previous post I showed some of the beautiful new images of Pluto from New Horizon’s mission, coloured using the new Matplotlib perceptual colormaps:
More recently I was experimenting with Principal Component Analysis in scikit-learn, and one of the things I used it for was compression of some of these Pluto images. Below is an example of the first two components from the False Color Pluto image:
You can take a look at the
. There are of course better ways of Python code available on this Jupyter Notebook compressing images, but this was a fun way to play around with PCA.
In a follow-up post I will use image registration and image processing techniques to reproduce from the raw channels NASA’s
Psychedelic Pluto Image.
Posted in Geoscience, Planetary science, Programming and code, Python, Tutorial |
Tagged machine learning, New Horizons, PCA, planetary science, Pluto, Python, scikit-learn |
new, perceptual MatplotLib colormaps…..
Here’s one stunning, recent Truecolor image of Pluto from the New Horizons mission:
Original image: The Rich Color Variations of Pluto. Credit: NASA/JHUAPL/SwRI. Click on the image to view the full feature on New Horizon’s site
Below, I recolored using two of the new colormaps:
Recolored images: I like Viridis, by it is Inferno that really brings to life this image, because of its wider hue and lightness range!
Posted in Color, color-2, Geoscience, Planetary science, Python, VIsualization |
Tagged color, colour, Inferno, Matplotlib, NASA, New Horizons, Pluto, Python, Truecolor, Viridis, visualisation, visualization |