Perceptual Evaluation of Colour Gamut Mapping AlgorithmsFabienne Dugay

The Norwegian Color Research Laboratory

Faculty of Computer Science and Media Technology

Gjøvik University College, Gjøvik, Norway

fabiennedugay@wanadoo.frhttp://www.colorlab.no

Master’s thesis presentation, 7th June 2007

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Outline

Introduction Colour Gamuts Goal

Gamut mapping algorithms Gamut mapping algorithms (GMAs)

Experimental setup Psychophysical evaluation Images, Media, Viewing conditions

Results & Analysis Conclusion and perspectives

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Introduction

Gamut = range of reproducible colours of a device or range of colours in a image

Printers have smaller gamut than monitor 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

Evaluate the performance of selected GMAs on real images

Influence of the test images

Influence of the observers

Influence of the experiments

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Gamut mapping algorithms

Non-spatial GMAs The image is treated globally Gamut compression or gamut clipping

Spatial GMAs Depend on the neighbourhood pixels Balance both colour accuracy and preservation of details

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Experimental methods

No metrics have been proved to be efficient for evaluating the performance of GMAs

Psychophysical tests with a panel of observers 20 observers (11 “experts” & 9 “non-experts”)

Asked about the accuracy of the reproductions

The raw data from the experiments are treated statistically to obtain z-scores

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Experimental methods

20 test images with various characteristics Original: sRGB image on calibrated monitor

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Experimental methods

Reproductions on a inkjet printer with plain paper

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Experimental methods

5 GMAs:

HPminDE: Hue preserving minimum delta E clipping SGCK: lightness and chroma compression, hue preserving

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

Viewing conditions follow the CIE guidelines: 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

Two psychophysical experiments

With printed reproductions 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 Pair comparison (choose the most accurate reproduction in a pair)

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Results

Results from the ranking experiment

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Analysis

HPminDE: not an accurate GMA

Kolås, SGCK and Gatta not significantly different

A spatial and non-spatial GMAs seen as accurate

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Results

Results from the ranking experiment, for each image and GMA

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Analysis

Dependant on the test images

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Analysis

But strong correlation between the % of out-of-gamut colours and the number of distinguishable GMAs

Strong correlation between the % of out-of-gamut colours and the perceived difficulty to rank the reproductions

Gamut mapping especially important when dealing with small gamut devices

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Results

Dependant on the observersAccuracy scores for all images, by experts and non experts

-1.4

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

HPminDE SGCK Zolliker Kolaas Gatta

GMAs

Ac

cu

rac

y

Experts

Non-experts

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Analysis

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 experimentsComparison paper and screen, all observers

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

HPminDE SGCK Zolliker Kolaas Gatta

GMAs

Acc

ura

cy

Paper

Screen

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Analysis

Globally comparable results

Some other parameters: Random of the scenes Accuracy or preference? Other media/printers LCD/CRT monitors

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Conclusion and perspectives

None GMA is significantly better than all the others

HPminDE (clipping) is not perceived as an accurate GMA

The choice of a efficient GMA may depend on the image, the media, the target customer and an universal GMA seems inexistent

Meta-analysis to join the results of the different GMA evaluations?

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Thank you for you attention

Any questions?