1、 Recommendation ITU-R BT.1908(01/2012)Objective video quality measurement techniques for broadcasting applications using HDTV in the presence of a reduced reference signalBT SeriesBroadcasting service(television)ii Rec. ITU-R BT.1908 Foreword The role of the Radiocommunication Sector is to ensure th
2、e rational, equitable, efficient and economical use of the radio-frequency spectrum by all radiocommunication services, including satellite services, and carry out studies without limit of frequency range on the basis of which Recommendations are adopted. The regulatory and policy functions of the R
3、adiocommunication Sector are performed by World and Regional Radiocommunication Conferences and Radiocommunication Assemblies supported by Study Groups. Policy on Intellectual Property Right (IPR) ITU-R policy on IPR is described in the Common Patent Policy for ITU-T/ITU-R/ISO/IEC referenced in Anne
4、x 1 of Resolution ITU-R 1. Forms to be used for the submission of patent statements and licensing declarations by patent holders are available from http:/www.itu.int/ITU-R/go/patents/en where the Guidelines for Implementation of the Common Patent Policy for ITU-T/ITU-R/ISO/IEC and the ITU-R patent i
5、nformation database can also be found. Series of ITU-R Recommendations (Also available online at http:/www.itu.int/publ/R-REC/en) Series Title BO Satellite delivery BR Recording for production, archival and play-out; film for television BS Broadcasting service (sound) BT Broadcasting service (televi
6、sion) F Fixed service M Mobile, radiodetermination, amateur and related satellite services P Radiowave propagation RA Radio astronomy RS Remote sensing systems S Fixed-satellite service SA Space applications and meteorology SF Frequency sharing and coordination between fixed-satellite and fixed serv
7、ice systems SM Spectrum management SNG Satellite news gathering TF Time signals and frequency standards emissions V Vocabulary and related subjects Note: This ITU-R Recommendation was approved in English under the procedure detailed in Resolution ITU-R 1. Electronic Publication Geneva, 2012 ITU 2012
8、 All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without written permission of ITU. Rec. ITU-R BT.1908 1 RECOMMENDATION ITU-R BT.1908 Objective video quality measurement techniques for broadcasting applications using HDTV in the presence of a reduced refe
9、rence signal (2012) Scope This Recommendation specifies methods for estimating the perceived video quality of broadcasting applications using HDTV when a reduced reference signal is available. The ITU Radiocommunication Assembly, considering a) that the ability to automatically measure the quality o
10、f broadcast video has long been recognized as a valuable asset to the industry; b) that Recommendation ITU-R BT.1683 describes objective methods for measuring the perceived video quality of standard definition digital broadcast television in the presence of a reduced reference; c) that Recommendatio
11、n ITU-R BT.709 describes parameter values for the HDTV standards for production and international programme exchange and Recommendation ITU-R BT.710 describes subjective assessment methods for image quality in high-definition television; d) that HDTV is becoming widely used in broadcasting; e) that
12、ITU-T Study Group 9, based on the results of the HDTV report sent by VQEG, has produced Recommendation ITU-T J.342, which specified objective video quality measurement of HDTV in the presence of a reduced reference; f) that objective measurement of the perceived video quality of HDTV may complement
13、subjective assessment methods, recommends 1 that the objective video quality model given in Annex 1 should be used for objective measurement of perceived video quality for broadcasting applications using HDTV in the presence of a reduced reference signal. Annex 1 1 Introduction This Recommendation p
14、rovides a video quality measurement method for use in high definition television (HDTV) non-interactive applications when the reduced reference (RR) measurement method can be used. The model was compared to subjective quality scores obtained using Recommendation ITU-R BT.500. Analyses showed that th
15、e accuracy of this model was equivalent to that of PSNR. 2 Rec. ITU-R BT.1908 For the RR model to operate correctly, the unimpaired source video should be available for the model to extract parameters. These extracted parameters as well as the degraded video sequence are the inputs to the RR model.
