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

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Presentation transcript:

1 Video Camera for Photometry: It can be done.. ….but… IOTA July 12, 2014 John Menke x x 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 Photometry with video can be done.. But all the details must be right (and it’s tougher than with CCD) More sources of error: photometry is Quantitative observing

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

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

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

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

10 Video cams complex.. May deliberately be non-linear (gamma<>1) AutoExp algorithms may depend on image, exposure often hard to control or know Readout /ADC may not handle stars properly Designed for non-point, mid-level brightness image 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 Video cams not tightly specified Actual saturation – 8bit=255 limit X X For bright targets, Saturation and Roll-Off issues Behavior approaching saturation (Roll-Off) Saturated Pixels:

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

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

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

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

18 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) Here’s how.. Use Occultation software.. Must compensate for its limitations Can or both..

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 Now, about linearity… Must account for all potential errors 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.. 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) (Differential Photometry)

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 x Study for a ten page paper evaluating Tangra, and on doing video photometry

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

25

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

27 Video Cameras Sensor Readout ADC USB x Sensor Readout ADC RCA PC

28