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Automated Extraction of Photometric Data: A demonstration project using MaximDL on CV Images

Explore how MaximDL automates extraction of photometric data from CV star images, enhancing AAVSO database in this project analysis. Compare automated and manual methods, highlight results and benefits.

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Automated Extraction of Photometric Data: A demonstration project using MaximDL on CV Images

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

  2. Contents • Abstract • Background • Concept • Design • The Software • Some Results • Conclusions 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

  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 Automated Extraction

  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. Automated Extraction

  6. Need a Specialized Software Tool Fill the Gap between: And: Automated Extraction

  7. Concept • How to go from: (with data from): To: 1848+26 CY LYR 2453613.6688 13.32 CCDV 125,139,1561848+26FHJZ Err: 0.03 By clicking on: Automated Extraction

  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 Automated Extraction

  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 Automated Extraction

  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 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 Automated Extraction

  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 Automated Extraction

  13. Design (continued) • Align New Image to Reference Image: Reference New Automated Extraction

  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) Automated Extraction

  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 = 3.7 + 12.5 } Also use of a check star to gauge accuracy: (K – C)o =? (K – C)s Automated Extraction

  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 = 3.7 + 12.5 } Then: n V = ( Vi)/ i {e.g. V = (16.2 + 16.3 + 16.4) / 3 } i=1 Automated Extraction

  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 = 3.7 + 12.5} 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 = 16.4 + 16.4 + 16.5) / 3 = 16.4} Automated Extraction

  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 Automated Extraction

  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 n I(total) =  Ii {sum intensities} i =1 Then: Vagg = -2.5 Log10 (Iv/I(total)) + C(total) {find var mag} Automated Extraction

  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 Automated Extraction

  21. Format Data • Format for output is specified on an AAVSO webpage: Column # 00000000011111111112222222222333333333344444444445555555555666666666677777777778 12345678901234567890123456789012345678901234567890123456789012345678901234567890 Design. Name Julian Date Magn. CommentStep Mag Charts Init.Remarks Codes or Comp Stars xxxx+xxxnnnnnnnnnnxxxxxxx.xxxx<xx.x:aaaaaaagggggggggggccccccccnnnnnxxxxxxxxxxx.. 0059+53 V723 CAS 2451777.628 14.1 SU 132,142 PD0296 WEO Automated Extraction

  22. The Software Start: Automated Extraction

  23. The Software Analysis Panel with Maxim DL: Maxim DL is started when tool starts Automated Extraction

  24. The Software Analysis Panel: Expand Analysis Panel Automated Extraction

  25. The Software Extended Main Panel: Load Photometry Data Automated Extraction

  26. The Software Load Star Data: Select File to Load Automated Extraction

  27. The Software Star Data Loaded, showing variable star info: Reference Files Observer and Comments Multiple Sequences Variable and Position Data Automated Extraction

  28. The Software Star Data Loaded, showing C1 star info: Comparison Magnitude and Position Data Automated Extraction

  29. The Software Edit Set-Up information: Set SNR Photometry Settings Calculation Types Automated Extraction

  30. The Software Choose Image Files: Automated Extraction

  31. The Software Ready for Analysis: Click on Analyze Image Files Set Automated Extraction

  32. The Software Analysis in Progress: Analysis Log Images Loaded and Aligned with Reference Image Automated Extraction

  33. The Software Analysis Complete: Maximize Log Save to File Scroll through Results Automated Extraction

  34. The Software Analysis Log: Each selected calculation is displayed Selecting fainter comparison stars Variable not detected Automated Extraction

  35. The Software Analysis Log: (continued) known K - C minus observed K-C Signal-to-noise values Automated Extraction

  36. The Software Analysis Log: (continued) Comparison of Selected Calculation Methods Automated Extraction

  37. The Software Marking Comparison and Variable Star Positions: Click on Mark Button Ref. File Loaded Select Seq to Mark Automated Extraction

  38. The Software Marking Comparison and Variable Star Positions (continued): Maxim DL Info Panel Set Star Positions Enter Mag for Comps Click Done Automated Extraction

  39. The Software Marking Comparison and Variable Star Positions (continued): Marked Position carried over to analysis panel Save Data Automated Extraction

  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 Automated Extraction

  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. Automated Extraction

  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. Automated Extraction

  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, 435-440 4. Kundik, T. et al, 1995, Astrophys. J., 455, L5-L8 5. Percy, J, Kolin, D., 2000, PASP 112, 363-366 Automated Extraction

  44. Questions? Automated Extraction

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