16、The estimation method performs both calibration (i.e. gain/offset and spatial/temporal registration) and objective video quality estimation. The validation test material contained both ITU-T H.264 and MPEG-2 coding degradations and various transmission error conditions (e.g. bit errors, dropped pack
17、ets). The model in this Recommendation may be used to monitor the quality of deployed networks to ensure their operational readiness. The visual effects of the degradations may include spatial as well as temporal degradations. The model in this Recommendation can also be used for lab testing of vide
18、o systems. When used to compare different video systems, it is advisable to use a quantitative method (such as that in Recommendation ITU-T J.149) to determine the models accuracy for that particular context. This Recommendation is deemed appropriate for broadcasting services delivered between 1 Mbi
19、t/s and 30 Mbit/s. The following resolutions and frame rates were considered in the validation test: 1080/59.94/I 1080/25/P 1080/50/I 1080/29.97/P. The following conditions were allowed in the validation test for each resolution: Test factors Video resolution: 1 920 1 080 interlaced and progressive
20、Video frame rates 29.97 and 25 frames per second Video bit rates: 1 to 30 Mbit/s Temporal frame freezing (pausing with skipping) of maximum 2 seconds Transmission errors with packet loss Conversion of the SRC from 1080 to 720/P, compression, transmission, decompression, and then conversion back to 1
21、080 Coding technologies H.264/AVC (MPEG-4 Part 10) MPEG-2 Note that 720/P was considered in the validation test plan as part of the test condition (HRC). Because currently 720/P is commonly up-scaled as part of the display, it was felt that 720/P HRCs would more appropriately address this format. 1.
22、1 Applications The applications for the estimation models described in this Recommendation include, but are not limited, to: 1) Video quality monitoring at the receiver when side-channels are available. 2) Video quality monitoring at measurement nodes located between the point of transmission and th
23、e point of reception. The model described in this Recommendation provides a statistically similar performance to PSNR, yet it can be used for video quality assessment when the reduced reference signal is available at the point of measurement. Rec. ITU-R BT.1908 3 1.2 Limitations The video quality es
24、timation model described in this Recommendation cannot be used to replace subjective testing. Correlation values between two carefully designed and executed subjective tests (i.e. in two different laboratories) normally fall within the range 0.95 to 0.98. This Recommendation cannot be used to make v
25、ideo system comparisons (e.g. comparing two codecs, comparing two different implementations of the same compression algorithm). The performance of the video quality estimation model described in this Recommendation is not statistically better than PSNR. When frame freezing was present, the test cond
26、itions typically had frame freezing durations less than 2 seconds. The model in this Recommendation was not validated for measuring video quality in a re-buffering condition (i.e. video that has a steadily increasing delay or freezing without skipping). The model was not tested on other frame rates
27、than those used in TV systems (i.e. 29.97 frames per second and 25 frames per second, in interlaced or progressive mode). It should be noted that in case of new coding and transmission technologies producing artefacts which were not included in this evaluation, the objective model may produce errone
28、ous results. Here, a subjective evaluation is required. Note that the model in this Recommendation was not evaluated on talking-head content typical of video-conferencing scenarios. 2 References The following ITU Recommendations and other references contain provisions, which, through reference in th
29、is text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edi
30、tion of the Recommendations and other references listed below. A list of the currently valid ITU Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation. Recommendation ITU-T J.244 (200
31、8), Full reference and reduced reference calibration methods for video transmission systems with constant misalignment of spatial and temporal domains with constant gain and offset. 3 Definitions 3.1 Terms defined elsewhere This Recommendation uses the following terms defined elsewhere: 3.1.1 Subjec
32、tive assessment (picture): The determination of the quality or impairment of programme-like pictures presented to a panel of human assessors in viewing sessions. 3.1.2 Objective perceptual measurement (picture): The measurement of the performance of a programme chain by the use of programme-like pic
33、tures and objective (instrumental) measurement methods to obtain an indication that approximates the rating that would be obtained from a subjective assessment test. 3.1.3 Proponent: An organization or company that proposes a video quality model for validation testing and possible inclusion in an IT
