Spectrophotometric Color Calibration
Warning
The calibration of the colors by photometry must imperatively be carried out on a linear image whose histogram was not yet stretched. Otherwise, the photometric measurements will be wrong and the colors obtained without guarantee of being correct.
Spectrophotometric Color Calibration (Ctrl + Shift + C) is the newest method of color calibration available in Siril. This method uses the extensive spectral data available in the Gaia DR3 online catalogue [GaiaDR3]. Owing to the data volumes, this method is only available when an internet connection is available: there is no offline version of the Gaia DR3 xp_sampled spectrum database that Siril can use.
Warning
As SPCC relies on connectivity to the Gaia Archive, note that when the archive is offline for maintenance or due to a fault, Siril's SPCC functionality will not be available. Fortunately the archive is normally very reliable, however a status indicator is built into the SPCC dialog. The archive status is checked when the dialog starts up and can be re-checked by clicking the status button.
SpectroPhotometric Color Calibration dialog window.
Tip
What's the difference between SPCC and PCC? When should I use one rather than the other? SPCC is a more accurate version of PCC and renders the latter obsolete. SPCC takes your setups sensor and filters into account. As a result, the color produced is much closer to "reality". The example in the picture below illustrates the difference in results.
Comparison between PCC (left) and SPCC (right): click to enlarge. (Courtesy of Ian Cass)
How it Works
SPCC requires knowledge of your sensor and the RGB filters you use. These are provided through an online repository which Siril will sync, either automatically at startup or manually when required. Sensor and filter information is updated via the same synchronization method as used for the online scripts repository. (This means that as data on new filters or sensors becomes available it can be added to the repository without requiring an update to the application.)
In the GUI you select your sensors and filters from the widgets in the SPCC dialog. Don't worry if there isn't an exact match for your equipment, just pick the closest option, or the appropriate default option. You also need to select a white reference. The default reference is the Average Spiral Galaxy reference which is suitable for a wide range of astrophotographic scenes, however there is an extensive range of galaxy and star types to choose from. The Sun's spectral type is G2(iv) so if you want to balance your image using sunlight as a white reference, you would pick Star, type G2(iv) from the list.
SPCC then uses the stellar spectra in Gaia DR3 and knowledge of your imaging sensor and filters to compute for each star in the catalogue that matches a star detected in the image by Siril the expected flux in each color channel. It then compares this with the actual flux measured in each channel using Siril's photometric capabilities.
Given the sensor and filter knowledge, SPCC computes the expected flux in each channel for the specified white reference. A robust linear fit is obtained to give the best fit of catalogue to image R/G and B/G flux ratios for each star and for the white reference. This fit is used to derive correction coefficients which are applied multiplicatively to each channel, resulting in spectrophotometrically accurate color channels.
Your image must be plate solved for SPCC to work: if it is not already, this should be done with the dedicated tool. It is important to make sure that the plate solving information is correct, as some software is known to add inaccurate WCS data to images.
Graphical Interface
Selection of Sensor In order to select your sensor, ensure that the mono / OSC toggle button is set correctly. You will then see the appropriate dropdown to choose from the available sensors.
Selection of Filters SPCC can operate in two modes.
The default mode is broadband operation. In this mode, the Narrowband mode check box should be unchecked. You can choose either red, green and blue filters (for composited images made with a mono sensor) or OSC filters, for example light pollution filters, for images made with an OSC sensor.
By checking the Narrowband mode check box, you enable narrowband mode. This is intended either for images composited from narrowband filters used with a mono sensor or for images made using an OSC sensor with a dual, tri-band or quad band narrowband filter. In this mode the available controls change, and for each color channel you enter the nominal wavelength and bandwidth of the filter passband. For ultra-narrowband mono filters the passband may be as little as 3nm; for a quadband OSC filter like the Altair QuadBand V2 the passbands may be as much as 35nm. Note that for a HOO composition where two channels are set to the same data, the nominal wavelength and bandwidth should be set equal in the SPCC interface too.
Calibrated HOO image. Image by Cyril Richard.
Tip
Some manufacturers specify a center wavelength and FWHM. It is fine to use the FWHM as the bandwidth: these filters have very sharp cutoffs.
Warning
Don't expect to retrieve the Hubble palette for SHO imaging using the wavelengths of the SII, \(\mathrm{H}\alpha\) and OIII filters respectively. The result will be an image with a huge green cast. This is easily explained by the fact that the SII emission line is much fainter than that of hydrogen, and the SPCC gives a representation of real intensities. But this is not the case in the Hubble palette. In fact, manual color calibration will give better results.
SHO image calibrated by SPCC compared to the same, manually calibrated one. The entire nebula was taken as a white reference during manual calibration. Image by Cyril Richard.
