1、TECHNICALREPORTTR CISPR29First edition2004-08Television broadcast receivers and associated equipment Immunity characteristics Methods of objective picture assessment Reference number TR CISPR 29:2004(E) INTERNATIONAL SPECIAL COMMITTEE ON RADIO INTERFERENCE Consolidated editions The IEC is now publis
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7、 further assistance, please contact the Customer Service Centre: Email: custserviec.ch Tel: +41 22 919 02 11 Fax: +41 22 919 03 00 TECHNICALREPORTTR CISPR29First edition2004-08Television broadcast receivers and associated equipment Immunity characteristics Methods of objective picture assessment For
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10、RNATIONAL SPECIAL COMMITTEE ON RADIO INTERFERENCE 2 TR CISPR 29 IEC:2004(E) CONTENTSFOREWORD.31 Scope 52 Normative references .53 Abbreviations .54 Test method for objective picture assessment .55 Methodology for detection of analogue picture degradations65.1 Algorithm for superimposed patterns, moi
11、r patterns 65.2 Algorithm for loss of luminance and contrast 75.3 Algorithm for loss of colour 75.4 Algorithm for loss of synchronisation76 Methodology for detection of digital picture degradations.86.1 Algorithm for blocking 86.2 Algorithm for frozen patterns, stop of moving element 86.3 Algorithm
12、for total loss of picture, irrecoverable data stream error.87 Alternative methodology for detection of digital picture degradations .97.1 Test pattern.97.2 Analysis 97.3 Comparison.10TR CISPR 29 IEC:2004(E) 3 INTERNATIONAL ELECTROTECHNICAL COMMISSION_TELEVISION BROADCAST RECEIVERS AND ASSOCIATED EQU
13、IPMENT IMMUNITY CHARACTERISTICS METHODS OF OBJECTIVE PICTURE ASSESSMENT FOREWORD1) The International Electrotechnical Commission (IEC) is a worldwide organization for standardization comprising all national electrotechnical committees (IEC National Committees). The object of IEC is to promote intern
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24、 it has collected data of a different kind from that which is normally published as an International Standard, for example “state of the art“. CISPR 29, which is a technical report, has been prepared by CISPR subcommittee I: Electromagnetic compatibility of information technology equipment, multimed
25、ia equipment and receivers. The text of this technical report is based on the following documents: Enquiry draft Report on voting CISPR/I/104/DTR CISPR/I/119/RVC Full information on the voting for the approval of this technical report can be found in the report on voting indicated in the above table
26、. 4 TR CISPR 29 IEC:2004(E) This publication has been drafted in accordance with the ISO/IEC Directives, Part 2. The committee has decided that the contents of this publication will remain unchanged until the maintenance result date indicated on the IEC web site under “http:/webstore.iec.ch“ in the
27、data related to the specific publication. At this date, the publication will be reconfirmed; withdrawn; replaced by a revised edition, or amended. A bilingual version of this publication may be issued at a later date. TR CISPR 29 IEC:2004(E) 5 TELEVISION BROADCAST RECEIVERS AND ASSOCIATED EQUIPMENT
28、IMMUNITY CHARACTERISTICS METHODS OF OBJECTIVE PICTURE ASSESSMENT 1 Scope This Technical Report describes the algorithms used for objective picture assessment in immunity tests of analogue and digital TV broadcast receivers and associated equipment. The algorithms used were developed on the basis of
29、the specifications included in Annex K1of CISPR 20. The method of objective picture assessment described in that annex employs the same interference mechanism and is based on the same wanted signal definition as specified in CISPR 20. Objective picture assessment, therefore, constitutes an alternati
30、ve to the subjective method and offers the advantage of direct correlation to the subjective method. 2 Normative references The following referenced documents are indispensable for the application of this document. For dated references, only the edition cited applies. For undated references, the lat
31、est edition of the referenced document (including any amendments) applies. CISPR 20:2002, Sound and television broadcast receivers and associated equipment Immunity characteristics Limits and methods of measurement Amendment 1 (2002) ITU-R BT.500-10, Methodology for the subjective assessment of the
32、quality of television picturesITU-R BT.801-1, Test signals for digitally encoded colour television signals conforming with Recommendations ITU-R BT.601 (Part A) and ITU.R BT.6563 Abbreviations For the purposes of this document, the following abbreviations apply. CCVS composite colour video signal (c
33、hrominance, video, blanking and sync signal) DCT discrete cosine transform EUT equipment under test HSL hue, saturation, luminance (colour space model) SSCQE (single stimulus continuous quality evaluation) 4 Test method for objective picture assessment Objective picture assessment is based on compar
