Satellite trails can be a major headache when photographing deep space objects, especially during the winter months when many popular targets are affected. These streaks disrupt the clarity of your images, and understanding how to manage them is key to producing clean, polished astrophotography.
Coming to you from Peter Zelinka, this detailed video dives into why geostationary satellites are the main culprits behind those unsightly streaks in deep space photos. While Starlink satellites often take the blame, they’re less problematic because they move across the sky and are easier to eliminate during stacking. Geostationary satellites, on the other hand, remain in the same position relative to Earth, making them harder to remove. By enabling satellite tracking in Stellarium, you can visualize the problem areas in the sky and better plan your shots.
The video emphasizes the importance of using PixInsight’s Weighted Batch Pre-Processing (WBPP) tool to address this issue. By modifying the integration parameters, you can leverage settings like large-scale pixel rejection and the Windsorized Sigma Clipping algorithm to effectively remove these trails. This algorithm identifies inconsistencies between frames and eliminates them from the final stacked image. Adjusting the Sigma High value to 1.9 further refines this process, as highlighted in a helpful forum post referenced by Zelinka.
These adjustments are especially useful for objects like the Angel Nebula and the Witch’s Head Nebula, which tend to be plagued by satellite streaks. Zelinka demonstrates the process step by step, showing how these settings improve image quality by reducing unwanted artifacts. For those photographing dimmer targets, the video also underscores the importance of gathering ample data—20 to 40 hours if possible—for cleaner, more detailed results.
If you’re new to PixInsight, the learning curve can seem steep, but the video provides enough insight to help you get started with these tools. Check out the video above for the full rundown from Zelinka.
