NoiseXTerminator is a fast and easy-to-use AI-powered noise reduction tool specifically for astrophotography. While AI-based noise reduction solutions exist for general photography, they were not trained on astronomical images. As a result, they often mangle stars and invent detail that simply isn’t there. NoiseXTerminator was trained exclusively on deep-sky astrophotography, so its neural network is “familiar” with stars and the types of detail we see in our photos.
NoiseXTerminator is available as a plug-in for both PixInsight and Photoshop. The Photoshop version also works with Affinity Photo.
✅ Affinity Photo
NoiseXTerminator is available as a plug-in process module for PixInsight and Photoshop. The photoshop version also works with Affinity Photo.
NoiseXTerminator requires a computer with a modern CPU having “AVX” instructions required to run neural networks. Older CPUs, and even some modern stripped-down CPUs in mini-PCs and lightweight laptops lack AVX instructions and are not supported. Request a trial before purchasing to make sure NoiseXTerminator will work on your machine.
Neural network computations can benefit greatly from GPU acceleration. On Macs, GPU acceleration of NoiseXTerminator is automatic, leveraging the “CoreML” software library provided by Apple. Performance is particularly fast on recent Apple silicon based Macs (M1, M2, etc.) due to their extremely performant built-in GPU and neural engine hardware.
On Windows and Linux machines, GPU acceleration takes a bit more effort.
- PixInsight 1.8.8-9 or later, or
- Photoshop CS4 or later (64-bit only), or
- Affinity Photo 1.0 or later
- MacOS 10.15 (Catalina) or later
- GPU/Neural Engine recommended for fast performance, but not required. External GPUs are not supported.
- Apple silicon neural engines and GPUs (e.g., M1, M2) are supported natively
- Windows 10 or later
- Modern CPU capable of running neural networks (AVX, SSE instruction set extensions)
- Linux (PixInsight only)
- Ubuntu 18.04 or later, or equivalent (glibc 2.27 or later required)