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 ..........................................................................................................................................................................................................................
CHI-5 Nikon 200 F/2
Camera ..........................................................................................................................................................................................................................
FLI ML16200
Location ..........................................................................................................................................................................................................................
El Sauce Chile
Date of observation ..........................................................................................................................................................................................................................
Jan - Feb 2022
Filters ..........................................................................................................................................................................................................................
Astrodon Ha (3nm), SII (3nm), OIII (3nm)
Processing ..........................................................................................................................................................................................................................
PixInsight, Photoshop, Lightroom, Topaz AI DeNoise
Credits ..........................................................................................................................................................................................................................
piAutoIntegrate.js
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