TY - GEN
T1 - EnBudget
T2 - Design, Automation and Test in Europe Conference and Exhibition, DATE 2010
AU - Shafique, Muhammad
AU - Bauer, Lars
AU - Henkel, Jörg
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - The limited energy resources in portable multimedia devices require the reduction of encoding complexity. The complex Motion Estimation (ME) scheme of H.264/MPEG-4 AVC accounts for a major part of the encoder energy [3]. In this paper we present a Run-Time Adaptive Predictive Energy Budgeting (enBudget) scheme for energy-aware ME that predicts the energy budget for different video frames and different Macroblocks (MBs) in an adaptive manner considering the run-time changing scenarios of available energy, video frame characteristics, and user-defined coding constraints while keeping a good video quality. It assigns different Energy-Quality Classes to different video frames and fine-tunes at MB level depending upon the predictive energy quota in order to cope with above-mentioned run-time unpredictable scenarios. Compared to UMHexagonS [4], EPZS [6], and FastME [20], our enBudget scheme for energy-aware ME achieves an energy saving of up to 93%, 90%, 88% (average 88%, 77%, 66%), respectively. It suffers from an average Peak Signal to Noise Ratio (PSNR) loss of 0.29 dB compared to Full Search. We also demonstrate that enBudget is equally beneficial to various other state-of-the-art fast adaptive MEs (e.g. [4]). We have evaluated our scheme for ASIC and various FPGAs.
AB - The limited energy resources in portable multimedia devices require the reduction of encoding complexity. The complex Motion Estimation (ME) scheme of H.264/MPEG-4 AVC accounts for a major part of the encoder energy [3]. In this paper we present a Run-Time Adaptive Predictive Energy Budgeting (enBudget) scheme for energy-aware ME that predicts the energy budget for different video frames and different Macroblocks (MBs) in an adaptive manner considering the run-time changing scenarios of available energy, video frame characteristics, and user-defined coding constraints while keeping a good video quality. It assigns different Energy-Quality Classes to different video frames and fine-tunes at MB level depending upon the predictive energy quota in order to cope with above-mentioned run-time unpredictable scenarios. Compared to UMHexagonS [4], EPZS [6], and FastME [20], our enBudget scheme for energy-aware ME achieves an energy saving of up to 93%, 90%, 88% (average 88%, 77%, 66%), respectively. It suffers from an average Peak Signal to Noise Ratio (PSNR) loss of 0.29 dB compared to Full Search. We also demonstrate that enBudget is equally beneficial to various other state-of-the-art fast adaptive MEs (e.g. [4]). We have evaluated our scheme for ASIC and various FPGAs.
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U2 - 10.1109/date.2010.5457093
DO - 10.1109/date.2010.5457093
M3 - Conference contribution
AN - SCOPUS:77953117997
SN - 9783981080162
T3 - Proceedings -Design, Automation and Test in Europe, DATE
SP - 1725
EP - 1730
BT - DATE 10 - Design, Automation and Test in Europe
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 8 March 2010 through 12 March 2010
ER -