Software HEVC video decoder: towards an energy saving for mobile applications
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Software HEVC video decoder: towards an energy saving for mobile applications Naty Sidaty1 · Julien Heulot2 · Wassim Hamidouche2 · Maxime Pelcat2 · Daniel Menard2 Received: 19 February 2019 / Revised: 19 March 2020 / Accepted: 5 May 2020 / © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract With the explosive growth of mobile video consumption over the Internet, delivering video at high quality while controlling the energy consumption of embedded decoding devices is becoming a primary concern. In this context, this paper demonstrates that tailored energy savings strategies, coupled with a video quality assessment protocol, have the potential to reduce the energy consumption of video decoding. We investigate on a real-time, optimized HEVC decoder, the relationship between the perceived mobile video quality and the energy consumption of the decoder. In addition to low level optimizations for ARM Neon platforms, two energy reduction methods named Approximate and Skipping have been investigated. Results show that energy savings of up to 20% can be achieved by using these methods with the same subjective perceived video quality. These subjective results confirm objective measurements, using PSNR and SSIM metrics, that depict a limited video quality degradation. Keywords HEVC · Quality assessment · Mobile energy saving · Filter complexity reduction · MOS · Statistical analysis · ARM
Naty Sidaty
[email protected] Julien Heulot [email protected] Wassim Hamidouche [email protected] Maxime Pelcat [email protected] Daniel Menard [email protected] 1
ViQuaM Labs, INSA Rennes, 20 Avenue des Buttes de Coesmes, Rennes, 35000, France
2
IETR/INSA Rennes, 20 Avenue des Buttes de Coesmes, Rennes, 35000, France
Multimedia Tools and Applications
1 Introduction Video communication services currently gain importance at an unprecedented pace. Social networking, data sharing platforms and user requirements to watch videos anytime, anywhere and on various mobile devices, have made the energy consumption of video decoding a very challenging problem. Over the past two decades, video coding tools have been developed to ensure a high Quality of Experience (QoE) for such services. The latest video coding standard High Efficiency Video Coding (HEVC), developed jointly by the Motion Picture Experts Group (MPEG) and the Video Coding Expert Group (VCEG) under the Joint Collaborative Team on Video Coding (JCTVC), [37] integrates these new tools and provides up to 60% [38] bit rate reduction, for a given perceived quality, when compared to the previous Advanced Video Coding (AVC) standard [42]. A large effort has been devoted, both at circuit and at system levels, to reduce the computational energy consumption of video codecs. On one side, new circuit technologies shrink down transistors and make hardware more energy efficient. On the other side, new system technologies are developed to adapt the instantaneous processing capacity to the requirements of the run
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