Development of Softcopy Environment for Primary Color Banding Visibility Assessment Byungseok Min*, Zygmunt Pizlo**, and Jan Allebach* *School of Electrical and Computer Engineering **Department of Psychological Sciences Purdue University, West Lafayette, IN Research supported by Hewlett-Packard Company

Outline Motivation Development of hardcopy environment for banding discrimination Development of softcopy environment Verification of the softcopy environment Conclusion

Past Studies on Banding Assessment Cui et al.(2001): measurement of monochrome banding threshold in inkjet printers Bang et al.(2003): monochrome banding discrimination in hardcopy environment Arslan et al.(2005): monochrome banding discrimination in softcopy environment Chen et al.(2004): softcopy environment for sinusoidal artificial banding of secondary color

Motivation 1-D space  beginning with primary colorant Hardcopy Image with intrinsic banding Paper process direction Softcopy Image with intrinsic banding Constant image OPC drum velocity variation Why we need softcopy ? A color is represented by 3-D signal, but the banding perception is described in 1-D space  beginning with primary colorant The same banding perception in both hardcopy and softcopy environment 4

Generation of Extrinsic Banding in Hardcopy Environment 1-D representation Extracting banding profile Intrinsic banding image Line pattern image 1-D Banding profile pixel (1~200 cpi) Printer Scanner Curve Projection & Filtering dE Scanner Banding Level Random phase Printer Σ Extrinsic Banding Image Extrinsic banding level PWM coding

1-D Representation of Color Banding Signal Test patch Scanned patch Printer process direction Scanner Line pattern (PWM code) Line pattern definition Scanner calibration projected point of * * if Yk > Yavg * projected point of if Yk < Yavg *

How Do We Print Extrinsic Banding ? 85 83 84 87 84.5 83.5 22 63 20 21 24 22 63 20 21 24 …. paper process direction PWM line code 1-D banding profile(ΔC) PWM index Extrinsic banding Exploit sub-pixel addressability of the laser beam in the scan direction to perform PWM

How pulse-width modulation (PWM) works with laser electrophotography Normally, we think of a monochrome laser EP printer as rendering a binary image, in which each pixel is either black or white. However, as suggested by the architecture diagram shown on the right, we can switch the laser beam on and off for a fraction of the width of each pixel in the scan direction. For example, we can assign an 8-bit PWM code to each pixel. The most significant 2 bits determine the justification mode (left, centered, right, and split). And the 6 least significant bits provide 64 sub-pixel pulse widths (0 = no pulse, 63 = full width pulse). The figure to the right does not include the center-justification mode.

Outline Motivation Development of hardcopy environment Development of softcopy environment Haploscopic matching method Appearance mapping function in adapted XYZ space Verification of softcopy environment Conclusion

Softcopy Environment Overview Extrinsic banding generation 1-D representation Extrinsic Banding Image Scanned Patch Background Image + + - Scanner Curve Projection & Filtering Back- projection Σ Σ + Back- projection Extrinsic Banding Image Brief explanation Adapted Space of Observer Banding Level β Color Appearance Mapping Function Inverse Monitor Curve Spectro- radiometer Calibration Color appearance matching process

Appearance Matching Experiment (Haploscopic Matching Setup) Front view Lighted room (Fluorescent) Viewing Box (Fluorescent) Memory matching method works with monochrome Dark surround Independent adaptation of each eye for each viewing condition 11

Another view of haploscopic matching set-up

Appearance Matching Procedure Fine adjustment Gray adaptation (1 min) Rough selection Observe hardcopy with left eye and softcopy with right eye Adjust a color by changing hue, chroma, and lightness

Device Characterization Scanned image XYZX-Rite XYZspectro XYZsoftcopy Scanner calibration Appearance mapping function Viewing booth Spectrophotometer Barco monitor Spectroradiometer Mapping function Delta E Avg: 0.38 Max: 1.33

Adapted XYZ space Viewing condition 1 Lighted surround / paper Von-Kries adaptation model XH, YH, ZH XHa, YHa, ZHa Measured by spectro- radiometer Mapping function Xsa, Ysa, Zsa Xs, Ys, Zs * Viewing condition 2 Dark surround / monitor * : Hunt-Pointer-Estevez transformation

Appearance Mapping Function Experiment result Appearance mapping function Fitting error Avg deltaE: 2.13 Max deltaE : 2.98

Outline Motivation Development of hardcopy environment Development of softcopy environment Verification of softcopy environment Banding level matching experiment Discrimination threshold (DL) experiment Conclusion

Softcopy Environment Validation 1: Banding Level Matching Hardcopy (Lighted surround) Softcopy (Dark surround) 3 different levels of banding are matched by memory matching method Memorize the banding level of the hardcopy in the lighted surround Match the banding level on the monitor in the dark surround

Banding Matching Experiment Result Total 12 subjects participated in the experiment For each subject, three pairs of Linear Regression model Hypothesis - Slope should be statistically equal to 1.0 in 95% confidence interval - Intercept should be statistically equal to 0 Result + intercept Parameter Standard error 95% lower limit 95% upper limit Slope 0.088 0.988 1.345 Intercept 0.036 0.009 0.165 The interval includes 1.0 The Intercept is almost 0

Softcopy Environment Validation 2: Difference Threshold (DL) Comparison Hardcopy (Lighted surround) GUI Softcopy (Dark surround) To remove individual variability The same experiment is performed in both environment Method of constant stimuli is used Probit analysis is used to estimate DL Environment Hardcopy Softcopy Average DL 0.103 0.091 95% C.I. ± 0.028 ±0.016

Discrimination Experiment Result Two-way ANOVA analysis - Two factors: Subject(# of subjects) and Environment (Hard/Softcopy) Hypothesis - H0: The environment factor does not affect the result - The null hypothesis is rejected if P-value is less than 0.05 Result by SAS program Source DF Mean Square F-value P-value Environment 1 0.00047 0.60 0.4546 Subject 11 0.00111 1.41 0.2903 No difference - between two environments - among 12 subjects

Conclusion and Future Work We Successfully developed and verified our softcopy environment for banding discrimination DL of 0.09 suggests that the banding magnitude should be reduced by 9% to yield noticeable reduction in the banding visibility Future work Color banding assessment on secondary colors

Question ?