The Owl Nebula in Ursa Major

M97 is about 2.8 arcmins in diameter, and has a faint halo surrounding it. The halo is mostly OIII, with a slight Ha signature in the brightest part. This is a bicolor Ha/OIII image. a>

Exposure: Total exposure time about 24.3 hours, 34:39 x 20 minutes Ha:OIII, bin 1x1. Data collected from January to April 2019.
Light pollution: Bortle 7-8 (white zone, NELM about 4.5)
Seeing: Average FWHM of subs around 2.3 arcsecs
Image scale at capture: 0.6 arcsecs/pixel = f/5.7
Scale of presentation: 0.84 arsecs/pixel (70% scale)

Equipment:
Scope: C11 (standard, not Edge) with Celestron 0.63 reducer
Mount: Paramount MX+, connected via ASCOM Telescope Driver 6.1 for TheSkyX, with MKS 5000 driver 6.0.0.0
Camera: SXVR-H694, connected via SX ASCOM driver 6.2.1.17140 (SX 1.2.2 also installed)
Filter wheel: Atik EFW2 with 7x1.25 carousel and Artemis 2.4.3.0 driver
Filters: Astrodon 5nm Ha/SII, 3nm OIII, Type IIe LRGB
Rotator: Optec Pyxis 2", connected via Andy Galasso's 0.4 driver (Optec Pyxis Rotator AG)
Focuser: Rigel Systems GCUSB nStep motor with driver version 6.0.7 on stock Celestron focuser
OAG: Orion Thin OAG
Guide cam: Lodestar (first generation). 4 second exposures
Automation SW: Sequence Generator Pro 3.0.3.169
Guide SW: PHD2.6.6, connected to guide cam via native SXV driver
ASCOM: ASCOM 6.3.0.2831
Platesolving: PlateSolve 2, failover to local Astrometry.net 0.19 server
Collimation: Metaguide 3, using ASI120MM connected via ZWO Direct Show driver 3.0.0.2
Processing Workflow by Workspace in PixInsight 1.86

1. Calibration
BatchPreProcessing with flats, darks and bias, using Cosmetic Correction with master dark
Blink to preview and reject a few frames
Subframe Selector to confirm selections and weight by FWHM and SNR
StarAlign to register frames

2. Stack and Mure Denoise
Image Integration on each channel
Mure Denoise on each channel
Dynamic Crop

3. Linear Processing
Dynamic Background Extraction
(skipped Deconvolution – it added nothing to the image except noise)

4. Stretching of Core
Core: Histo Trans
Local Histogram Equalization
HDR Transform
Halo: HistoTrans x 3
TGV Denoise
Aggressive Multiscale Median Transform to remove lumpiness in background, using an inverted and blurred luminance frame as a mask to protect highlights

5. Channel Blending
PixelMath
Core: mapped channels to:
Red: Ha
Green: OIII*0.85
Blue: OIII*1.15 + Ha*0.15
Halo: used above as color, then used OIII as luminance
SCNR to shift halo color toward blue
Curves to desaturate color in halo
Background: used halo images, mapped HOO for color, 50/50 Ha:OIII as luminance

6. Blend Core and Halo
Photoshop: select blown-out core in the halo image, expand it a few pixels
Filter>Distort>Pinch to shink the halo out of the image
Curves to darken core
Pixinsight: Use PixelMath max(Core, Halo) to combine images
Photoshop: layer core and halo onto background with mask

7. Final
Final Histogram Transformation
sRGB
Save as JPG