24 maja 2007Joanna Falzmann Algorithm for automatic estimation of measurements quality 1 Pi of the...
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24 maja 2007 Joanna Falzmann Algorithm for automatic estimation of measurements quality 1
Pi of the SkyPi of the Sky
AlgorithmAlgorithm for for automatic estimation of automatic estimation of quality of quality of measurementsmeasurements
Joanna Falzmann UKSW
24 maja 2007 Joanna Falzmann Algorithm for automatic estimation of measurements quality 2
Pi of the SkyPi of the Sky
Searching for optical flashes of astronomical origin
Every night thousands of pictures (frames) are taken
All data goes to the huge database
Part of this data has low quality. It’s caused by clouds, full moon…
24 maja 2007 Joanna Falzmann Algorithm for automatic estimation of measurements quality 3
Division into fieldsDivision into fields
Sky has been divided into fields
Astronomical coordinates gives name for each field (Right Ascention and Declination)
Example: 0800+20 Ra= 08h 00m Dec=20
600 fields in database
About 500 was observed at least once
24 maja 2007 Joanna Falzmann Algorithm for automatic estimation of measurements quality 4
Number of visible starsNumber of visible stars
Each field has characteristic number of stars on it
If we know this number we can use it for estimation of quality of fames
Plot of the number of stars on each field is automatically created every night
24 maja 2007 Joanna Falzmann Algorithm for automatic estimation of measurements quality 5
Clouds and High MoonClouds and High Moon
Clouds
Sun sets
Good data
Sun raises
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Example of good dataExample of good data
Good data
Sun sets
Good data Sun
raises
24 maja 2007 Joanna Falzmann Algorithm for automatic estimation of measurements quality 7
Clouds and High MoonClouds and High Moon
System sees less stars that it is there
We need to build an automatic tool to select bad and good frames
Associate a „quality measure” to each frame
24 maja 2007 Joanna Falzmann Algorithm for automatic estimation of measurements quality 8
Building an algorithmBuilding an algorithm
Finding all interesting data for each field
Number of measurements greater than 10
Creating histograms for all fields fo all nights
Analizing the histograms
Inserting characteristic number of stars to database
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HistogramsHistograms
Some histograms are regular – we can fit one gauss
24 maja 2007 Joanna Falzmann Algorithm for automatic estimation of measurements quality 10
Histograms – one gauss Histograms – one gauss
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Information to the databaseInformation to the database
About 50 fields in 500 of all has this regularity
Info about mean value and sigma to the database
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Histograms – two gaussesHistograms – two gausses
Some histograms show two gausses
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Histograms – two gaussesHistograms – two gausses
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Strange eventsStrange events
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InvestigationInvestigation
Histograms of about 150 fields in 500 of all are useless
We need to collect more data
For the rest we have to investigate why they have two (or more) gausses structure
24 maja 2007 Joanna Falzmann Algorithm for automatic estimation of measurements quality 16
CriteriaCriteria
Changing criteria
More than 30 measurements of the field during one night
Cut observations from begin and end of the night
Cut measurements with full moon
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ImplementationImplementation
Sipmle algorithm wich will give number for each frame:
Frames with number of stars equal mean value - sigma – very good
Frames with mean value – 1 to 2.5 sigma – acceptable, but suspicious
Discard the rest