Selection of DSLR Low Pass Filter (LPF) DSLRs contain a low-pass filter (sometimes also called a 'hot mirror'. These reduce transmittance at wavelengths of interest to astronomers (Ha at 656nm and S-II at 674nm). If the selected OSC is a DSLR, a dropdown will be provided from which you can the appropriate LPF profile. Options exist for stock LPFs as well as astro-modified LPFs and an ideal Full spectrum filter model for if the LPF has been removed altogether.
Selection of White Reference SPCC requires an absolute white reference spectrum. The default is Average Spiral Galaxy and the source spectra used to create this white reference are taken from the SWIRE templates [SWIRE] in a manner consistent with other astrophotography software providing the same white reference. A wide range of other white references is available, covering the full range of galaxy and star classifications [Stellar]. If you wish to use sunlight as your white reference, you would choose the white reference Star, type G2(iv) as the Sun is a type G2(iv) star.
Graphs showing white reference data from spiral galaxies. At around 350 nm, the Average Spiral Galaxy data become identical to the Sc galaxies, which are also a good representation of the white reference.
NGC 4414 is a great example of a Sc-type galaxy, the type closest of the average spiral galaxy used as white reference by default. Image Credit: NASA, ESA, W. Freedman (U. Chicago) et al, & the Hubble Heritage Team (AURA/STScI), SDSS; Processing: Judy Schmidt.
Tip
Summary of Stellar Spectral Classifications Stellar classifications have two parts, a Morgan-Keenan type and a Luminosity index.
The first part of the spectral classification (G2 in the case of the Sun) takes one of the following letters: O, B, A, F, G, K, M. O represents extremely hot blue stars, while M represents cool red stars. The sun is roughly in the middle of the spectrum. The number represents intermediate cases, for example a B5 star is halfway between type B and type A.
The second part of the spectral classification is the luminosity index ranging from i to v. Stars with luminosity index i are supergiants, whereas stars with luminosity index v are dwarfs. Main sequence stars such as the sun have a luminosity index of iv.
Graphs showing white reference data for a set of two different star classes, G and K.
Difference in color calibration depending on the choice of white reference. On the left, an M-type star, on the right the average spiral galaxy. Please note that the data are linear, and only an autostretch has been applied to the visualization.
Atmospheric Correction Siril's SPCC supports atmospheric correction. When imaging from Earth we image through the atmosphere. This does not have perfect transmittance and therefore acts as another, non-optional, filter in the imaging chain between the sensor and the astronomical object. Whether or not to correct for this is an artistic choice each astrophotographer must make, but the option is provided.
Theory
Atmospheric extinction arises from several sources. The most important are:
Rayleigh scattering. This is the elastic scattering of light by particles that are small compared with the wavelength of light. The strong wavelength dependence of the Rayleigh scattering (\(\approx λ^{−4}\)) means that shorter (blue) wavelengths are scattered more strongly than longer (red) wavelengths.
Aerosol scattering. This is scattering of light by particles that are larger than the wavelength of light. This is quite variable but (in the absence of significant short term dust or smoke effects) relatively spectrally flat and less significant than Rayleigh scattering.
Molecular absorption lines.
Siril models only Rayleigh scattering. This is the most important contribution in most atmospheric conditions, and is highly predictable making it easy to model without requiring the user to provide complex data.
The formula for the Rayleigh transmittance of the atmosphere as a function of wavelength \(\lambda\) nm, observer height \(H\) m and pressure \(p\) hPa is:
\(\tau_R(\lambda, H, p) = \left( \frac{p}{1013.25} \right) \left( 0.00864 + 6.5 \times 10^{-6} \cdot H \right) \lambda^{-(3.916 + 0.074 \lambda + \frac{0.050}{\lambda})}\).
Under normal circumstances aerosol scattering has a roughly flat response in the visible region. This changes in specific conditions, for example when there is high atmospheric smoke particle concentration after wildfires or, in parts of Europe, when Saharan dust is carried into the atmosphere. However these effects are very difficult to model accurately as they depend on the concentration of sand or smoke particles in the atmosphere at the time. Siril therefore does not model this effect.
The main molecular absorption lines in the visible spectrum are the Chappuis stratospheric ozone bands and the Fraunhofer B molecular oxygen absorption line. However the Fraunhofer B line is very narrow and does not have a significant effect on overall calibration. The Chappuis bands are broad but with a low peak absorption, with a much smaller overall impact than Rayleigh scattering. Molecular absorption bands are not currently modelled in Siril.
When selecting the Atmospheric correction check box, the following options become available:
Observer Height. This allows setting of the observer height, which is used in the Rayleigh extinction calculation. Set this to the altitude of your observatory above sea level. Some capture software sets the FITS header
SITEELEVcard: if this is present, the height from this card will be used, otherwise the value is editable and defaults to 10 m.Atmospheric pressure. This allows setting atmospheric pressure at the time of observation. For convenience it can be specified as sea level pressure (as provided by weather forecasts) or as local pressure (as measured by a barometer at the observatory). In case you are unsure, the default is standard atmospheric pressure at sea level (1013.25 hPa).
