1. Jerry Horne San Jose, California USA
Automated Extraction of Photometric Data: A demonstration project using MaximDL on CV Images
AAVSO Spring Meeting
5-6 May 2006
AAVSO Spring Meeting, Rockford, IL.
Jerry Horne
San Jose, California USA

2. Contents Abstract Background Concept Design The Software Some Results
Conclusions
Table of Contents
- Abstract
- Background
- Concept
- Design
- The Software
- Results and Tests
- Conclusions
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Automated Extraction

3. Abstract Automated Extraction of Photometric Data:
A demonstration project using MaximDL on CV images
The intrinsic photometric functions and scripting capability of the image processing software MaximDL is used to automate the extraction of photometric data from images of Cataclysmic Variable stars using standard AAVSO comparison stars. The resulting photometric data is then formatted for inclusion in the AAVSO variable star database. This automated technique is compared with manual data extraction methods and other photometric software.
Automated Extraction of Photometric Data:
A demonstration project using MaximDL on CV images
The intrinsic photometric functions and scripting capability of the image processing software MaximDL is used to automate the extraction of photometric data from images of Cataclysmic Variable stars using standard AAVSO comparison stars. The resulting photometric data is then formatted for inclusion in the AAVSO variable star database. This automated technique is compared with manual data extraction methods and other photometric software
CV = Cataclysmic Variables such as CY and AY Lyra
AAVSO Spring Meeting 06
Automated Extraction

4. Background
Multiple Image Processing and Photometry programs available:
MaxIm DL, AIP4Win, Mira, Astro Art, IRAF, Canopus, AstroMB, xPhot…
All have varying ability to process single or multiple images, then extract photometric data, and:
Produce light curves
Output data files that can be further analyzed by other programs
MaxImDL and IRAF have a programmable interface.
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5. Background No single program or tool that
Computes the magnitude of AAVSO program stars
Using data on comparison stars on AAVSO charts
To produce formatted output ready for inclusion in the data base, via Web Obs or PC Obs
Problem: How to reduce the labor required to extract data from images taken the night before and send the data off to AAVSO Hq.
Various tools and spreadsheets can be used to obtain the data that can be inserted into PC Obs
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6. Need a Specialized Software Tool
Fill the Gap between:
The current PC Obs program will be changing this summer.
And:
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7. Concept How to go from: (with data from): To: By clicking on:
CY LYR CCDV 125,139, FHJZ Err: 0.03
By clicking on:
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8. Software Design Main Requirements:
A programmable interface to an existing Image Processing Software program
Ability to load and align images
Find & Store Magnitude and stellar position data
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9. Software Design Main Requirements (continued):
Ability to Identify specific stars on an image
Ability to measure intensities and SNR
Perform calculations and format data
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10. Design (continued) Programmable interface possibilities for MaximDL
Windows Scripting Language (VBS)
Visual Basic or Visual C++ stand-alone program
VB or Visual C++ plug-in
VB stand-alone program chosen
Ease and speed of development
MaximDL data structure reasons
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Automated Extraction

