RCW 57 4 panel mosaic

RCW 57 4 panel mosaic
0

RCW 57 4 panel mosaic

11800 by 8800 pixel mosaic built using PI Gradient Merge, SHO colour processing with PS, dynamic depth of field using Lightroom and some final noise reduction using Topaz AI DeNoise and compressed down from a 1.25 Gb Tiff to an 8Mb Jpg
SPECIFICATIONS
Telescope ..........................................................................................................................................................................................................................
Telescope
CHI-5 Nikon 200 F/2
Camera ..........................................................................................................................................................................................................................
Camera
FLI ML16200
Location ..........................................................................................................................................................................................................................
Location
El Sauce Chile
Date of observation ..........................................................................................................................................................................................................................
Date of observation
Jan - Feb 2022
Filters ..........................................................................................................................................................................................................................
Filters
Astrodon Ha (3nm), SII (3nm), OIII (3nm)
Processing ..........................................................................................................................................................................................................................
Processing
PixInsight, Photoshop, Lightroom, Topaz AI DeNoise
Credits ..........................................................................................................................................................................................................................
Credits
piAutoIntegrate.js
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