34、ison with a reference picture or a reduced reference picture. Both the reference picture and the test picture can be recorded from the EUT monitor by means of a video camera or at the EUTs video output (CCVS) direct. _1See Amendment 2 to CISPR 20:2002, to be published. 6 TR CISPR 29 IEC:2004(E) The
35、recorded test picture is digitised, and deviations from a stored reference picture are determined by means of the picture assessment algorithms described below. An alternative methodology computes the deviation from specific features determined on both the reference picture and the picture to assess
36、. 5 Methodology for detection of analogue picture degradations Analogue picture degradations are defined as: superimposed patterns, moir patterns; loss of luminance and contrast; loss of colour; loss of synchronization. 5.1 Algorithm for superimposed patterns, moir patterns To assess picture degrada
37、tion showing as a set of lines, an average signal value is formed for a defined area in the simplest case. The deviation of the average signal value of this area from a reference value determined from an undisturbed picture serves as a criterion of whether or not picture degradation is present. For
38、picture assessment according to this method, the colour bar pattern according to ITU-R BT.801-1 is first converted to a suitable colour space, preferably grey. From each colour bar, a rectangular section is taken into which a rectangular test window is positioned. The test window is divided into col
39、umn segments (see Figure 1). To reliably detect picture degradation, the test window is rotated by a constant angular increment of 2 until 180 is attained. For picture degradation in the form of lines, the test window segments will, in the case of one of the angles measured, be aligned approximately
40、 parallel to the interference lines, thus producing a significant deviation from average signal values. As already mentioned, an average value or column sum is determined for each segment, and the deviation from a reference value is calculated. In addition, a regression line over all column sums is
41、formed, and the square offset of each column sum from the regression line is calculated. If the sum of the square offsets of the column sums exceeds the corresponding value determined for a reference picture, a superimposed pattern or moir pattern is detected. The position and size of the test windo
42、w, or the test window diagonal, should be selected such that, for any angular position of the test window, all pixels of the test window are located within the same colour bar of the test pattern, i.e. within the homogeneous area of the colour bar. This excludes impairment of results by influences f
43、rom the cross-colour region. After a 180 rotation, the test window is shifted vertically, i.e. parallel to the borders of the colour bar section, by a length increment of half the test window height. In its new position, the test window is again rotated by 180, and a measurement is performed for eac
44、h angular increment. By repeatedly shifting the test window within the colour bar section, virtually the complete colour bar is covered. TR CISPR 29 IEC:2004(E) 7 Rectangular sectionTest windowSegmentFigure 1 Colour bar pattern with test elements for detection of analog picture degradation The above
45、 procedure is repeated for each colour bar of the test pattern. To cover the complete colour bar pattern, the cross-colour regions between the bars also have to be analysed. For this purpose, the cross-colour regions are divided into vertical segments of seven pixels in height. For each segment, the
46、 position of the colour transition edge and its deviation are determined. Evaluation is performed on the assumption of a Gaussian distribution of the colour transition edge in each segment over a defined number of reference pictures, preferably 20 and based on a confidence interval of five times the
47、 standard deviation V. Picture degradation is present if the position of colour transition in a segment is found to be outside the confidence interval of the corresponding reference segment.5.2 Algorithm for loss of luminance and contrast As described under 5.1, the colour bar pattern is converted t
48、o a suitable colour space, preferably grey. Any change in luminance or contrast directly affects the grey level, so this type of degradation can be reliably identified. The algorithm detects grey-level errors if the grey level deviates by a minimum of r5 grey tones from the grey level of the stored
49、reference picture based on a quantisation of 8 Bit (256 grey tones). 5.3 Algorithm for loss of colour Colour errors are identified by checking the hue of each colour contained in the colour bar pattern. To this effect, the test window is additionally converted to another colour space, preferably HSL. The algorithm detects colour errors if the hue deviates by a minimum of r10from the value of the stored reference picture. 5.4 Algor
