StarNet++ is a software tool widely used in astrophotography to remove stars from astronomical images. By isolating stars, it allows astrophotographers to focus on processing the details of deep-sky objects like nebulae or galaxies without being affected by the bright stars in the image.
Star Removal: The primary purpose of StarNet++ is to create a "starless" version of an astronomical image, which is often useful for enhancing details in nebulae and other deep-sky objects.
Standalone and Plug-in Versions:
It can be used as a standalone application on operating systems like Windows, macOS, and Linux.
It is also available as a plug-in for popular astrophotography tools like PixInsight.
Support for Monochrome and RGB Images: StarNet++ works with both monochrome images (grayscale) and color images (RGB).
Ease of Use: The software typically accepts images in TIFF or FITS format and requires minimal configuration.
StarNet++ employs a machine learning model trained to distinguish stars from other image features. This allows it to effectively subtract stars from the image while preserving the background features, such as nebulae or galaxies.
Prepare your astrophotography image in a suitable format (e.g., TIFF or FITS).
Input the image into StarNet++.
Run the tool to generate a starless version of the image.
Use the starless image in your astrophotography workflow for further processing.
Optionally, recombine the starless image with the stars for final adjustments.
Enhanced Image Processing: Isolating stars lets astrophotographers focus on faint details of nebulae and galaxies, improving their appearance.
Artistic Effects: Some astrophotographers prefer the aesthetic of starless images.
Layered Editing: Reintroducing stars after processing the background allows for a more controlled and polished final image.
Simplifies complex image editing tasks by automating star removal.
Preserves image quality and faint details better than manual star removal methods.
Freely available and accessible to amateur and professional astrophotographers.
Star Retention: In some cases, small stars or star artifacts may remain in the processed image.
Computationally Intensive: Processing large images, especially in RGB, can be time-consuming and resource-intensive.
Learning Curve: New users may require some practice to achieve optimal results.
You can find StarNet++ on its official GitHub page or other astrophotography forums. Detailed instructions for installation and usage are typically included in the distribution package.