Pixinsight tricks

Image integration tricks

For WBPP script:

  1. in order to use multiple nights and group dark, bias, light etc by night rename folder that contain each night like “Night 1”, “Night 2” etc…
    folders can be anything not necessarly “Night X” than you keywords to group by night adding “NIGHT” keyword
  2. To separate Darks even more use exposre tolerance and lower it down on the Darks tab

Basic DeepSky Algorythm

  1. start with Script > Batch Processing > Weightedbakchprocessing
  2. Open result folder from NINA and select autocropped images
  3. Select output folder
  4. Start Batch processing it might take a while, if it is new installation of pixinsight you might need to install NVIDIA
    support
  5. After the processing open _drizzle_autocrop files
  6. Rename files to match filters, just makes it easier later
  7. Appy dynamic crop to all files, this makes it easier to extract background later
  8. Add Images to image container, makes it easier to batch process
  9. Use grxpert for background extraction, select all images in container and run script
  10. Apply BlurXTerminator to all images in container
  11. Use channel combination to create RGB image
  12. use image solver to plate solve the image
  13. Apply spectrophotometric color calibration, don’t forget to select right filers settings
  14. Use statistical stretch to stretch the image, both rgb and light
  15. remove stars from the RGB and light with StarX
  16. Combine light and rgb with LRGBcombination
  17. Use curves to adjust the gradients
  18. Add stars back with PixelMath plugin: apply formula ~((~rgb)*(~stars))

SOH DeepSky Algorythm

  1. As usual start with Script > Batch Processing > Weightedbakchprocessing
  2. Open result folder from NINA and select autocropped images
  3. Select output folder
  4. Notice that there is a exposure tolerance that can be set in Dark Files, set it lower for perfect results
  5. After the processing open _drizzle_autocrop files
  6. Rename files to match filters, just makes it easier later (SOH in this case)
  7. Appy dynamic crop to all files, this makes it easier to extract background later
  8. Add Images to image container, makes it easier to batch process
  9. Run BlurXTerminator
  10. If you Drizzled you images use Integer resample before NoiseXTerminator
  11. Run NoiseXTerminator
  12. Run GRXPert for background extraction, select all images in container and run script
  13. (a) alternativly use gradient correction
  14. Apply statistical stretch to all images in container
  15. Use LRGBcombination, put H into L and G, O into B and S into R
  16. After creation new colored image apply StarXTerminator
  17. To remove green from the stars inver, apply SCNR and invert again
  18. Open NarrowbandNormalization script and run it with SHO settings
  19. Use color masks with curves to enchance the colors, use convolution to blur the mask