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https://github.com/mycarta/pmkmp
Matlab function to create perceptual colormaps
https://github.com/mycarta/pmkmp
Last synced: about 2 months ago
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Matlab function to create perceptual colormaps
- Host: GitHub
- URL: https://github.com/mycarta/pmkmp
- Owner: mycarta
- Created: 2014-10-17T16:50:05.000Z (about 10 years ago)
- Default Branch: master
- Last Pushed: 2022-05-31T04:05:47.000Z (over 2 years ago)
- Last Synced: 2023-09-08T06:50:59.447Z (over 1 year ago)
- Language: Matlab
- Homepage: http://www.mathworks.com/matlabcentral/fileexchange/28982-perceptually-improved-colormaps
- Size: 5.44 MB
- Stars: 6
- Watchers: 4
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
PMKMP
=====
Matlab function to create perceptual colormaps, [as submitted on the Matlab File Exchange] (http://www.mathworks.com/matlabcentral/fileexchange/28982-perceptually-improved-colormaps).
Function and supporting files and images licensed under the terms of [BSD] (https://opensource.org/licenses/BSD-2-Clause) license.
>function map=pmkmp(n,scheme)
>PMKMP Returns perceptually balanced colormaps with rainbow-like colors
>PMKMP(N,SCHEME) returns an Nx3 colormap.
>usage: map=pmkmp(n,scheme);
JUSTIFICATION: rainbow, or spectrum color schemes are considered a poor
choice for scientific data display by many in the scientific community
(see for example reference 1 and 2) in that they introduce artifacts
that mislead the viewer. "The rainbow color map appears as if it’s separated
into bands of almost constant hue, with sharp transitions between hues.
Viewers perceive these sharp transitions as sharp transitions in the data,
even when this is not the casein how regularly spaced (interval) data are
displayed (quoted from reference 1). This submission is intended to share
the results of my work to create more perceptually balanced,
rainbow-like color maps. Please see output arguments section for descriptions.
arguments: (input)
scheme - can be one of the following strings:
'IsoL' Lab-based isoluminant rainbow with constant luminance L*=60
For interval data displayed with external lighting
'IsoAZ' Lightness-Chroma-Hue based isoluminant rainbow going
around the full Hue circle.
For azimuthal and phase data.
'LinearL' Lab-based linear lightness rainbow.
For interval data displayed without external lighting
100 perceptual
'LinLhot' Linear lightness modification of Matlab's hot color palette.
For interval data displayed without external lighting
100 perceptual
'CubicYF' Lab-based rainbow scheme with cubic-law luminance(default)
For interval data displayed without external lighting
100 perceptual
'CubicL' Lab-based rainbow scheme with cubic-law luminance
For interval data displayed without external lighting
As above but has red at high end (a modest deviation from
100 perceptual)
'Edge' Diverging Black-blue-cyan-white-yellow-red-black scheme
For ratio data (ordered, constant scale, natural zero)
n - scalar specifying number of points in the colorbar. Maximum n=256
If n is not specified, the size of the colormap is determined by the
current figure. If no figure exists, MATLAB creates one.
arguments: (output)
map - colormap of the chosen scheme
- IsoL is based on work in paper 2 in the reference section.
In both this paper and in several others this is indicated as the
best for displaying interval data with external lighting.
This is so as to allow the lighting to provide the shading to
highlight the details of interest. If lighting is combined with a
colormap that has its own luminance function associated - even as
simple as a linear increase this will confuse the viewer. The only
difference from the paper is that I changed the value of constant
luminance to L*=60 to make it brighter that the authors' example.
- IsoAZ is a Lightness-Chroma-Hue based isoluminant rainbow that
goes around the full Hue circle.For azimuthal and phase data.
Created with code snippet below. This is a modification from an example
by Steve Eddins on his Matlab central blog (reference 15). Steve had
lightness increasing while as hue changed. I hold the ligthness
constant instead to make the result isoluminant. I also use the
Colorspace transformations function instead of the Image Processing
Toolbox for the color conversion. Here's the code:
radius = 50; chroma
theta = linspace(0, pi/2, 256)'; hue
a = radius * cos(theta);
b = radius * sin(theta);
L = (ones(1, 256)*100)'; lightness
Lab = [L, a, b];
RGB=colorspace('RGB<-Lab',(Lab));
(needs Colorspace transformations from Matlab File Exchange)
www.mathworks.com/matlabcentral/fileexchange/28790-colorspace-transformations
- LinearL is a linear lightness modification of another palette from
paper 2 in the reference. For how it was generated see my blog post:
mycarta.wordpress.com/2012/12/06/the-rainbow-is-deadlong-live-the-rainbow-part-5-cie-lab-linear-l-rainbow/
- LinLhot is a linear lightness modification of Matlab's hot
color palette. For how it was generated see my blog post:
mycarta.wordpress.com/2012/10/14/the-rainbow-is-deadlong-live-the-rainbow-part-4-cie-lab-heated-body/
- CubicL too is based on some of the ideas in paper 2 in the
reference section but rather than using a linearly increasing
L* function such as the one used by those authors, I am
using a compressive or cubic law function for the increase in
L*. L* ranges between 31 and 90 in the violet to yellowish
portion of the colormap, then decreases to about 80 to get
to the red (please refer to figure L_a_b_PlotsCubicL.png).
