Transcript Perceptual Evaluation of Colour Gamut Mapping Algorithms (.vnd.ms-powerpoint)

Perceptual Evaluation of Colour
Gamut Mapping Algorithms
Fabienne Dugay
The Norwegian Color Research Laboratory
Faculty of Computer Science and Media Technology
Gjøvik University College, Gjøvik, Norway
[email protected]
http://www.colorlab.no
Master’s thesis presentation, 7th June 2007
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Outline
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Introduction
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Gamut mapping algorithms
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Gamut mapping algorithms (GMAs)
Experimental setup
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Colour Gamuts
Goal
Psychophysical evaluation
Images, Media, Viewing conditions
Results & Analysis
Conclusion and perspectives
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Introduction
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Gamut = range of reproducible colours of a device or range of
colours in a image
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Printers have smaller gamut than monitor
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How to reproduce those out-of-gamut colours ?
Gamut mapping algorithms (GMAs): ensure a good
correspondence of overall colour appearance between the
original and the reproduction
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Goal
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Evaluate the performance of selected GMAs on real images
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Influence of the test images
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Influence of the observers
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Influence of the experiments
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Gamut mapping algorithms
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Non-spatial GMAs
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The image is treated globally
Gamut compression or gamut clipping
Spatial GMAs
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Depend on the neighbourhood pixels
Balance both colour accuracy and preservation of details
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Experimental methods
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No metrics have been proved to be efficient for evaluating the
performance of GMAs
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Psychophysical tests with a panel of observers
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20 observers (11 “experts” & 9 “non-experts”)
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Asked about the accuracy of the reproductions
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The raw data from the experiments are treated statistically to
obtain z-scores
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Experimental methods
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20 test images with various characteristics
Original: sRGB image on calibrated monitor
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Experimental methods
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Reproductions on a inkjet printer with plain paper
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Experimental methods
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5 GMAs:
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HPminDE: Hue preserving minimum delta E clipping
SGCK: lightness and chroma compression, hue preserving
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Zolliker: recovers local contrast, preserves lightness and
saturation
Kolås: hue and edge preserving spatial GMA
Gatta: preserves hue and local relationships
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Experimental methods
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Viewing conditions follow the CIE guidelines:
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Simulated D50 lights for the prints
D65 white point for the monitor
Viewed in a neutral grey room with lights at their minimum
intensity
Original and reproduction images have the same size and a white
border
Neutral grey background
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Experimental methods
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Two psychophysical experiments
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With printed reproductions
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Ranking (rank the 5 reproductions from the most to the least accurate
to the original displayed on the monitor)
With simulated printed reproductions on screen
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Pair comparison (choose the most accurate reproduction in a pair)
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Results
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Results from the ranking experiment
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Analysis
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HPminDE: not an accurate GMA
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Kolås, SGCK and Gatta not significantly different
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A spatial and non-spatial GMAs seen as accurate
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Results
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Results from the ranking experiment, for each image and GMA
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Analysis
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Dependant on the test images
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Analysis
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But strong correlation between the % of out-of-gamut colours
and the number of distinguishable GMAs
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Strong correlation between the % of out-of-gamut colours and
the perceived difficulty to rank the reproductions
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Gamut mapping especially important when dealing with small
gamut devices
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Results
Dependant on the observers
Accuracy scores for all images, by experts and non experts
0.8
0.6
0.4
0.2
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HPminDE
Accuracy
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SGCK
Zolliker
-0.2
Kolaas
Gatta
Experts
Non-experts
-0.4
-0.6
-0.8
-1
-1.2
-1.4
GMAs
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Analysis
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Different results between the two groups
Stronger consensus among the experts
All GMAs have tight scores for the non-experts
Experts look at the best rendering of details
Non-experts look more at the saturation
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Results
Dependant on the experiments
Comparison paper and screen, all observers
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0.2
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Accuracy
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HPminDE
SGCK
Zolliker
Kolaas
Gatta
Paper
Screen
-0.2
-0.4
-0.6
-0.8
GMAs
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Analysis
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Globally comparable results
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Some other parameters:
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Random of the scenes
Accuracy or preference?
Other media/printers
LCD/CRT monitors
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Conclusion and perspectives
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None GMA is significantly better than all the others
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HPminDE (clipping) is not perceived as an accurate GMA
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The choice of a efficient GMA may depend on the image, the
media, the target customer and an universal GMA seems
inexistent
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Meta-analysis to join the results of the different GMA
evaluations?
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Thank you for you attention
Any questions?