1. RGB Color Balance with ExCalibrator – “Take 2” SIG Presentation B. Waddington 5/21/2013

2. Options for Getting Color Balance “Prescriptive” tool like Goldman’s RGB calculator CCDStack background and white point calibration G2V calibration Ad-hoc – “make it look like Adam Block’s” Something better…

3. ExCalibrator Automated tool written by Bob Franke – V4 is *much* more automated Used to determine R:G:B color ratios Based on quantitative measures of star color Uses your DSO target FOV rather than a separate G2V calibration Freeware

4. What is ExCalibrator Doing? Downloads professional survey (photometry) data for your field-of-view Scans your image and identifies non- saturated stars that are in the survey data Measures the corresponding R,G,B star brightness values in your image Computes average R,G,B ratios to best match the survey data

5. ExCalibrator Installation Just download the zip file from Bob Franke’s site: http://bf- astro.com/excalibrator/excalibrator.htmhttp://bf- astro.com/excalibrator/excalibrator.htm Unzip it to a location you want – there is no installer required Run it…

6. Using the Program Select your combined and aligned red, green, and blue images Select an aligned file that has been plate- solved – filter doesn’t matter Choose your calibration method Be sure you’ve specified a “server” – Strasbourg, France is fine Click on ‘Calibrate Image’

7. Calibration Options ExCalibrator “classic” –Locates the stars in your image using a fairly simple algorithm –Selects only those stars that are “near-white” –Computes the ratios so the white stars in your image look white –Works well when there are many stars to choose from

8. Calibration Options SExtractor –Uses a background, professional-grade program for locating the stars in your image –Still selects only “near-white” stars and computes the RGB ratios accordingly –A good option if the ‘classic’ approach is finding few stars to use

9. Calibration Options SExtractor/ Linear regression –Uses a background, professional-grade program for locating the stars in your image –Uses a much broader range of star colors in your image –Applies linear regression to compute the optimal RGB ratio across all star colors –Can only be used with SDSS data

10. Calibration Options Use multiple options to see a range of results Use the ‘remove outliers’ command to converge on the final result

11. What Survey Data Are Used? Two sources of data for photometric (not spectroscopic) data Sloan Digital Sky Survey (SDSS) –Highly accurate, all-digital data –Does not cover 100% of the sky –http://www.sdss3.org/dr9/index.php#coveragehttp://www.sdss3.org/dr9/index.php#coverage NOMAD (US Naval Observatory) –Merged data from 6 catalogs –Highly variable (often poor) photometry –Over 1 billion stars

12. What Survey Data Are Used? Photometric data represent magnitude measures through various filters – B, V(green), and R are useful to us B-V is the primary “color index” Empirical data show that Nomad values are “too blue” compared to SDSS – so ExCalibrator includes a “Nomad adjustment”

13. Possible Hiccups You get a nasty error message: function loadFitsKeyWords failed for Sum File. – You didn’t specify a plate-solved image! –Be sure you saved the file after plate-solving –Look in the file header to be sure the plate solution data are present

14. Possible Hiccups You see an error message saying something like: Check your file names – avoid blanks and most special characters…

15. Possible Hiccups ExCal can’t find any stars –Are the color files aligned with each other and with the plate-solved file? –For SDSS data, try the linear regression option –Try the Nomad catalog – if it fails, there’s something wrong with your images

16. Possible Hiccups You get a message saying the FOV is not covered by the SDSS database –Well, it isn’t –Use the Nomad catalog – this may require resetting your calibration method to ‘classic’

17. Possible Hiccups You are getting results but there are very few stars being used –If you’re using SDSS data, you’re probably ok –You can “gently” widen the ‘Min’ and ‘Max’ color values –Use linear regression option – it uses all the stars

18. White Balance: What’s Going On Instrumentation effects –Filter band-pass –Camera sensitivity Sky –Altitude of DSO –Transparency (moisture, dust, clouds) –Reddening due to interstellar dust Goals is to set RGB ratios so “neutral is neutral”

19. Review of Options CCDStack background/white adjustment –Very quick and easy and will usually get you “close” –Can be a challenge when a white point is not evident –Normal spiral galaxies make a very good white point, but nebulas can be difficult

20. Review of Options G2V imaging system calibration –Uses very accurate spectral classification of individual stars – G2V is ‘white’ –Used to characterize your imaging system, not your sky Stars are relatively sparse (< 800) so they won’t be in your DSO field of view RGB ratios must be adjusted for “atmospheric extinction” based on DSO altitude Doesn’t handle transparency or reddening effects

21. System Calibration with ExCal (G2V’) Image a star-field near the zenith on a good, clear night Be sure the FOV is covered by SDSS data Do a linear regression calibration to compute your “G2V-equivalent” ratios

22. When Would You Use G2V’? To understand color response of your system for planning exposure times To sidestep having to use Nomad data or to sanity-check Nomad results Remember that you must correct for atmospheric extinction http://www.kellysky.net/White%20Balancin g%20RGB%20Filters.pdf‎http://www.kellysky.net/White%20Balancin g%20RGB%20Filters.pdf‎

23. Review of Options ExCalibrator Strengths –Uses DSO field of view – so it handles both instrumentation and sky effects –For digital SDSS data, results are likely to be very good –Has no impact on data capture – purely a post- processing step –Relatively easy to use and nothing to lose in trying it –Much easier than G2V with equal or better results

24. Review of Options ExCalibrator Challenges –Can be problematic for small FOVs –Requires a plate-solved image –Nomad data can produce “iffy” results –Ratios produce an “apparent” view, not necessarily an “intrinsic” view (reddening)

25. The Weird Magnitude System (Useless historical sidebar)