The choice to start at 31 was a matter of taste.
I like having violet instead of black at the cold end of the
colormap. The latter choice was so as to have red and not
white at the warm end of the colorbar, which is also a
matter of personal taste. As a result, there is an inversion in
the L* trend, but I believe because it is a smooth one that
this is an acceptable compromise and the resulting
colormap is much of an improvement over the standard
rainbow or spectrum schemes, which typically have at least 3 sharp
L* inversions. Please run CompareLabPlotsUsingColorspace.m or see
figures: L_plot_for_CubicL_colormap.png, L_plot_for_jet_colormap.png,
and L_plot_for_spectrum_colormap.png for a demonstration
- CubicYF A fully perceptual version of the above in which I eliminated
the red tip at the high end. The work is described in papers 12 and 13.
I've uploaded 2 figures. The first, spectrum vs cubicYF.png, is a comparison
of lightness versus sample number for the spectrum (top left) and the
new color palette (bottom left), and also a comparison of test surface
(again the Great Pyramid of Giza)using the spectrum (top right)and
the new color palette (bottom right). The second figure
simulations color vision deficieny.png
is a comparison of spectrum and cubicYF rainbow for all viewers.
Left column: full color vision – for the spectrum (top left) and for the
cubeYF rainbow (bottom left). Centre column: simulation of Deuternaopia
for spectrum (top centre) and cubeYF rainbow (bottom centre).
Right column: simulation of Tritanopia for spectrum (top right) and
cubeYF rainbow (bottom right). For the cubeYF there are no
confusing color pairs in these simulations. There are several in the
spectrum. Please refer to reference 14 for vcolor vision deficiency
terminoligy. For how it was generated see my blog post:
http://mycarta.wordpress.com/2013/02/21/perceptual-rainbow-palette-the-method/
- Edge is based on the Goethe Edge Colors described in the book in
reference 3. In practice the colormap resembles a cold color map attached
to a warm color map. But the science behind it is rigorous and the
experimental work is based on is very intriguing to me: an alternative
to the Newtonian spectrum. This is not perceptually balanced in a
strict sense but because it does not have green it is perceptually
improved in a harmonious sense (refer to paper reference 10 for a review
of the concept of harmony in color visualization).
Example1: 128-color rainbow with cubic-law luminance (default)
load mandrill;
imagesc(X);
colormap(pmkmp(128));
colorbar;
Example2: 128-color palette for azimuthal data
a=0:8:360;
b = repmat(a,[46 1]);
imagesc(b);
colormap(pmkmp(128,'IsoAZ'));
colorbar;
See files examples.m, examples1.m, and example2.m for more examples
See files MakeLabPlotUsingColorspace.m and CompareLabPlotsUsingColorspace.m
for some demonstrations
See also: JET, HSV, GRAY, HOT, COOL, BONE, COPPER, PINK, FLAG, PRISM,
COLORMAP, RGBPLOT
Other submissions of interest
Matlab's new Parula colormap
http://blogs.mathworks.com/steve/2014/10/13/a-new-colormap-for-matlab-part-1-introduction/
Haxby color map
www.mathworks.com/matlabcentral/fileexchange/25690-haxby-color-map
Colormap and colorbar utilities
www.mathworks.com/matlabcentral/fileexchange/24371-colormap-and-color
bar-utilities-sep-2009
Lutbar
www.mathworks.com/matlabcentral/fileexchange/9137-lutbar-a-pedestrian-colormap-toolbarcontextmenu-creator
usercolormap
www.mathworks.com/matlabcentral/fileexchange/7144-usercolormap
freezeColors
www.mathworks.com/matlabcentral/fileexchange/7943
Bipolar Colormap
www.mathworks.com/matlabcentral/fileexchange/26026
colorGray
www.mathworks.com/matlabcentral/fileexchange/12804-colorgray
mrgb2gray
www.mathworks.com/matlabcentral/fileexchange/5855-mrgb2gray
CMRmap
www.mathworks.com/matlabcentral/fileexchange/2662-cmrmap-m
real2rgb & colormaps
www.mathworks.com/matlabcentral/fileexchange/23342-real2rgb-colormaps
ColorBrewer: Attractive and Distinctive Colormaps
http://www.mathworks.com/matlabcentral/fileexchange/45208-colorbrewer--attractive-and-distinctive-colormaps
Acknowledgements
For input to do this research I was inspired by:
ColorSpiral - http://bsp.pdx.edu/Software/ColorSpiral.m
Despite an erroneous assumption about conversion/equivalence to
