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      In this tutorial, Telescope Live tutor Nik Szymanek introduces the latest version of GraXpert, a free AI-powered tool for astrophotographers. Nik demonstrates how to process a dataset of NGC 660 using GraXpert’s intuitive workflow, including gradient correction, deconvolution, and denoising. Key steps include:

      Interface Overview and Setup:

      - Install GraXpert, download required AI models, and prepare your image with basic cropping to remove dithering artefacts.

      Gradient Removal with AI Background Extraction:

      - Use the AI mode for a simplified alternative to PixInsight’s DBE, with sigma and saturation controls for fine-tuning.

      Deconvolution and Denoising:

      - Apply AI-based deconvolution and denoising with recommended starting values, using preview modes to compare results.

      Saving and Exporting:

      - Save the final image in 32-bit FITS or 16-bit TIFF format, optionally retaining the applied stretch for further editing in Photoshop or Affinity Photo.

      Nik’s walkthrough shows how GraXpert can streamline core astrophotography tasks with minimal complexity.

      22 Apr 2025

      Beginner-Friendly Gradient Removal and Denoising with GraXpert

      Nik Szymanek
      • Parts
        ............................................................................................................................
        1 Video
      • Duration
        ............................................................................................................................
        10m
      • Image type
        ............................................................................................................................
        Deep Sky Imaging
      • Difficulty level
        ............................................................................................................................
        Beginner
      • Category
        ............................................................................................................................
        Techniques
      • Tier
        ............................................................................................................................
        Standard
      • Software used
        ............................................................................................................................