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A Method of Codec Comparison and Selection for Good Quality Video Transmission Over Limited-Bandwidth Networks

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A Method of Codec Comparison and Selection for Good Quality Video Transmission Over Limited-Bandwidth Networks sensors Article A Method of Codec Comparison and Selection for Good Quality Video Transmission Over Limited-Bandwidth Networks Janusz Klink Department of Telecommunications and Teleinformatics, Wroclaw University of Science and Technology, 50-370 Wroclaw, Poland; [email protected] Abstract: Finding a proper balance between video quality and the required bandwidth is an important issue, especially in networks of limited capacity. The problem of comparing the efficiency of video codecs and choosing the most suitable one in a specific situation has become very important. This paper proposes a method of comparing video codecs while also taking into account objective quality assessment metrics. The author shows the process of preparing video footage, assessing its quality, determining the rate–distortion curves, and calculating the bitrate saving for pairs of examined codecs. Thanks to the use of the spline interpolation method, the obtained results are better than those previously presented in the literature, and more resistant to the quality metric used. Keywords: video quality assessment; dynamic adaptive streaming; MPEG DASH; coding efficiency; codec comparison; spline interpolation; H.264 (AVC); H.265 (HEVC); AV1 1. Introduction A huge growth in Internet traffic has been observed in recent years. According to the Citation: Klink, J. A Method of Cisco’s Visual Networking Index (VNI) forecast, by the year 2022, more Internet protocol Codec Comparison and Selection for (IP) traffic will cross global networks than all the traffic observed before 2017. Busy-hour Good Quality Video Transmission Internet traffic (the busiest 60 min period in a day) has grown even more (i.e., by a factor Over Limited-Bandwidth Networks. of 4.6) than average Internet traffic (by a factor of 3.2) in the years 2016–2021. Moreover, Sensors 2021, 21, 4589. https:// video will account for up to 82 percent of global Internet traffic in 2022 [1,2]. In this context, doi.org/10.3390/s21134589 proper resource management in the case of low-bandwidth networks, or their segments, plays a crucial role. The delivery of good quality video content may be a challenging task Academic Editor: Petr Koudelka owing to the limitations of the last mile-, wireless-, or sensor networks. In the case of sensor networks, their resource constraints, especially in terms of processing capability, memory, Received: 10 May 2021 battery, and achievable data rates, may seriously decrease the offered quality of service Accepted: 30 June 2021 Published: 4 July 2021 (QoS) [3]. Thus, the implementation of proper multimedia source coding techniques, in order to achieve less demanding video content, may help to solve this problem. The main Publisher’s Note: MDPI stays neutral objectives of designing a coder for sensor networks are high compression efficiency and low with regard to jurisdictional claims in complexity in order to limit bandwidth and energy consumption. A further challenge is the published maps and institutional affil- provision of the robust and error-resilient coding of source video. However, the delivery of iations. good quality video is not only an important issue in the case of specific environments like sensor networks, and this problem can be discussed in a much wider context. The Internet is currently the most popular and broadly available means of commu- nication, and is it used for video streaming to almost every place in the world. Data streaming must be adapted to the dynamically varying circumstances, while also taking Copyright: © 2021 by the author. Licensee MDPI, Basel, Switzerland. into account different network parameters. This idea was implemented in the Internet as This article is an open access article adaptive streaming over the hypertext transport protocol (HAS). It was initially introduced distributed under the terms and by leading companies like Apple (HTTP live streaming) [4], Adobe (HTTP dynamic stream- conditions of the Creative Commons ing) [5], and Microsoft (smooth streaming) [6]. Subsequently, ISO/IEC (2014) proposed an Attribution (CC BY) license (https:// open and vendor independent standard that describes dynamic adaptive streaming over creativecommons.org/licenses/by/ HTTP (DASH), which was then ratified by the Moving Pictures Experts Group (MPEG- 4.0/). DASH) [7–10]. Sensors 2021, 21, 4589. https://doi.org/10.3390/s21134589 https://www.mdpi.com/journal/sensors Sensors 2021, 21, x FOR PEER REVIEW 2 of 21 streaming) [5], and Microsoft (smooth streaming) [6]. Subsequently, ISO/IEC (2014) pro- posed an open and vendor independent standard that describes dynamic adaptive Sensors 2021 21 , , 4589 streaming