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Video Camera for Photometry: It can be done.. ….but…

Video Camera for Photometry: It can be done.. ….but…. IOTA July 12, 2014. x. John Menke. x. www.menkescientific.com. x. If you are worried about the time. If you are measuring the time, you are doing occultation/timing. If you are measuring the intensity, you are doing photometry.

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Video Camera for Photometry: It can be done.. ….but…

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  1. Video Camera for Photometry: It can be done.. ….but… IOTA July 12, 2014 x John Menke x www.menkescientific.com x

  2. If you are worried about the time If you are measuring the time, you are doing occultation/timing If you are measuring the intensity, you are doing photometry x x x

  3. What is the biggest problem using video for photometry? x x x x x Seductively easy: intensity vs time!

  4. Now that I have your attention: Software issues: software not really suited to photometry Hardware issues: video cameras not really suited to photometry and Occultation skills <> Photometry skills x

  5. Problems: Photometry not as easy as it looks More sources of error: photometry is Quantitative observing Photometry with video can be done.. But all the details must be right (and it’s tougher than with CCD)

  6. So, the best way to do video photometry is Don’t x x x (Use a CCD camera..) x

  7. Why not… x x The observing SYSTEM is the software plus the camera plus the person x First, the software…

  8. Actually, there are two programs LiMovie-older, less sophisticated Tangra-newer, Hristo Pavlov,more advanced Both excellent for timing x Tangra somewhat better for photometry x x

  9. Video timing software not designed for photometry (Designed for timing, not intensity) Hard/impossible to measure individual pixels (and you have many more to check…) Hard to handle long series (hours of data) Hard to use reference or comparison stars Photometric tools, calibrations, corrections not integrated Software not realtime Next, the camera..

  10. Video cams complex.. May deliberately be non-linear (gamma<>1) Designed for non-point, mid-level brightness image AutoExp algorithms may depend on image, exposure often hard to control or know Readout /ADC may not handle stars properly High readout noise (100,000 video images are worse than a dozen 5min CCD images) Limited dynamic range (8 vs 16 bit in CCD)

  11. Saturated Pixels: For bright targets, Saturation and Roll-Off issues Video cams not tightly specified Behavior approaching saturation (Roll-Off) Actual saturation – 8bit=255 limit X X

  12. Typical frame near occultation Saturation X X X Io X X

  13. JEE events challenges.. Satellite images bright 5-6mag Occulting image is changing shape and size with time (from two to one PSF) Occulting image changing with time Getting brighter, not dimmer! These are all unusual—we’re not used to them

  14. But Sometimes video is the only way Fast timing required (NEOs, flares, etc) No other instrument available So, how to avoid errors.. x

  15. Ya’ gotta’… Learn photometric methods Gotta’ practice! Apply rigorously Know/measure all the relevant characteristics of the sensors Use appropriate tools (linear camera, photometric software such as MaximDL) Be skeptical of results (lots of possible errors)

  16. Many sources of error.. Sensor issues-non-linearity. saturation, exp varies, color, unstable gain, noise Astro/Sky-sky transparency, altitude/ (extinction and color), scintillation, color mismatch, dew Analysis-improper comparison, inappropriate software

  17. Basic photometric methods Must use software allowing easy individual pixel measurement, analysis Must use reference intensity source (comparison object) Assure sensor always within linear response range (or results will be junk) Evaluate need for transformations (color, atmospheric extinction) Document, document, document!

  18. Use Occultation software.. Must compensate for its limitations And/or Photometric software.. (MaximDL or CCDSoft—used for photometry) Can use for video—two steps, though not real time (actually, neither is Li, etc) or both.. Here’s how.. Can

  19. Convert video to JPGs Use VirtualDub to select ~100 frames Export/ImageSequence/..JPG Paste into Maxim or other photometry prog, examine pixels, take averages, etc. Examine pixels, average, etc. Can’t do time series (header data wrong) Write VB routine to fix..

  20. Whichever you do… Must assure that the camera AND software is/are linear in the regime of interest Must assure that you have reference/comp objects Must account for all potential errors Now, about linearity… x

  21. How to measure cam linearity Difficult to do right (great exercise) eg., Video a star cluster with known values of same color (or use filter), all in same frame Convert video to JPGs Measure JPG star inten. in Maxim Plot ..but have to use same conditions

  22. Use Comp (reference) object.. (Differential Photometry) Comparison object use can correct for many, though not all astro/sky errors Beware variable comps, different colors, etc Due to short exp, comps often not available, then find nearby (move scope during run)

  23. Minimum To do List.. Read how-to photometry books Practice: DO several “easy” variable stars (eg., WW Ursa Major) Be skeptical of your results- seek anomalies Peruse AAVSO, MPO sites Study http://www.hristopavlov.net/Articles/VideoPhotometry.html for a ten page paper evaluating Tangra, and on doing video photometry x

  24. Again, strongly consider.. Use video where needed—primarily for fast response, accept limited dynamic range Video used for slow objects have huge files, higher noise, hard to analyze But, use CCD whenever possible x Wider dynamic range (x255), cam and software designed for photometry

  25. 255 3 * * 2 * 1 * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * Ever wonder how an 8 bit camera can yield higher precision results? more noise noise bins x Averaging depends on noise to gain precision o o x o x * eg, three points * * * *

  26. Video Cameras Readout Sensor ADC USB PC Readout Sensor RCA ADC x

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