TL;DRAbstract
The recently developed H.264 / MPEG-4 Part 10 video compression standard achieves better video compression efficiency than previous video compression standards at the expense of increased computational complexity and power consumption. Multiple reference frame (MRF) Motion Estimation (ME) is the most computationally intensive and power consuming part of H.264 video encoders. Therefore, in this thesis, we designed and implemented a reconfigurable baseline H.264 video encoder hardware for real-time portable applications in which the number of reference frames used for MRF ME can be configured based on the application requirements in order to trade-off video coding efficiency and power consumption. The proposed H.264 video encoder hardware is based on an existing low cost H.264 intra frame coder hardware and it includes new reconfigurable MRF ME, mode decision and motion compensation hardware. We first proposed a low complexity H.264 MRF ME algorithm and a low energy adaptive hardware for
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The recently developed H.264 / MPEG-4 Part 10 video compression standard achieves better video compression efficiency than previous video compression standards at the expense of increased computational complexity and power consumption. Multiple reference frame (MRF) Motion Estimation (ME) is the most computationally intensive and power consuming part of H.264 video encoders. Therefore, in this thesis, we designed and implemented a reconfigurable baseline H.264 video encoder hardware for real-time portable applications in which the number of reference frames used for MRF ME can be configured based on the application requirements in order to trade-off video coding efficiency and power consumption. The proposed H.264 video encoder hardware is based on an existing low cost H.264 intra frame coder hardware and it includes new reconfigurable MRF ME, mode decision and motion compensation hardware. We first proposed a low complexity H.264 MRF ME algorithm and a low energy adaptive hardware for
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