34、U Recommendation. 4 Rec. ITU-R BT.1908 3.2 Terms defined in this Recommendation This Recommendation defines the following terms: 3.2.1 Frame rate: The number of unique frames (i.e. total frames repeated frames) per second. 3.2.2 Simulated transmission errors: Errors imposed upon the digital video bi
35、t stream in a highly controlled environment. Examples include simulated packet loss rates and simulated bit errors. Parameters used to control simulated transmission errors are well defined. 3.2.3 Transmission errors: Any error imposed on the video transmission. Example types of errors include simul
36、ated transmission errors and live network conditions. 4 Abbreviations and acronyms This Recommendation uses the following abbreviations and acronyms: ACR Absolute Category Rating (see Recommendation ITU-R BT.500) ACR-HR Absolute Category Rating with Hidden Reference (see Recommendation ITU-T P.910)
37、AVI Audio Video Interleave DMOS Difference Mean Opinion Score FR Full Reference FRTV Full Reference TeleVision HRC Hypothetical Reference Circuit ILG VQEGs Independent Laboratory Group MOS Mean Opinion Score MOSp Mean Opinion Score, predicted NR No (or Zero) Reference PSNR Peak Signal-to-Noise Ratio
38、 PVS Processed Video Sequence RMSE Root Mean Square Error RR Reduced Reference SFR Source Frame Rate SRC Source Reference Channel or Circuit VQEG Video Quality Experts Group YUV Colour Space and file format 5 Conventions None. Rec. ITU-R BT.1908 5 6 Description of the reduced reference measurement m
39、ethods 6.1 Introduction Although PSNR has been widely used as an objective video quality measure, it is also reported that it does not well represent perceptual video quality. By analysing how humans perceive video quality, it is observed that the human visual system is sensitive to degradation arou
40、nd the edges. In other words, when the edge pixels of a video are blurred, evaluators tend to give low scores to the video even though the PSNR is high. Based on this observation, the reduced reference models which mainly measure edge degradations have been developed. Figure 1 illustrates how a redu
41、ced-reference model works. Features which will be used to measure video quality at a monitoring point are extracted from the source video sequence and transmitted. Table 1 shows the side-channel bandwidths for the features, which have been tested in the VQEG HDTV test. FIGURE 1 Block diagram of redu
42、ced reference model BT.1908-01ChannelTransmitterSourcevideosequenceRRmodelFeature extractionfor video qualitymeasurementReceivedvideosequenceReceiverChannelTABLE 1 Side-channel bandwidths Video format Tested bandwidths 1080/60 Hz (29.97 fps) 1080/30Pp (29.97 fps) 56 kbit/s, 128 kbit/s, 256 kbit/s 10
43、80/25Pp (25 fps) 1080/50I Hz (25 fps) 56 kbit/s, 128 kbit/s, 256 kbit/s 6.2 The EPSNR reduced-reference model 6.2.1 Edge PSNR (EPSNR) The RR models mainly measure on-edge degradations. In the models, an edge detection algorithm is first applied to the source video sequence to locate the edge pixels.
44、 Then, the degradation of those edge pixels is measured by computing the mean squared error. From this mean squared error, the edge PSNR is computed. 6 Rec. ITU-R BT.1908 One can use any edge detection algorithm, though there may be minor differences in the results. For example, one can use any grad
45、ient operator to locate edge pixels. A number of gradient operators have been proposed. In many edge detection algorithms, the horizontal gradient image ghorizontal(m,n) and the vertical gradient image gvertical(m,n) are first computed using gradient operators. Then, the magnitude gradient image g(m
46、 n) may be computed as follows: Finally, a thresholding operation is applied to the magnitude gradient image to find edge pixels. In other words, pixels whose magnitude gradients exceed a threshold value are considered as edge pixels. Figures 2-6 illustrate the procedure. Figure 2 shows a source im
47、age. Figure 3 shows a horizontal gradient image ghorizontal(m,n), which is obtained by applying a horizontal gradient operator to the source image of Fig. 2. Figure 4 shows a vertical gradient image gvertical(m,n), which is obtained by applying a vertical gradient operator to the source image of Fig
48、 2. Figure 5 shows the magnitude gradient image (edge image) and Fig. 6 shows the binary edge image (mask image) obtained by applying thresholding to the magnitude gradient image of Fig. 5. FIGURE 2 A source image (original image) BT.1908-02),(),(),( nmgnmgnmgverticalhorizontal+=Rec. ITU-R BT.1908
49、7 FIGURE 3 A horizontal gradient image, which is obtained by applying a horizontal gradient operator to the source image of Fig. 2 BT.1908-03FIGURE 4 A vertical gradient image, which is obtained by applying a vertical gradient operator to the source image of Fig. 2 BT.1908-048 Rec. ITU-R BT.1908 FIGURE 5 A magnitude gradient image BT.1908-05FIGURE 6 A binary edge image (mask image) obtained by applying thresholding to the magnitude gradient image of Fig. 5 BT.1908-06Alternatively, one may use a modified procedure to find edge pixels. For instance, one may first apply a vertic
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