over HTTP (DASH), which was then ratified by the Moving Pictures2 ofExperts 17 Group (MPEG-DASH) [7–10]. In the case of the above mentioned techniques, clients pull video from a standard HTTPIn server, the case which of the hosts above the mentioned media content, techniques, using HTTP clients as pull the videoapplication, from a and standard the trans- missionHTTP server, control which protocol hosts (TCP) the media as the content,transport- usinglayer HTTP protocols. as the The application, video is stored and the on the HTTPtransmission server controlas a stream protocol of media (TCP) segments as the transport-layer (chunks) that protocols. are typically The videotwo to is ten stored seconds long.on the The HTTP segments server asare a streamencoded of at media multiple segments bitrate (chunks) levels and that listed are typically in a media two topresenta- ten seconds long. The segments are encoded at multiple bitrate levels and listed in a media tion description (MPD) file that provides an index for the available segments at the server. presentation description (MPD) file that provides an index for the available segments at The adaptation streaming mechanism assumes that a DASH client estimates the available the server. The adaptation streaming mechanism assumes that a DASH client estimates the networkavailable bandwidth network bandwidth and uses and information uses information from the from playback the playback buffer buffer to select to select a suitable a bitratesuitable of bitrate the video of the chunk video to chunk be requested to be requested (using GET (using message) GET message) from the from server. the server. This pro- Thiscess, process,called bitrate called bitrateswitching, switching, allows allows sufficient sufficient data data to tobe be kept kept in in the the playbackplayback buffer buffer in orderin order to toavoid avoid video video stalls stalls and toto preservepreserve a a seamless, seamless, or or at leastat least smoother, smoother, streaming streaming experience [[11].11]. WhenWhen the the network network bandwidth bandwidth is severelyis severely limited, limited, lower lower resolutions resolutions and and coding ratesrates are are used, used, and and when when the the situation situation improves, improves, it reverts it reverts to higher to resolutionshigher resolutions and andcoding coding rates rates [12,13 [12,13]] (see Figure (see Figure1). 1). Figure 1.1. CommunicationCommunication in in HTTP HTTP adaptive adaptive streaming streamin systems.g systems. MPD, MPD, media media presentation presentation descrip- de- scription;tion; DASH, DASH, dynamic dynamic adaptive adaptive streaming streaming over HTTP. over HTTP. The datasetdataset shouldshould be be chosen chosen so so that that efficient efficient and and unobtrusive unobtrusive switching switching between between different video resolutions is possible. This is required in order to preserve a high, and different video resolutions is possible. This is required in order to preserve a high, and possibly stable, video quality. The quality may be defined by objective parameters that possibly stable, video quality. The quality may be defined by objective parameters that describe quality of service (QoS) [14–18], or by the users’ subjective assessment scores describethat represent quality the of so-called service (QoS) quality [14–18], of experience or by the (QoE) users’ [19 subjective–21]. In this assessment paper, the scores objec- that representtive approach the willso-called be presented quality asof aexperience method of (QoE) assessing [19–21]. video In quality this paper, and comparing the objective approachcodec performance. will be presented A set of as objective a method methods of assessing may be video divided quality into full-referenceand comparing (FR), codec performance.reduced-reference A set (RR), of objective and no-reference methods (NR) may methods, be divided respectively. into full-reference FR methods (FR), assume reduced- referencethat there (RR), is access and to no-reference both the video (NR) footage methods, (reference) respectively. and the FR distorted methods (tested)assume videothat there issamples, access whichto both are the subsequently video footage compared (reference with) and the the reference distorted [22]. (tested) When onlyvideo partial samples, whichinformation are subsequently regarding the compared source video with is available,the reference RR methods [22]. When are usedonly [partial23]. In theinformation case regardingof NR methods, the source there isvideo only is access available, to the RR distorted methods signal, are andused video [23]. qualityIn the case estimation of NR ismeth- performedods, there is without only access any knowledge to the distorted of the sign sourceal, and video video footage quality [24]. estimation In order to is examine performed withouttwo codecs, any itknowledge is worth
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