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R2-29 report ppt/Bp © METAS - 1 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices Dr. Peter Blattner Swiss Federal Office of Metrology and Accreditation METAS R2-29 (2nd report) Characterization of Imaging Luminance Measurement Devices (ILMDs) video photometer, imaging photometer, CCD luminance meter
R2-29 report ppt/Bp © METAS - 2 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices Conclusion of the 1st report from metrological point of view ILMDs are complex systems (traceability, software validation, etc) the parameters defined by CIE are not sufficient to characterize ILMDs there is some interest from industry to have some guidelines on how characterize ILMDs Prepare a Technical Report on methods for the characterization of imaging luminance measurement devices TR:
R2-29 report ppt/Bp © METAS - 3 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices Progress since the last meeting Discussions with several users and manufacturers: more products/manufacturers on the market increasing number of devices were sold more quantities that are measured/deduced -> new applications some inconsistencies are found between different users in some specific cases
R2-29 report ppt/Bp © METAS - 4 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices Quantities derived with ILMDs (1) Luminance distributions -> Display, lamps, filaments -> tunnel lightening © TechnoTeam GmbH
R2-29 report ppt/Bp © METAS - 5 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices Quantities derived with ILMDs (2) geometrical parameters (angles,…) “partial” vertical illuminance Physiological glare
R2-29 report ppt/Bp © METAS - 6 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices Quantities derived with ILMDs (3) - >Analysis of complex sceneries © TechnoTeam GmbH Illuminance distributions UGR
R2-29 report ppt/Bp © METAS - 7 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices Quantities derived with ILMDs (4) luminance coefficients - > Analysis of non uniform surfaces angular dependant luminance distribution -> near field goniophotometry (color coordinates) - > colorimetry
R2-29 report ppt/Bp © METAS - 8 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices Discussions with users Some differences in measurements of the same sample were found between different users having different systems (differences up to 20%) Explication: - Measurement task: measurement of luminance distribution of displays with LED backlights. This is inherit to ILDMs: partial filtering is not applicable and there is only a limited number of glass fiters available. © TechnoTeam GmbH One has to life/deal with that problem ! The situation is even worse when grayfilters have to be used Most users are „happy“ with the system they were using However: best possible f 1 ‘ that can be done on ILMDs is in the order of 2.5%
R2-29 report ppt/Bp © METAS - 9 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices Discussions with manufacturers There is a limited interest from industry to have some internationally agreed guidelines on how to characterize ILMDs. The characterization problems are solved mostly within the industry. Some procedures are part of the “in-house” knockledge of the manufactures. One manufacturer is strongly in favor for a CIE-TC (and would like to chair a possible TC).
R2-29 report ppt/Bp © METAS - 10 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices Close R2-29, new TC to generate a „User‘s guide“ Close R2-29, new TC to generate guide for characterizing ILDMs Close R2-29, no action (yet) Some of the problems are not specific to ILDMs but to LDMs Only a few number of manufacturers are concerned How to go on? What to do with the parameters in CIE that are not applicable or missing?
R2-29 report ppt/Bp © METAS - 11 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices deviation of relative spectral responsivity from the V(l) function - > f 1 ‘ UV response, IR response -> u, r directional response -> f 2 (g) effect from the surrounding field -> f 2 (u) linearity error -> f 3 error of display unit -> f 4 temperature coefficient -> a fatigue -> f 5 modulated radiation -> f 7 polarization -> f 8 range change -> f 11 error of focus -> f 12 lower/upper frequency limit -> f l, f u properties of luminance meter as defined by CIE publication
R2-29 report ppt/Bp © METAS - 12 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices properties of video camera system number of pixels (total, effective, output) cell size frame rate shutter speed noise dynamic range photo response non-uniformity (PRNU) dark signal non-uniformity (DSNU) defective pixels optical imaging parameter (MTF, distortion, etc)
R2-29 report ppt/Bp © METAS - 13 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices CIE publication : inconsistencies, missing parameters gloss trap measurement field Examples: measurement of the effect of the surrounding field spatial homogeneity (shading: depends on aperture, focusing distance) cross talk between neighbor pixels (blooming, smearing,data compression, etc)
R2-29 report ppt/Bp © METAS - 14 maets metrology and accreditation switzerland R2-29 Characterization of imaging luminance measurement devices other problems associated with ILMDs timing problems (integration time : 0.01 msec - 1 sec) dark current (resp. drift of dark current), depends on temperature, position fixed aperture/ focus versus variable aperture/ focus image compression straylight dynamic range polarization and finally data acquisition, manipulation, and evaluation made by a computer. There is always a mathematical transformation between the luminance value and the pixel value, typically luminance(x,y,t) = (pxl (x,y,t) - dark(x,y) - dark(t)) * calibration * shading (x,y) * nonlinearity (pxl) luminance(x,y,t) = pxl (x,y,t) * calibration ideal: real:
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