ITU-R BT 1676-2004 Methodological framework for specifying accuracy and cross-calibration of video quality metrics《规定视频质量度量的精确度和交叉刻度的方法框架》.pdf
《ITU-R BT 1676-2004 Methodological framework for specifying accuracy and cross-calibration of video quality metrics《规定视频质量度量的精确度和交叉刻度的方法框架》.pdf》由会员分享,可在线阅读,更多相关《ITU-R BT 1676-2004 Methodological framework for specifying accuracy and cross-calibration of video quality metrics《规定视频质量度量的精确度和交叉刻度的方法框架》.pdf(23页珍藏版)》请在麦多课文档分享上搜索。
1、 Rec. ITU-R BT.1676 1 RECOMMENDATION ITU-R BT.1676 Methodological framework for specifying accuracy and cross-calibration of video quality metrics (Question ITU-R 44/6) (2004) The ITU Radiocommunication Assembly, considering a) that digital TV and HDTV utilizing bit-rate reduction technologies such
2、as MPEG-2, DV and others have achieved widespread use; b) that the Radiocommunication Sector is responsible for setting the overall quality perfor-mance of broadcasting chains; c) that impairments to television pictures can be shown to correlate with measurable features of the signals; d) that overa
3、ll picture quality is related to the combination of all impairments; e) that in the case of digital TV it is necessary, in particular, to assess the performance of bit-rate reduction methods both in terms of subjective and objective parameters; f) that for television systems a number of objective pi
4、cture quality parameters as well as associated performance measurement and monitoring methods have been developed for the studio environment and in broadcasting; g) that full reference objective picture quality measurement methods are useful in evaluating studio and broadcasting systems; h) that dat
5、a sets of test materials, subjective scores and objective values are used in the validation testing of objective picture quality measurement methods; j) that there are a number of proposed full reference video quality metrics (VQMs) that can be used to provide objective picture quality ratings; k) t
6、hat there are a number of well-known statistical evaluation methods documented in the literature that can be used to validate and compare VQMs based on data sets of test materials, subjective scores and objective values; l) that when one or more VQMs are accepted as normative in ITU Recommendations
7、there will still be a need to estimate the mathematical accuracy (resolving power) of the VQM being used; m) that cross-calibration of full reference objective picture quality measurement methods based on available data sets is important for international exchange of measurement and monitoring resul
8、ts, 2 Rec. ITU-R BT.1676 recommends 1 that the calculations specified in Annex 1 be used to estimate the accuracy and cross-calibration of objective picture quality measurements utilizing the full reference method; 2 that the calculations specified in Annex 1 may be used as one of several methods to
9、 deter-mine the accuracy in evaluation and validation of various objective picture quality measurements utilizing the full reference method. Annex 1 Method for specifying accuracy and cross-calibration of VQMs 1 Scope VQMs are intended to provide calculated values that are strongly correlated with v
10、iewer subjective assessments. This Recommendation provides: Methods for curve fitting VQM objective values to subjective data in order to facilitate the accuracy calculation and to produce a normalized objective value scale that can be used for cross correlation between different VQMs. An algorithm
11、(based on statistical analysis relative to subjective data) to quantify the accuracy of a given VQM. A simplified root mean square error calculation to quantify the accuracy of a VQM when the subjective data has roughly equal variance across the VQM scale. A method to plot classification errors to d
12、etermine the relative frequencies of “false tie”, “false differentiation”, “false ranking”, and “correct decision” for a given VQM. The methods specified in this Recommendation are based on objective and subjective evaluation of component video such as defined by Recommendation ITU-R BT.601 using me
13、thods such as described in Recommendation ITU-R BT.500 Methodology for the subjective assessment of the quality of television pictures. A data set for a VQM will consist of objective values and mean subjective scores for a variety of motion video sources (SRCs) processed by a variety of hypothetical
14、 reference circuits (HRCs). An example of such a data set is given in ITU-T Document COM 9-80-E, Final report from the video quality experts group on the validation of objective models of video quality assessment. The methods specified in this Recommendation are directly applicable to a defined data
15、 set as described above. For measurements not specifically part of the data set the methods specified in this Recommendation provide a reasonable estimate of accuracy and cross-calibration for applications that can be considered to be similar to and within the scope of the defined data set. Rec. ITU
16、-R BT.1676 3 The methods specified in this Recommendation are appropriate for use in combination with other statistical calculations in order to evaluate the usefulness of a VQM. Informative information regarding the use of the methods is presented in Appendix 1. A complete verification process by s
17、uitable independent laboratories is required for a VQM to be considered for inclusion as a normative part of an ITU-R Recommendation. 2 Accuracy of a VQM In order to use an objective VQM, one must know whether the score difference between two processed videos is statistically significant. Hence, a q
18、uantification is needed of the accuracy (or resolving power) of the VQM. To visualize this resolving power, it helps to begin with a scatter plot in which the abscissa of each point is a VQM score from a particular video SRC and distortion HRC, and the ordinate is a subjective score from a particula
19、r viewing of the SRC/HRC. Each SRC/HRC combination (associated with a particular VQM score) contains a distribution of mean subjective scores, S, based on a number of viewers, which represents (approximately) the relative probabilities of S for the particular SRC/HRC combination. The resolving power
20、 of a VQM can be defined as the difference between two VQM values for which the corresponding subjective-score distributions have means that are statistically different from each other (typically at the 0.95% significance level). Given this qualitative picture, two metrics for resolving power will b
21、e described in this section, each one useful in a different context. The metrics are described in 2.3 and 2.4. Also, in 2.5, a method is described for evaluating the frequencies of different kinds of errors made by the VQM. As an example of implementation of all the methods, a computer source code i
22、n MATLAB (The Mathworks, Inc., Natick, MA) is provided in Appendix 2. 2.1 Nomenclature and coordinate scales Let each SRC/HRC combination in a data set be called a “situation”, and let N be the number of situations in this data set. A subjective score for situation i and viewer l will be denoted as
23、Sil, and an objective score for situation i will be denoted as Oi. Averaging over a variable such as viewer will be denoted with a dot in that variable location. For instance, the mean opinion score of a situation will be denoted as .iS The subjective-score statistics from each pair (i, j) of these
24、situations are to be assessed for significance of VQM difference, and then used to arrive at a resolving power for the VQM difference, as a function of the VQM value. Prior to any statistical analysis, the original subjective mean opinion scores iS are linearly transformed to the interval 0, 1, defi
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