Episode 4: Deconvolution and BlurXTerminator, revealing the hidden detail in the stars

Hello again,

In this fourth episode of the PixInsight image processing tutorial, we take a decisive step toward improving the detail and sharpness of our astronomical images. After calibrating and balancing the color, it's time to recover the finer structure of our nebulae, galaxies, and clusters.

We'll begin by exploring the classic Deconvolution process, one of PixInsight's most powerful and delicate tools. To harness its full potential, we'll learn how to prepare the necessary elements:

DynamicPSF will allow us to model the true shape of the stars in our image and precisely define the point dispersion function. StarMask and RangeMask will be used to protect the brightest or most sensitive areas, ensuring a natural, artifact-free result.

Once you've mastered this technique, we'll move on to one of the most revolutionary additions of recent years: BlurXTerminator, developed by Russell Croman. This AI-powered tool offers a fast and controlled way to restore sharpness and contrast while maintaining the integrity of astronomical data.

In this episode we'll analyze when to use each method, how to combine them in a balanced way, and what precautions to take to obtain fine results without over-processing the image.

In the next episode, which I'll publish later this week, we'll continue refining our processing workflow with techniques focused on enhancement and noise reduction. We'll look at MaskedStretch, a controlled way to stretch the image while preserving bright areas; explore LocalHistogramEqualization to improve local contrast without losing naturalness; apply NoiseXTerminator, Russell Croman's AI tool for efficient noise removal; and work with ACDNR, a PixInsight classic that remains incredibly useful for smoothing backgrounds and refining details.

Don't miss it! We're getting closer and closer to revealing all the depth and color hidden in our deep-sky data.

✨ See you among the pixels and the stars. — Alberto Pisabarro