Perceptually Uniform Colour Maps
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This website presents a collection of perceptually uniform colour maps.
Many colour maps provided by vendors have highly uneven perceptual contrast. Colour maps may have sections of low perceptual contrast that prevent you from seeing significant features in your data. They may also have points of locally high colour contrast leading to the perception of false anomalies in your data when there are none.
The colour maps shown above are rendered on a test image consisting of a sine wave superimposed on a ramp function. The amplitude of the sine wave is progressively reduced to zero at the bottom of the image.
What we should see is the sine wave uniformly visible across the image from left to right. We also want the contrast level, the distance down the image, at which the sine wave remains discernible to be uniform across the image.
At the top of the test image the sine wave height from peak to trough is 10% of the total data range. It is not unusual for the sine wave pattern to completely disappear in parts of some vendor colour maps. At the bottom of the image we just have a linear ramp which simply reproduces the colour map. Given that the underlying data is a featureless ramp we should not perceive any identifiable features across the bottom of the image.
What difference does this make?
On the left is the result of rendering an aeromagnetic image of the Yilgarn region in Western Australia with the default colour map of a widely used geophysics package. On the right is the same data rendered with the perceptually uniform colour map CET-L20.
The vendor map exhibits a large perceptual dead zone at green, a smaller dead zone at red, and false features at cyan and yellow. A lot of very expensive data has been corrupted and lost!
Organisation of the Colour Maps
The colour maps are organised according to the attributes: Linear, Diverging, Rainbow, Cyclic, Isoluminant, and Colour Blind.
Linear colour maps are intended for general use and have colour lightness values that increase or decrease linearly over the colour map's range. Such maps are also known as sequential maps.
Diverging colour maps are suitable where the data being displayed has a well defined reference value and we are interested in differentiating values that lie above, or below, the reference value. The centre point of the colour map will be white, black or grey. It should be noted that, in general, diverging colour maps have a small perceptual flat spot at the centre. The exception being linear-diverging maps which avoid this problem.
Rainbow colour maps are widely used but often misused. It is suggested that they be avoided because they have reversals in the lightness gradient at yellow and red which can upset a viewer's perceptual ordering of the colours in the colour map. However, they are attractive and perhaps can have a legitimate use where the main aim is to differentiate data values rather than communicate a data ordering. I believe the rainbow colour maps presented here have minimal badness though they do have localised perceptual flat spots at yellow and red.
Cyclic colour maps have colours that are matched at each end. They are intended for the presentation of data that is cyclic such as orientation values or angular phase data. They require particular care in their design (the standard colour circle is not a good map).
Isoluminant colour maps are constructed from colours of equal perceptual lightness. These colour maps are designed for use with relief shading. On their own these colour maps are not very useful because features in the data are very hard to discern. However, when used in conjunction with relief shading their constant lightness means that the colour map does not induce an independent shading pattern that will interfere with, or even hide, the structures induced by the relief shading. The relief shading provides the structural information and the colours provide the data classification information.
Colour Blind colour maps. These are not designed to be merely 'colour blind safe'. These maps have been constructed to lie within either the 2D model of protanopic/deuteranopic colour space, or the 2D model of tritanopic colour space. Hopefully by working within these colour spaces people who are colour blind will be able to share a common perceptual interpretation of data with those who have normal colour vision. It also ensures maximal use of the available colour spaces, and allows chroma and lightness to be properly used in the design of colour maps. I would value any feedback on the usefulness, or otherwise, of these maps. For more information you can view a conference presentation describing the design of these colour maps.
View the Gallery to see the full collection of colour maps.
- MATLAB code that was used to generate and analyse these colour maps.
- Julia Package for the generation and analysis of colour maps.
If you find this work useful please cite this site, colorcet.com, and the paper:
Peter Kovesi. Good Colour Maps: How to Design Them.
arXiv:1509.03700 [cs.GR] 2015
I am indebted to Tom Horrocks for his help in generating the colour maps for ArcGIS.
The aeromagnetic image of the Yilgarn region in Western Australia was generated from data that is the property of Fugro Airborne Surveys Pty Ltd.
Centre for Exploration Targeting
School of Earth Sciences
The University of Western Australia