A Decoding-Complexity and Rate-Controlled Video-Coding Algorithm for HEVC

Thanuja Mallikarachchi, Dumidu Talagala, Hemantha Kodikara Arachchi, Chaminda Hewage and Anil Fernando
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Thanuja Mallikarachchi: Cardiff School of Technologies, Cardiff Metropolitan University, Llandaff Campus, Western Avenue, Cardiff CF5 2YB, UK
Dumidu Talagala: ARM Ltd., Manchester M1 3HU, UK
Hemantha Kodikara Arachchi: School of Science & Technology, Nottingham Trent University, Nottingham NG1 4FQ, UK
Chaminda Hewage: Cardiff School of Technologies, Cardiff Metropolitan University, Llandaff Campus, Western Avenue, Cardiff CF5 2YB, UK
Anil Fernando: Centre for Vision Speech and Signal Processing (CVSSP), University of Surrey, Guildford GU2 7XH, UK

Future Internet, 2020, vol. 12, issue 7, 1-23

Abstract: Video playback on mobile consumer electronic (CE) devices is plagued by fluctuations in the network bandwidth and by limitations in processing and energy availability at the individual devices. Seen as a potential solution, the state-of-the-art adaptive streaming mechanisms address the first aspect, yet the efficient control of the decoding-complexity and the energy use when decoding the video remain unaddressed. The quality of experience (QoE) of the end-users’ experiences, however, depends on the capability to adapt the bit streams to both these constraints (i.e., network bandwidth and device’s energy availability). As a solution, this paper proposes an encoding framework that is capable of generating video bit streams with arbitrary bit rates and decoding-complexity levels using a decoding-complexity–rate–distortion model. The proposed algorithm allocates rate and decoding-complexity levels across frames and coding tree units (CTUs) and adaptively derives the CTU-level coding parameters to achieve their imposed targets with minimal distortion. The experimental results reveal that the proposed algorithm can achieve the target bit rate and the decoding-complexity with 0.4% and 1.78% average errors, respectively, for multiple bit rate and decoding-complexity levels. The proposed algorithm also demonstrates a stable frame-wise rate and decoding-complexity control capability when achieving a decoding-complexity reduction of 10.11 (%/dB). The resultant decoding-complexity reduction translates into an overall energy-consumption reduction of up to 10.52 (%/dB) for a 1 dB peak signal-to-noise ratio (PSNR) quality loss compared to the HM 16.0 encoded bit streams.

Keywords: decoding-complexity–rate–distortion; decoding-complexity control; decoding-energy; HEVC; rate control; energy consumption control (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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