11. Design (continued) Ability to Load and Align Images
MaximDL provides software access to standard FITS load functions and image align routines
Find/Store Magnitude and Position Data
MaximDL contains intrinsic tools to obtain X & Y position data for stars in the image
Input magnitude data from AAVSO Charts
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12. Design (continued) Ability to Identify Specific Stars
Two possible methods:
Astrometrically solve a new image using a large star catalog such as GSC
Align a new image to a reference image of the star field where the positions of stars of interest have already been identified.
#2 is easier and faster
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13. Design (continued) Align New Image to Reference Image: Reference New
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14. Design (continued) Ability to measure intensities and SNR
Internal MaximDL functions:
Document.CalcInformation( X, Y[, Rings ])
Integrated intensity of star image in aperture
Signal to Noise ratio of star image with respect to the background
Rings settings (Aperture, Gap, Annulus)
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15. Design (continued) Perform calculations and format data
Multiple calculation methods for differential photometry:
Basic V-C: the magnitude of the variable found by using a single comparison star:
V = (v – c)o + C {e.g. V = }
Also use of a check star to gauge accuracy:
(K – C)o =? (K – C)s
This method is straightforward and available in MaxIm DL and AIP4Win
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16. Design (continued)
Methods of calculation - continued
Average = Mean of variable magnitudes found using each comparison star:
Vi = (v – c)i + Ci {e.g. Vi = }
Then: n
V = ( Vi )/ i {e.g. V = ( ) / 3 }
i=1
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17. Design (continued) Methods of calculation - continued
Biased Mean = Mean of variable magnitude using the results from selected comparison stars - using comparison stars closest in magnitude to the variable:
a) Perform V-C Calculation, for example, using C1 (12.5)
{16.3 = }
b) Since variable’s magnitude is faint, go back and use
the fainter comparison stars (C3 = 15.6, C4 = 16.0, C5 =16.4)
for the calculation :
{ e.g. V = ) / 3 = 16.4}
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18. Design (continued) Methods of calculations - continued
Weighted Mean - weight the average by the inverse of the standard errors: n
Vw =  (Vi/i) * 1/(1/i + 1/i+1…+ 1/n )
i=1
where i = individual error and Vi = the individual calculated magnitudes from each comparison star
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19. Design (continued)
Methods of calculations - continued
Aggregate – combining all comparison star intensities and magnitudes to form a virtual star to compare with the variable (also called ensemble, composite, master star): n
C(total) = ( -2.5)Log10 ( 10(-Ci/2.5)) {sum comparison magnitudes}
i =1
I(total) =  Ii {sum intensities}
Then:
Vagg = -2.5 Log10 (Iv/I(total)) + C(total) {find var mag}
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20. Design (continued) Methods of calculations - continued
Ensemble – (Inhomogenous Exposures - Honeycutt, 1992) combining all comparison star intensities and magnitudes from multiple images using a sophisticated weighting technique to form a reference frame to measure all stars against:
m(e, s) = m0(s) + em(e) {instrumental mag}
ee ss
b =   [m(e, s) - m0(s) em(e)]2 w(e,s) {least sqrs}
e=1 s=1
The magnitude measured of star is a function of both the intrinsic magnitude of the star m0(s), but also the magnitude difference from the individual exposure, such as air mass, seeing, instrumental error
The technique is to find a least-squares fit to each star and exposure to build a reference frame to measure all stars against.
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21. Format Data Format for output is specified on an AAVSO webpage:
Column # Design. Name Julian Date Magn. CommentStep Mag Charts Init.Remarks Codes or Comp Stars xxxx+xxxnnnnnnnnnnxxxxxxx.xxxx<xx.x:aaaaaaagggggggggggccccccccnnnnnxxxxxxxxxxx V723 CAS SU , PD WEO
From the AAVSO website
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22. The Software
Start:
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23. The Software Analysis Panel with Maxim DL:
Maxim DL is started when tool starts
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24. The Software Analysis Panel: Expand Analysis Panel
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25. The Software Extended Main Panel: Load Photometry Data
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26. The Software Load Star Data: Select File to Load
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27. The Software Star Data Loaded, showing variable star info:
Reference Files
Observer and Comments
Multiple Sequences
Variable and Position Data
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28. The Software Star Data Loaded, showing C1 star info:
Comparison Magnitude and Position Data
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29. The Software Edit Set-Up information: Set SNR Photometry Settings
Calculation Types
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30. The Software Choose Image Files: AAVSO Spring Meeting 06
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31. The Software Ready for Analysis: Click on Analyze Image Files Set
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32. The Software Analysis in Progress: Analysis Log
Images Loaded and Aligned with Reference Image
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33. The Software Analysis Complete: Maximize Log Save to File
Scroll through Results
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34. The Software Analysis Log: Each selected calculation is displayed
Selecting fainter comparison stars
Variable not detected
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35. The Software Analysis Log: (continued) Signal-to-noise values
known K - C minus observed K-C
Signal-to-noise values
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36. The Software Analysis Log: (continued)
Comparison of Selected Calculation Methods
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37. The Software Marking Comparison and Variable Star Positions:
Click on Mark Button
Ref. File Loaded
Select Seq to Mark
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38. The Software
Marking Comparison and Variable Star Positions (continued):
Maxim DL Info Panel
Set Star Positions
Enter Mag for Comps
Click Done
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39. The Software
Marking Comparison and Variable Star Positions (continued):
Marked Position carried over to analysis panel
Save Data
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40. Some Comparisons Tool vs AIP4Win:
Used approximately 50 observations CY & AY Lyr:
Bias Mean (AIP – Tool)
Mean Difference = 0.01, Std Dev = 0.11
Aggregate (AIP – Tool)
Mean Difference = 0.03, Std Dev = 0.11
Average (AIP – Tool)
Mean Difference = 0.00, Std Dev = 0.13
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41. The Software Limitations and Notes:
Software assumes Image Files are fully processed beforehand (Flat, Bias, Dark)
Reference and Image Files must be the same scale
If you change your f-ratio, you must take new reference images
The 0.1 mag values of many AAVSO charts obviously limits the accuracy that could be achieved.
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42. Conclusions This is a demonstration piece of software
Different techniques or algorithms could have been used.
It does seem to provide a straight-forward method of obtaining photometric data.
As always, the photometric results are only as good as the images.
It cannot pull good data out of bad images
Each observer must evaluate the results in terms of the errors, consistency, and overall image quality.
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43. References
1. Berry, R., Burnell, J. 2005, The Handbook of Astronomical Image Processing, 2nd Edition.
2. Crawford, T., 2006, JAAVSO Submission
3. Honeycutt, K., 1992, PASP 104,
4. Kundik, T. et al, 1995, Astrophys. J., 455, L5-L8
5. Percy, J, Kolin, D., 2000, PASP 112,
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44. Questions?
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