Theory
If the pressure is provided as a sea-level pressure measurement, the local pressure at the observer's height is calculated according to the barometric formula:
\(P(h) = P_0 \left( 1 - \frac{L h}{T_0} \right)^{\frac{g M}{R L}}\),
where:
\(L = 0.0065~\text{K}/\text{m}\) (Temperature lapse rate),
\(T_0 = 288.15~\text{K}\) (Sea level standard temperature),
\(g = 9.80665~\text{m}/\text{s²}\) (Acceleration due to gravity),
\(M = 0.0289644~\text{kg}/\text{mol}\) (Molar mass of Earth's air),
\(R = 8.3144598~\text{J}/(\text{mol}·\text{K})\) (Universal gas constant).
Airmass. This is not an editable parameter but shows the airmass that will be used in the calculations. It is obtained, in order of preference, from the
AIRMASSFITS header card; by calculation using theCENTALTFITS header card; or as a last resort by using the average zenith angle of all parts of the more than 30° above the horizon. The tooltip shows which source the used figure is based on.Theory
If the
AIRMASSheader is unavailable the calculation used to derive airmass from zenith angle is calculated in accordance with [Young1994]:\(X(z) = \frac{1.002432 \cos^2 z + 0.148386 \cos z + 0.0096467}{\cos^3 z + 0.149864 \cos^2 z + 0.0102963 \cos z + 0.000303978}\).
The interface allows you to view details of the selected sensor, filter and white reference using the Details button next to each combo box. From the details information box that this brings up you also have the option to plot the Quantum Efficiency (for sensors) or transmittance (for filters) or relative photon count (for white references) against wavelength. A Plot All button is also available in the main SPCC dialog which allows you to see the responses of all your filters and your sensor and the white reference spectrum all plotted together.
Plotting all the responses of all your filters and your sensor and the white reference spectrum all plotted together
When you are happy, click Apply and SPCC will run. It will cache catalogue data but the first time you apply it to an image it will take a few seconds to perform the online catalogue searches and retrieve the source and spectral data. SPCC will then be applied to the image. Additional plots showing the linear fit of the catalogue Red / Green and Blue / Green to image Red / Green and Blue / Green ratios.
By default, Siril outputs graphs showing the fits used in the process. In this example the magnitude was limited to 17.
Tip
How do I process L-RGB images? We recommend that you process them as normal RGB images. In fact, the L filter generally has very good transmission in the visible range and therefore has little influence on image colorimetry.
Tip
For images taken with an OSC sensor, we recommend using Bayer Drizzle to recover image colors. This ensures more accurate colors as shown in the following image.
SPCC applied identically to the same image. On the left, conventional demosaicing using the VNG algorithm; on the right, the Bayer Drizzle technique. A dominant green hue is clearly visible on the conventionally demosaiced image. Note that the VNG algorithm was chosen for this example because the effects explained here are more pronounced. However, in Siril, the default demosaicing algorithm is RCD. Click to enlarge image.
SPCC filter and sensor database
SPCC is based on the provision of data on various filters, sensors and white references. This database is free, and we are counting on the community to help us grow it to benefit as many users as possible. The database and instructions on how to improve it can be found here.
Saved Preferences
As most users are likely to do most of their imaging with one setup, or maybe two, it would be tedious to reselect the sensor and filters each time. The user choices are therefore automatically remembered when set and restored next time the tool is used, even if Siril is closed and restarted in between. This works using the preferences system but there is no need to use the preferences dialog to remember the set sensor and filters, it is done automatically.
The chosen white reference is not remembered: the default Average Spiral Galaxy is a suitable choice for most astronomical scenes, and alternative white references would normally be set for a specific image to draw out a particular aspect of the color.
Siril command line
spcc [-limitmag=[+-]] [ { -monosensor= [ -rfilter= ] [-gfilter=] [-bfilter=] | -oscsensor= [-oscfilter=] [-osclpf=] } ] [-whiteref=] [ -narrowband [-rwl=] [-gwl=] [-bwl=] [-rbw=] [-gbw=] [-bbw=] ] [-bgtol=lower,upper] [ -atmos [-obsheight=] { [-pressure=] | [-slp=] } ]
spcc_list { oscsensor | monosensor | redfilter | greenfilter | bluefilter | oscfilter | osclpf | whiteref }
References
Vallenari, A., et al. "Gaia Data Release 3-Summary of the content and survey properties." Astronomy & Astrophysics 674 (2023): A1. 99(613), 191.