Bernhard Hubl CEDIC 2009 Colour Calibration of RGB Images Advantages and disadvantages of different colour calibration methodes

Contents  Field Stars Calibration  G2 Star Calibration Procedure Disadvantages  B-V Calibration Workflow Experiences  Alternative Methodes  Summary

Why Colour Calibration?   Atmosphere Zenith distance Transparency   Telescope   Filters   Camera

White Balance  Average of field stars = white  Sunlight = white Stars with sun-like spectral type (G2) Stars with sun-like photometry (B-V)

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Field Stars Calibration  Assumption Average colour of bright field stars is white  Advantages Easy (e.g. AIP4Win) Independent of atmospheric extinction Works fine for galaxy fields  Disadvantages Open star clusters Interstellar extinction Bright nebulae

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Extinction

Workflow G2 Star Calibration Measurement of bright G2 star RGB weights in zenith Exposure of object in specific altitude Calculate extinction Corrected RGB- weights

When does the G2 calibration fail?  No measurement of a G2 star  Very low altitude of the object  Bad transparency (clouds, fog,..) Measurement of bright G2 star RGB weights in zenith Exposure of object in specific altitude Calculate extinction Corrected RGB- weights

Object exposures for G2 star calibration  Idea: Search for not saturated G2 stars  Two problems: Spectral type of faint stars is often unknown Reddening of G2 strars by interstellar dust.

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B-V Calibration  Idea: Peter Riepe & Harald Tomsik VdS Journal  Calibration uses the object image  Instead of spectral type -> photometry Comprehensive photometric data of faint stars Johnson-Cousins UBVRI filter system.

UBVRI Filter   U – Ultraviolet   B – Blue   V – Visual (Green)   R – Red   I – Infrared

Colour Index  = difference of the brightness measured through two different filters  e.g: B-V, V-R Sp. typeColourB-V [mag] SpicaB1Blue-0.23 DenebA2Blue-White+0.09 SunG2White+0.65 BetelgeuseM0Orange-Red+1.50

HR Diagram

Idea  Colour index of a G2 star without interstellar extinction: B-V=0.65 mag V-R=0.36 mag  Search for white stars inside the image field: Not saturated 0.6 mag < B-V < 0.7 mag 0.2 mag < V-R < 0.6 mag  Measurement of the brightness of selected white stars in Red, Green and Blue.

B-V Workflow  Preprocessing Dark, Flat Registration Averaged R, G and B image  Aladin B-V steps 1.Load DSS image 2.Load photometric catalogue 3.Load filter 4.Measure brightness of selected stars

Step1: Load DSS image DSS = Digitized Sky Survey Aladin:

Step1: DSS

Step2: Load Photometric Catalogue NOMAD1 = Naval Observatory Merged Astrometric Dataset Advantage: 100% sky coverage Disadvantage: Accuracy

Step3: Load Filter Select white stars 0.6 < B-V < < V-R < 0.6 Save Wolfgang Piracher‘s filter on your local disk

Step3: Filter

Aladin - Filter

Step4: Measurement  Aperture photometry of standard image processing software (e.g. AstroArt)  Result: 3 ADU values (R,G and B)  Example: Red / Green / Blue > Green and Blue are too bright -> Red 1,00 / Green 0,85 / Blue 0,94.

Experiences with B-V  Methode is laborious  NOMAD1 catalogue Inhomogeneous Is based partly on plate scans The fainter the reference stars, the more unreliable  -> at least 5 stars are necessary (outliers)  The blue weight is often too high  Average between G2 and B-V.

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Alternative Methodes  Regim by Andreas Rörig Up to 5 stars; manual selection  Theli by Mischa Schirmer LINUX software Astrometric registration Fully automated B-V methode: Usage of a big number of stars, which are found by the software (Vizier data base).  SDSS Much better photometric data Filter system ugriz (u-g=1.43mag; g-r=0.44mag) At the moment far away from full sky coverage.

Summary  New catalogues In several years much better catalogues compared with NOMAD1  Fully automated B-V methode is possible E.g. Theli  B-V methode as standard The B-V calibration works in all thinkable situations (bad transparency, Milky Way fields,..), provided that the used catalogue is enough accurate.  Best procedure at the moment: Combination of G2 and B-V

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