad Shafique, Sergio Bampi, Jörg Henkel (auth.)
This publication exhibits readers the right way to improve 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, therefore, the power intake. This ebook permits readers to minimize the multiview video coding strength intake via together contemplating the algorithmic and architectural degrees. assurance comprises an advent 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
Chapter 7 depicts the conclusions of this work and points to future research opportunities and challenges related to the next generations of 3D multimedia processing and 3D-video coding. Additional tools and simulation environments are presented in the appendixes. Appendix A presents the MVC reference software, the JMVC, and details the modifications applied to the JMVC in order to enable software experimentation. The in-house developed Memory Access Analyzer tool and its graphic interface is presented in Appendix B.
2009), the proposed systems handle an ASIC HW video codec, audio codecs, VLIW processors, MIPS host CPU, DSP, and other HW accelerators. The system proposed by Kondo et al. (2009) is composed of two specific accelerators (video decoder and descriptor), one general accelerator (MX), three RISC CPUs, and caches. Woo et al. (2008) describe a 195 mW mobile multimedia SoC with ARM 9, AVC/MPEG decoder, JPEG codec, fully programmable 3D engine, and multiple peripheral interfaces. The heterogeneous multicores approach is the most used in the current set-top boxes, digital TV decoders, and smart mobile devices.
8, where modes 0 and 1 apply a simple copy of the neighboring blocks and modes 3–8 perform a weighted interpolation according to the prediction direction. Mode 2 (DC) replicates the average of the neighboring samples to the entire block. Each one of the 16 blocks inside the MB may use different prediction directions in order to find the best prediction. The intra-prediction can also be performed using the 16 × 16 block size. However, in this mode the number of prediction directions is restricted.
3D Video Coding for Embedded Devices: Energy Efficient Algorithms and Architectures by Bruno Zatt, Muhammad Shafique, Sergio Bampi, Jörg Henkel (auth.)