Software to automatically measure Jupiter and its moons in astrophotography images
Asked 6/14/2016
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I have a large set of astrophotography images of Jupiter and the Galilean moons, and I want to automate measuring Jupiter’s center and the moons’ distances from it across many frames. The goal is to estimate orbital distances and periods from the image data rather than manually marking each object in an editor.
Is there software or a practical workflow for this kind of image analysis? Ideally I’d like a method that can detect bright objects, find their centroids accurately, and process many images in batch.
Originally by Photography Stack Exchange contributor. Source · Licensed CC BY-SA 4.0
Photography Stack Exchange contributor
10y ago
2 Answers
1
If you have some programming skills, OpenCV has all the functionality you'd need to write a program to analyse your images. For example you would likely perform some denoising before using circle detection, or bounding circles creation.
This tutorial might give you a good head start and has the advantage of using Python which might be more accessible than C++.
Originally by user50096. Source · Licensed CC BY-SA 4.0
user50096
10y ago
0
Generated from our catalog & community — verify before relying on it.
Yes. A practical approach is to use image-analysis software or a small scripting workflow rather than measuring by hand.
Common suggestions are:
- OpenCV: good for automated processing, including denoising, blob detection, circle detection, and finding object centers.
- ImageJ: useful for detecting bright blobs and measuring their centroids with less coding.
- Python astronomy tools such as FITS readers (for astronomy image formats) if your camera saves FITS files.
A typical workflow would be:
- Preprocess each image to reduce noise.
- Detect the bright objects (Jupiter and the moons).
- Compute each object’s centroid rather than guessing its center manually.
- Identify which moon is which across frames.
- Convert pixel distances to angular/physical distances using your telescope/camera image scale.
If you’re comfortable coding, Python is a good choice because it gives access to OpenCV and astronomy libraries. If you want something more turnkey, ImageJ is worth trying first. In short: centroid-based automated measurement is the right method, and tools like OpenCV, ImageJ, and Python/FITS libraries are well suited to it.
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