colour.py assembles a viewable image from whatever a session actually
has: LRGB, RGB with a synthetic luminance, SHO in the Hubble palette,
HOO, or a single filter as greyscale. Nothing is assumed about which
filters exist, which is the whole point - three of the four archived
sessions have no luminance channel.
The background fit takes the lesson from Centaurus A, where a plane
fitted around a large galaxy absorbed 17.9 ADU/px of its halo. The
excluded region is now sized from the data: the ellipse grows until it
contains most of the flux above sky, so it suits a galaxy filling the
frame and a small nebula equally, and only a plane is ever fitted, never
a flexible surface. One mask is derived from the deepest channel and
applied to all of them, so the fit cannot shift the colour balance.
Broadband and narrowband need opposite stretches, which cost a round to
discover. Broadband channels share the luminance's midtone, preserving
the real brightness ratios that keep star colours honest. Narrowband
cannot: the lines differ enormously in strength, so a shared stretch
renders the entire nebula in whichever colour Ha was mapped to. Each
narrowband channel is now stretched to its own sky target instead.
Green suppression is applied to broadband only. On a narrowband palette
it would fight the palette, green being a deliberate channel assignment
rather than an artefact.
Measured rather than eyeballed, because the SHO render looked wrong by
eye and was not: both palettes put the sky at 0.098 against a 0.10
target and neutral to within 0.004. What differs is the data. NGC 2030's
brightest pixels reach 0.80 to 0.87, the Tarantula's only 0.23 to 0.33,
because that session is a single 60 second frame per filter - three
minutes in total. A correct pipeline renders nearly empty data as a
nearly empty frame.
