Proceedings of ACIVS 2002 (Advanced Concepts for Intelligent Vision Systems), Ghent, Belgium, September 9-11, 2002 QUALITY ASSESSMENT OF VIDEO STREAMING IN THE BROADBAND ERA Jan Janssen, Toon Coppens and Danny De Vleeschauwer Alcatel Bell, Network Strategy Group, Francis Wellesplein 1, B-2018 Antwerp, Belgium {jan.janssen, toon.coppens, danny.de_vleeschauwer}@alcatel.be ABSTRACT Since the transport capacity in the access networks to the Internet and in the Internet core itself has increased substantially, PC ap- plications that make use of streaming video of good quality are nowadays emerging. The well-known MPEG-1 video compres- sion standard is an adequate candidate to be used in such kind of applications. In this paper, we determine the bit rate needed to attain good quality for streaming video. We use the well-known Mean Square Error (MSE) and the Just Noticeable Difference (JND) implemented in the commercially available JNDmetrixIQ software, which models the characteristics of the human visual system, as objective quality measures. We correlate both these measures with the Mean Subjective Score (MSS) resulting from a small-scale subjective experiment and show that the JND corre- lates better than the MSE in the region of interest (i.e., where the quality is not too bad). In this process we also calibrate the JND scale, i.e., we determine the JND value that corresponds to “good” quality. Finally, we show that the bit rate needed to attain good quality depends on the video content but (for MPEG-1) a bit rate of 1.5 Mbit/s is sufficient for any kind of video. 1. INTRODUCTION During the last years, the transport capacity of both the Internet core and the access networks to it, has increased dramatically. In particular, broadband access technologies (e.g. ADSL, cable, …) provide typical downstream link rates in the order of Mbit/s, allowing more bandwidth- intensive services than a traditional dial-up connection. Streaming video, i.e., video that needs to be displayed al- most immediately (i.e., some small amount of buffering time) after its request, is an example of such a bandwidth- demanding service. On-demand streaming is initiated by the end user who requests certain content (e.g. news, weather forecast, …) to be streamed from the Internet. Live streams, on the other hand, can be captured by any end user and are typically used for special occasions (e.g. music shows, sport events, …). Also broadcasting video over the Internet can be considered as a streaming service. In uncompressed form, video sequences require a huge amount of bit rate. In principle, for every frame pixel, 3 bytes have to be reserved for its RGB color values. How- ever, as the human eye is known to be more sensitive to luminance than chrominance, a subsampling technique may be used when using the YC b C r color space, with Y standing for luminance and C b and C r for chrominance difference values. In the latter color space, it suffices to store only a C b and a C r value for every 2 pixels, often referred to as 4:2:2 subsampling. For Standard Intermediate Format (SIF) sequences of 352 × 288 pixels and 25 frames/s, this leads to a bit rate of 352 × 288 × 25 × 16 bit/s = 40.55 Mbit/s. To reduce this bit rate, video compression techniques can be used. The most wide-spread video codecs nowadays were developed by the Moving Picture Experts Group (MPEG) and are referred to as MPEG-{1, 2} [2], [3], [5]. A seg- ment-oriented successor of these codecs (MPEG-4 [1]) has already been introduced, but this is outside the scope of this paper. The basic idea of the MPEG-{1,2} codecs is quite similar, i.e., they both divide the successive frames in blocks and perform Discrete Cosine Transform (DCT) and motion-compensated prediction techniques on them. Obviously, the quality of MPEG-encoded video streams is strongly related to the bit rate reserved for it. Streaming video services require the effective bit rate of the video stream (= the bit rate of the encoded video + some packeti- zation overhead) to be such that it fits within the access capacity of the user. Otherwise, information will be lost and the expected video quality will not be reached. In this paper, we try to determine the bit rate needed to encode SIF sequences at decent quality levels using the Constant Bit Rate (CBR) mode of MPEG-1. In order to do so, the quality of the encoded video streams will be assessed with 2 objective measures, i.e., Sarnoff’s Just Noticeable Difference (JND) [9] and the Mean Square Error (MSE). Also, a small subjective quality assessment experiment was performed. As an important side-result of this paper, we also compare and discuss the results of these 3 evaluation methods. This paper is organized as follows. In Section 2, we de- scribe the original, high-quality video sequences that will be under test in this paper. Section 3 starts with a descrip- tion of both objective quality measures (JND and MSE). Afterwards, the outcome of both measures are reported, discussed and correlated. The results of our subjective quality experiment are described in Section 4. Also, some correlation with the objective results is given. Finally, the conclusions are reported in Section 5. 38