-- AaronAndrews - 01 Dec 2016

Observation on 25/11/2016:

Simulation: Simulation_test11.py.txt

  • Can generate background mean (or standard deviation) using taylor series:
 \begin{equation} f\left ( x;a_{ij} \right ) = \sum_{i=0}^{N_{i}} \sum_{j=0}^{N_{j}} \frac{a_{ij}}{i!j!} \left ( x-x_{0} \right )^{i} \left ( y-y_{0} \right )^{j} \end{equation}
  • In order to get parameters, set up code to do a fit over an array of values using the expansion, up to a set number of terms.
  • First applied fit directly to image of M103 from observation 1, up to 25 terms:
  • LEFT: original image, M103. RIGHT: taylor series fit (25 terms, origin=(0,0))
  • M103_VIS_60S.pngM103_Simtest_BGmean_3.png
  • Then applied median analysis to frame first, then attempted fit (25 terms):
  • LEFT: Median filter for M103. RIGHT: taylor series fit (25 terms, origin=(0,0))
  • M103_Median_65box.pngM103_Simtest_BGmean_2.png
  • Attempted to fit up to 100 terms - failed.
Truncated Histogram:
  • Aim to make a mode filter over an image by defining a function that returned the mode of a truncated histogram
  • Stars populate the tail of the histogram with low frequencies --> set threshold frequency for mode filter as 1000/((1530*1020)/65^2) = 2
  • The mode is the pixel value with the highest frequency
  • Fit a gaussian to the truncated histogram, the mean of the gaussian corresponds to the mode of the truncated data
  • If there are not enough bins (less than 25), fit may not be executed, therefore we estimate the mode by finding the bin with the maximum frequency, return single value of mode
  • Run mode filter using output from truncation algorithm to obtain an array of modal pixel values
Topic attachments
I Attachment History ActionSorted ascending Size Date Who Comment
PNGpng DoubleCluster_200s_blue_5stack.png r1 manage 1074.2 K 01 Dec 2016 - 09:53 AaronAndrews Double Cluster (blue) stacked
PNGpng M103_Median_65box.png r1 manage 92.9 K 02 Dec 2016 - 00:03 AaronAndrews M103 median
Texttxt M103_Simtest_BG_2.txt r1 manage 0.7 K 02 Dec 2016 - 00:07 AaronAndrews median background fit - parameters
Texttxt M103_Simtest_BG_3.txt r1 manage 0.7 K 02 Dec 2016 - 00:07 AaronAndrews direct background fit - parameters
PNGpng M103_Simtest_BGmean_2.png r1 manage 100.6 K 01 Dec 2016 - 23:59 AaronAndrews Background mean using median
PNGpng M103_Simtest_BGmean_3.png r1 manage 132.2 K 01 Dec 2016 - 23:59 AaronAndrews Background mean using raw image
Unknown file formatfits M103_Simtest_starsBG_3.fits r1 manage 12195.0 K 02 Dec 2016 - 00:03 AaronAndrews M103 simulation plus background directly from real image
PNGpng M103_VIS_60S.png r1 manage 1533.2 K 02 Dec 2016 - 00:06 AaronAndrews M103 - real image
Compressed Zip archivezip Obs2_images_stacked.zip r1 manage 20147.7 K 01 Dec 2016 - 09:44 AaronAndrews Observation2 - stacked images
Texttxt Simulation_test11.py.txt r1 manage 32.0 K 01 Dec 2016 - 23:05 AaronAndrews Simulation code (11)
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Topic revision: r5 - 02 Dec 2016 - LauraBevilacqua

 
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