grayscale (which CMRmap achieves correctly) the main idea is ingenious
and the code is well written. It also got me interested in perceptual
colormaps. See reference 5 for paper
For function architecture and code syntax I was inspired by:
Light Bartlein Color Maps
www.mathworks.com/matlabcentral/fileexchange/17555
(and comments posted therein)
For idea on world topgraphy in examples.m I was inspired by:
Cold color map
www.mathworks.cn/matlabcentral/fileexchange/23865-cold-colormap
To generate the spectrum in examples1.m I used:
Spectral and XYZ Color Functions
www.mathworks.com/matlabcentral/fileexchange/7021-spectral-and-xyz-color-functions
For Lab=>RGB conversions I used:
Colorspace transforamtions
www.mathworks.com/matlabcentral/fileexchange/28790-colorspace-transformations
For the figures in example 2 I used:
Shaded pseudo color
http://www.mathworks.cn/matlabcentral/fileexchange/14157-shaded-pseudo-color
For plots in CompareLabPlotsUsingColorspace.m I used:
cline
http://www.mathworks.cn/matlabcentral/fileexchange/14677-cline
For some ideas in general on working in Lab space:
Color scale
www.mathworks.com/matlabcentral/fileexchange/11037
http://blogs.mathworks.com/steve/2006/05/09/a-lab-based-uniform-color-scale/
A great way to learn more about improved colormaps and making colormaps:
MakeColorMap
www.mathworks.com/matlabcentral/fileexchange/17552
blogs.mathworks.com/videos/2007/11/15/practical-example-algorithm-development-for-making-colormaps/
References
1) Borland, D. and Taylor, R. M. II (2007) - Rainbow Color Map (Still)
Considered Harmful
IEEE Computer Graphics and Applications, Volume 27, Issue 2
Pdf paper included in submission
2) Kindlmann, G. Reinhard, E. and Creem, S. Face-based Luminance Matching
for Perceptual Colormap Generation
IEEE - Proceedings of the conference on Visualization '02
www.cs.utah.edu/~gk/papers/vis02/FaceLumin.pdf
3) Koenderink, J. J. (2010) - Color for the Sciences
MIT press, Cambridge, Massachusset
4) Light, A. and Bartlein, P.J. (2004) - The end of the rainbow?
Color schemes for improved data graphics.
EOS Transactions of the American Geophysical Union 85 (40)
Reprint of Article with Comments and Reply
http://geography.uoregon.edu/datagraphics/EOS/Light-and-Bartlein.pdf
5) McNames, J. (2006) An effective color scale for simultaneous color
and gray-scale publications
IEEE Signal Processing Magazine, Volume 23, Issue1
http://bsp.pdx.edu/Publications/2006/SPM_McNames.pdf
6) Rheingans, P.L. (2000), Task-based Color Scale Design
28th AIPR Workshop: 3D Visualization for Data Exploration and Decision Making
www.cs.umbc.edu/~rheingan/pubs/scales.pdf.gz
7) Rogowitz, B.E. and Kalvin, A.D. (2001) - The "Which Blair project":
a quick visual method for evaluating perceptual color maps.
IEEE - Proceedings of the conference on Visualization ‘01
www.research.ibm.com/visualanalysis/papers/WhichBlair-Viz01Rogowitz_Kalvin._final.pdf
8) Rogowitz, B.E. and Kalvin, A.D. - Why Should Engineers and Scientists
Be Worried About Color?
www.research.ibm.com/people/l/lloydt/color/color.HTM
9) Rogowitz, B.E. and Kalvin, A.D. - How NOT to Lie with Visualization
www.research.ibm.com/dx/proceedings/pravda/truevis.htm
10) Wang, L. and Mueller,K (2008) - Harmonic Colormaps for Volume Visualization
IEEE/ EG Symposium on Volume and Point-Based Graphics
http://www.cs.sunysb.edu/~mueller/papers/vg08_final.pdf
11) Wyszecki, G. and Stiles W. S. (2000) - Color Science: Concepts and
Methods, Quantitative Data and Formulae, 2nd Edition, John Wiley and Sons
12) Niccoli, M., (2012) - How to assess a color map - in:
52 things you should know about Geophysics, M. Hall and E. Bianco,
eds.
13) Niccoli, M., and Lynch, S. (2012, in press) - A more perceptual color
palette for structure maps, 2012 CSEG Geoconvention extended
abstract.
14) Color Blind Essentials eBook
http://www.colblindor.com/color-blind-essentials/
15) Eddins, S. (2006) - A Lab-based uniform color scale
http://blogs.mathworks.com/steve/2006/05/09/a-lab-based-uniform-color-scale/
Author: Matteo Niccoli
e-mail address: [email protected]
Release: 4.02
Release date: October 2014
Full research at:
http://mycarta.wordpress.com/2012/05/29/the-rainbow-is-dead-long-live-the-rainbow-series-outline/