• Title/Summary/Keyword: Video Decoding

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Optimal Channel Power Allocation by Exploiting Packet Semantics for Real-time Wireless Multimedia Communication (실시간 멀티미디어 통신을 위한 의미 기반 채널 파워 할당 기법)

  • Hong, Sung-Woo;Won, You-Jip
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.1
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    • pp.171-184
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    • 2010
  • In this work, we develop a novel channel power allocation method for the real-time multimedia over the wireless network environment. Since each frame has different effect on the user perceivable QoS, improving packet loss does not necessarily coincide with perceivable improvements in QoS. A new channel power control scheme is suggested based on the quantified importance of each frame in terms of user perceivable QoS. Dynamic programming formulation is used to obtain optimal transmit power which minimizes power consumption and maximizes user perceivable QoS simultaneously. The experiment is performed by using publicly available video clips. The performance is evaluated using network simulator version 2 (NS 2) and decoding engine is embedded at the client node, and calculated PSNR over the every frame transmitted. Through the semantics aware power allocation (SAPA) scheme, significant improvement on the QoS has been verified, which is the result of unequal protection to more important packets. SAPA scheme reduced the loss of I frame by upto 27% and reduced power consumption by upto 19% without degradation on the user perceivable QoS.

Efficient Coding of Motion Vector Predictor using Phased-in Code (Phased-in 코드를 이용한 움직임 벡터 예측기의 효율적인 부호화 방법)

  • Moon, Ji-Hee;Choi, Jung-Ah;Ho, Yo-Sung
    • Journal of Broadcast Engineering
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    • v.15 no.3
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    • pp.426-433
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    • 2010
  • The H.264/AVC video coding standard performs inter prediction using variable block sizes to improve coding efficiency. Since we predict not only the motion of homogeneous regions but also the motion of non-homogeneous regions accurately using variable block sizes, we can reduce residual information effectively. However, each motion vector should be transmitted to the decoder. In low bit rate environments, motion vector information takes approximately 40% of the total bitstream. Thus, motion vector competition was proposed to reduce the amount of motion vector information. Since the size of the motion vector difference is reduced by motion vector competition, it requires only a small number of bits for motion vector information. However, we need to send the corresponding index of the best motion vector predictor for decoding. In this paper, we propose a new codeword table based on the phased-in code to encode the index of motion vector predictor efficiently. Experimental results show that the proposed algorithm reduces the average bit rate by 7.24% for similar PSNR values, and it improves the average image quality by 0.36dB at similar bit rates.

An Application-Specific and Adaptive Power Management Technique for Portable Systems (휴대장치를 위한 응용프로그램 특성에 따른 적응형 전력관리 기법)

  • Egger, Bernhard;Lee, Jae-Jin;Shin, Heon-Shik
    • Journal of KIISE:Computer Systems and Theory
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    • v.34 no.8
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    • pp.367-376
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    • 2007
  • In this paper, we introduce an application-specific and adaptive power management technique for portable systems that support dynamic voltage scaling (DVS). We exploit both the idle time of multitasking systems running soft real-time tasks as well as memory- or CPU-bound code regions. Detailed power and execution time profiles guide an adaptive power manager (APM) that is linked to the operating system. A post-pass optimizer marks candidate regions for DVS by inserting calls to the APM. At runtime, the APM monitors the CPU's performance counters to dynamically determine the affinity of the each marked region. for each region, the APM computes the optimal voltage and frequency setting in terms of energy consumption and switches the CPU to that setting during the execution of the region. Idle time is exploited by monitoring system idle time and switching to the energy-wise most economical setting without prolonging execution. We show that our method is most effective for periodic workloads such as video or audio decoding. We have implemented our method in a multitasking operating system (Microsoft Windows CE) running on an Intel XScale-processor. We achieved up to 9% of total system power savings over the standard power management policy that puts the CPU in a low Power mode during idle periods.