Making Sense of Satellite Data, an Open Source Workflow: Color Correction with GIMP

Auto-adjusted SkySat image on a clear day (June 21, 2017 (left)) and on a day with scattered clouds (May 7, 2017 (right)). Images ©2018 Planet Labs, Inc. CC-by SA 4.0.
Snow comes and goes on Mount St. Helens, but the scene remains the same. Sentinel-2 images from May to October of 2017 via Planet’s timelapse tool.
Uniform color correction across multiple scenes allows seamless stitching of data, and works well over large areas. Images ©2018 Planet Labs, Inc. CC-by SA 4.0.
With global color adjustments many landscapes lack contrast—forests remain dark and desrts are uniformly bright. Images ©2018 Planet Labs, Inc. CC-by SA 4.0.

Color-correction with GIMP

Before getting started, I highly recommend reading either or both of my previous tutorials on color correction—How to Make a True-Color Landsat Image and A Hands-On Guide to Color Correction. They both use Photoshop (decidedly not open source) but I include background on my workflow and even more rationalization for a labor-intensive process that doesn’t scale. Rather than repeating myself, I’ll get into the specifics of using GIMP.

Pre-processed SkySat image of Boston. ©2018 Planet Labs, Inc. CC-by SA 4.0.

Step 1: Tonal Adjustment

Tonal adjustment (balance between bright and dark) of the image adapts the linear scaling of a scientific instrument to a human’s nonlinear perception. In short, it changes data into pictures.

Here’s where to find GIMP’s Curves palette.
Step 1: tonal adjustment.

Step 2: Black Point Color Adjustment

Next, you’ll need to change the relative brightness of the Red, Green, and Blue channels individually, to compensate for the blue tinge imparted by the atmosphere. In practice, I tend to leave the shadows a little bit blue, and make the highlights a little bit yellow—a mapmaker’s trick I learned from National Park Service cartographer Tom Patterson. Removing atmospheric effects entirely makes images look unnatural.

Step 2: black point adjustment.

Step 3: White Point Color Adjustment

The final step is to modify the highlights to appear more natural. Human eyes inherently adjust surrounding colors based on surfaces we think are white (remember The Dress?), so it’s important that white areas are white. White point adjustments are similar to black point adjustments, but instead of moving the bottom of the curve to the right, move the top of the curve to the right. This will make the bright region of each channel brighter.

Step 3: white point adjustment.
Pre-processed image of the Alps on July 4, 2017, from Sentinel 2B.

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Robert Simmon

Robert Simmon

Data Visualization, Planet Labs. Ex-NASA. Blue Marble, Earth at Night, color.