An Interactive Perception Based Model for Characterization of Display Devices 1 Institute of Computer Graphics and Algorithms Vienna University of Technology, Austria 2 Grup de Gràfics de Girona, Universitat de Girona, Spain Attila Neumann 1, Alessandro Artusi 1, Georg Zotti 1, László Neumann 2, Werner Purgathofer 1

Attila TU Wien Motivation

Attila TU Wien Device Characteristics Different color spaces Different color reproduction technology

Attila TU Wien Motivation By human observation Reliable characterization of display By a measuring device

Attila TU Wien Colors of the display Additive RGB channels Additive RGB channels characteristics separable by channel characteristics separable by channel Side effects Side effects slight cross effects (stronger for LCD) slight cross effects (stronger for LCD) environmental effects environmental effects Pipeline Pipeline graphics card [byte] graphics card [byte] display device [voltage] display device [voltage] eye [luminance] eye [luminance] brain [color appearance] brain [color appearance]

Attila TU Wien Colors of the display Additive RGB channels Additive RGB channels characteristics separable by channel characteristics separable by channel Side effects Side effects slight cross effects (stronger for LCD) slight cross effects (stronger for LCD) environmental effects environmental effects Pipeline Pipeline graphics card [byte] graphics card [byte] display device [voltage] display device [voltage] eye [luminance] eye [luminance] brain [color appearance] brain [color appearance] voltage luminance (by channel)

Attila TU Wien Tone Reproduction Curve byte luminance (by channel)

Attila TU Wien Previous Work – Models for the TRC Models with small number of parameters Models with small number of parameters Linear functions: GOG, version 1.x IEC GGO, version 2.x 3.x IEC GOGO Linear functions: GOG, version 1.x IEC GGO, version 2.x 3.x IEC GOGO [Berns et al. 1993] [Berns et al. 1993] Non linear functions: LIN-LIN2, LOG-LIN, LOG-LIN2, LOG-LOG, LOG-LOG2 Non linear functions: LIN-LIN2, LOG-LIN, LOG-LIN2, LOG-LOG, LOG-LOG2 [Post and Calhoun 1989], [Katoh and Deguchi 1998] [Post and Calhoun 1989], [Katoh and Deguchi 1998] S-curve (S-shaped function): handling cross effect (mainly at LCD monitors) S-curve (S-shaped function): handling cross effect (mainly at LCD monitors) [Kwak MacDonald 2001], [Miyake et al. 1990] [Kwak MacDonald 2001], [Miyake et al. 1990] Arbitrary number of parameters Arbitrary number of parameters Masking model (spline) Masking model (spline) [Tamura et al. 2003] [Tamura et al. 2003]

Attila TU Wien Our method Basic measurement steps Basic measurement steps Human observations Human observations Errors are tolerable and can be reduced Errors are tolerable and can be reduced Relative measurements Relative measurements Finding the input values (instead of output values) Finding the input values (instead of output values) Automatic stop and setup of basic steps Automatic stop and setup of basic steps Optimization (definition of the TRC function) Optimization (definition of the TRC function) Generic function is achieved Generic function is achieved A relative curve is defined A relative curve is defined Passes requirements of human perception Passes requirements of human perception

Attila TU Wien Basic step Similar to classic gamma applet

Attila TU Wien Basic step Similar to classic gamma applet

Attila TU Wien Basic step Similar to classic gamma applet

Attila TU Wien Basic step Similar to classic gamma applet

Attila TU Wien Basic step Similar to classic gamma applet

Attila TU Wien Basic step Similar to classic gamma applet

Attila TU Wien Basic step

Attila TU Wien Basic step

Attila TU Wien Basic step

Attila TU Wien The math problem No direct measurements for f(x) No direct measurements for f(x) only relative measurements ((x 0, x 2, r), x 1 ) only relative measurements ((x 0, x 2, r), x 1 ) diff = y 1 -y 1 = r f(x 0 )+(1-r) f(x 2 )-f(x 1 ) depends on the unknown y=f(x) TRC diff = y 1 -y 1 = r f(x 0 )+(1-r) f(x 2 )-f(x 1 ) depends on the unknown y=f(x) TRC Optimum criteria for the y=f(x) TRC Optimum criteria for the y=f(x) TRC y-y expressions are to be minimized y-y expressions are to be minimized instead of the usual y i =f(x i ) i.e. diff i =0 !! instead of the usual y i =f(x i ) i.e. diff i =0 !! other targets can be defined other targets can be defined smoothness condition smoothness condition repeatable measurements repeatable measurements

Attila TU Wien The compound minimum problem f(i) [i=0..255] are unknown Measurement conditions: M(j) = r j f(low j )+(1-r j ) f(high j )-f(back j ) [j=1..N] M(j) = r j f(low j )+(1-r j ) f(high j )-f(back j ) [j=1..N] Smoothness conditions: S(i) = f(i+1)+f(i-1)-2 f(i) [i=1..254] Convex quadratic minimum problem F = i=1..N m j M(j) 2 + i= s i S(i) 2 Minimized by a conjugate gradient method

Attila TU Wien Additional questions Setting the coefficients Setting the coefficients weights m and s control the behaviour of f weights m and s control the behaviour of f Definition of triplets (low i, high i, ratio i ) Definition of triplets (low i, high i, ratio i ) predefined triplets predefined triplets optimal next triplet, stop criterium optimal next triplet, stop criterium defined by the local and/or overall reliability defined by the local and/or overall reliability LOG-LOG coordinate system LOG-LOG coordinate system Seems more natural Seems more natural power function transformed to linear function power function transformed to linear function Additional degree of freedom Additional degree of freedom But: numerical and algorithmic problems But: numerical and algorithmic problems

Attila TU Wien Results CRT monitor CRT monitor R,G,B results by our method R,G,B results by our method Compared to simple power function Compared to simple power function Perceivable deviation Perceivable deviation Derivative can deviate upto !

Attila TU Wien Results Compared to spectro- photometer measurements Compared to spectro- photometer measurements Absolute/relative data conversion Absolute/relative data conversion Accuracy acceptable Accuracy acceptable Mutual verification Mutual verification

Attila TU Wien Conclusion, future work + Human based TRC measurement Cheap solution Cheap solution New implicit approach New implicit approach + Complements existing methods Traditional gamma applet Traditional gamma applet Masking model [Tamura 2003] Masking model [Tamura 2003] ? Missing absolute luminance values By channel, cross effects By channel, cross effects contrast value by human observation contrast value by human observation ? Preferring LOG-LOG type functions Instead of spline-like (LIN-LIN) functions Instead of spline-like (LIN-LIN) functions ? Combining with other methods (LIN-LIN, etc)

Attila TU Wien Acknowledgements Supported by Supported by European Union: RealReflect Project European Union: RealReflect Project IST IST Realtime Visualization of Complex Behaviour in Virtual Prototyping Realtime Visualization of Complex Behaviour in Virtual Prototyping Spanish Government Spanish Government TIC C03-01 TIC C03-01 Helped with implementation Helped with implementation Benjamin Roch (TU Vienna, Austria) Benjamin Roch (TU Vienna, Austria) Wolfgang Deix (TU Vienna, Austria) Wolfgang Deix (TU Vienna, Austria)

Attila TU Wien Thank you for your attention