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

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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

AAVSO Spring Meeting 06 Automated Extraction 2

Contents

• Abstract• Background• Concept• Design• The Software• Some Results• Conclusions


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.


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


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.


Need a Specialized Software Tool

Fill the Gap between:

And:


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:


Software Design

• Main Requirements:1) A programmable interface to an

existing Image Processing Software program

2)Ability to load and align images

3)Find & Store Magnitude and stellar position data


Software Design

• Main Requirements (continued):

4) Ability to Identify specific stars on an image

5) Ability to measure intensities and SNR

6) Perform calculations and format data


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


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


Design (continued)

• Ability to Identify Specific Stars – Two possible methods:

1) Astrometrically solve a new image using a large star catalog such as GSC

2) 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


Design (continued)• Align New Image to Reference Image:

Reference New


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)


Design (continued)

• Perform calculations and format data• Multiple calculation methods for differential

photometry:1) 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


Design (continued)

• Methods of calculation - continued

2) 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


Design (continued)• Methods of calculation - continued

3) 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}


Design (continued)

• Methods of calculations - continued4) 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


Design (continued)• Methods of calculations - continued

5) 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}


Design (continued)

• Methods of calculations - continued6) 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

= [m(e, s) - m0(s) em(e)]2 w(e,s) {least sqrs}

e=1 s=1


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


The Software

Start:


The SoftwareAnalysis Panel with Maxim DL:

Maxim DL is started when tool starts


The SoftwareAnalysis Panel:

Expand Analysis Panel


The SoftwareExtended Main Panel:

Load Photometry Data


The SoftwareLoad Star Data:

Select File to Load


The SoftwareStar Data Loaded, showing variable star info:

Variable and Position DataMultiple SequencesObserver and Comments

Reference Files


The SoftwareStar Data Loaded, showing C1 star info:

Comparison Magnitude and Position Data


The SoftwareEdit Set-Up information:

Photometry Settings Calculation Types

Set SNR


The SoftwareChoose Image Files:


The Software

Ready for Analysis:

Image Files SetClick on Analyze


The SoftwareAnalysis in Progress:

Analysis Log

Images Loaded and Aligned with Reference Image


The SoftwareAnalysis Complete:

Save to File Scroll through Results

Maximize Log


The SoftwareAnalysis Log:

Each selected calculation isdisplayed

Selecting fainter comparison stars

Variable not detected



(continued)

Signal-to-noise valuesknown K - C minus observed K-C



(continued)

Comparison of Selected Calculation Methods


The SoftwareMarking Comparison and Variable Star Positions:

Ref. File Loaded

Select Seq to Mark

Click on Mark Button


The SoftwareMarking Comparison and Variable Star Positions (continued):

Set Star Positions

Enter Mag for Comps

Click Done

Maxim DL Info Panel


The SoftwareMarking Comparison and Variable Star Positions (continued):

Marked Position carried over to analysis panel Save Data


Some ComparisonsTool 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


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.


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.


References 1. Berry, R., Burnell, J. 2005, The Handbook of Astronomical Image Processing,

2nd Edition. 2. Crawford, T., 2006, JAAVSO Submission3. Honeycutt, K., 1992, PASP 104, 435-4404. Kundik, T. et al, 1995, Astrophys. J., 455, L5-L85. Percy, J, Kolin, D., 2000, PASP 112, 363-366


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