ExtensionToolset is a collection scripts to support image processing and analysis in PixInsight. The goal is to offer solutions for common processing challenges as well as offer meaningful insights about your images, location, equipment and sky conditions.
BTM (Brightness and Transparency Meter)
The BTM allows users to measure the night sky brightness and transparency based on a single calibrated image and minimal metadata.
Besides the image itself, the only information required are the exact time and location of the image acquisition and an astrometric solution for the image.
The night sky brightness will be calculated in magnitudes/arcsec^2, the transparency will be expressed as both a percentage value and an extinction rate in magnitude. All values include comprehensive estimates of their measurement errors.
These values, in combination with the next feature, make it easy for users to compare locations and imaging conditions between nights or with other users.
USQCalculator
Computes the Unified Sky Quality (USQ) index from brightness and transparency values. The USQ index, ranging from 0 to 100 for typical conditions, provides an intuitive, SNR-proportional score that allows easy comparison of imaging conditions. Required inputs can be obtained via the BTM script.
For example, an image taken under conditions with a USQ index of 60 will have 3x the SNR of an image taken under conditions with a USQ index of 20, all other things being equal.
This makes it easy for users to compare their locations and different nights.
The USQ index will be explained in more detail later in this document.
GradientStrength
Analyzes the strength of gradients across a set of images. The strength of a gradient is defined by both the magnitude and the standard deviation of a large scale feature map.
This allows users to select an ideal subset of images for the generation of a LocalNormalization reference image, enabling more effective reduction of gradients in the final integrated images.
Note: The selection of images with this script is purely based on the gradient strength, and not on SNR. You should verify whether this matches your goals or not. Do not use this metric blindly.
AdditiveColorCalibration
Performs a high-accuracy additive color calibration of RGB images based on a background preview.
Stars are automatically rejected from the background sample.
This is making it easier to find suitable background regions, even in crowded fields, and still perform accurate color calibration, even in hard cases.
Note: This script is intended to be used after applying a multiplicative color calibration, such as PhotometricColorCalibration or SpectrophotometricColorCalibration. It is, in no way, a replacement for these processes, especially not for the high accuracy multiplicative color calibration they perform.
ExtensionToolsetOverview
Shows this current document, briefly describing all features of the ExtensionToolset and providing the release notes.
After installation, all scripts are accessible under:
Scripts → ExtensionToolset → [Script name]
Each script includes comprehensive documentation through the tooltips of all UI controls.
Since the USQ index is a new concept, I want to explain it in more detail.
Most of the time, it is hard to compare the sky quality for imaging purposes across different nights or locations. Clearly, darker skies are better, but how much better are they actually, and how much better is a dark sky if it is not as transparent as a brighter sky?
The USQ index solves this problem by combining both metrics of quality into a single index. The USQ index is a value between 0 and 100, where 0 is the worst possible sky quality and 100 is the best possible sky quality. It is proportional to the SNR of a well‑exposed image taken under these conditions.
In practice, this means that if you have calculated a USQ index of 20 for location A and a USQ index of 60 for location B, then you can expect a well‑exposed image taken at location B to have an SNR of 60 / 20 = 3 times the SNR of a well‑exposed image taken at location A with all other conditions being equal. That means that, at location A, you have to expose 3^2 = 9 times as long for the same SNR compared to location B.
Of course, there are some limitations here, but I have tried to make them as small as possible:
I have the strong hope that the USQ index can be established as a standard measure for night‑sky quality, improving the community’s ability to compare locations and nights with each other, fostering a better understanding of the quality of images by other astrophotographers and what can be achieved by changing locations.
If you encounter any issues or have suggestions, feel free to reach out to me through any of the forums where I have published the initial announcement. Feedback and feature requests are always welcome!