Data Rejection Basics

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```					CCDStack Take 2
CCDStack Version 2 Tutorial
4/19/2011
Stack-based Rejection

Compute
statistics on
each “column”
of pixels in a
stack of
images…
Stack-based Rejection
   Basic Concept
   Estimate the “most likely value” for each column in the
stack – typically the “average” value
   Look at the dispersion of values in that column relative to
the average
   Reject those pixels that look “too far off the mark”
   Rejection occurs for individual pixels in each
image, not the whole image
   Most of the data rejection techniques are all about
defining “too far off the mark”           │
Stack-based Rejection

Individual pixels
in each column
are rejected as
being outliers…
Rejected Pixels
   What happens to the pixels that are
rejected?
   They are assigned a “rejected value” and
are excluded from subsequent calculations
– but the original values are not lost
   They may need to be given “imputed”
values if there are no “good” values to use
in their place (e.g. blooms)
Data Rejection Choices – Sigma Clip
   Computes the average and std. deviation of
the pixel stack; keeps only those pixels that
lie within a sigma factor of the average
   Strong noise rejection but needs 10+
images for best results
   Allows “tuning” based on the sigma factor
you specify
   Can be iterated                      │
Sample Values in a “Pixel Stack”
Sampled Values of Single Pixel Position

12
10                                                Bogus
Frequency

8                                                values
6
4
2
0

e
00

50

00

50

00

50

00

50

or
22

22

23

23

24

24

25

25

M
Pixel Value
Rejection by Sigma Clip
Sampled Values of Single Pixel Position
3σ
12                                2σ
10
Frequency

8                                                      3-Sigma
6                                                      Clip
4
2
0

e
00

50

00

50

00

50

00

50

or
22

22

23

23

24

24

25

25

M
Pixel Value
Rejection by Sigma Clip
Sampled Values of Single Pixel Position
3σ
12                                2σ
10
Frequency

8
2-Sigma
6
4
2-Sigma                                      Clip
2
0

e
00

50

00

50

00

50

00

50

or
22

22

23

23

24

24

25

25

M
Pixel Value
Poisson Data Reject
   Uses a theoretical “spread” (sigma)
assuming a Poisson distribution of data
   Poisson sigma == Sqrt(average signal)
   Average signal value calculation includes use of
   Camera values need to be correct
Poisson Data Reject
   Can be used on small stacks – even two or
three images
   Very strong noise rejection
   May damage stars if the star sizes are not
pretty similar across frames
   You need to try various sigma factors and
look closely at the results
Workflow
   Calibration
   Registration
   Normalization
   Data rejection
   Combine (mean)
   DDP processing for luminance
   Sharpening for “preview”
Registration Tips
   Pick whatever image is well-framed as reference
   CCDIS is preferred – requires CCDInspector plug-
in (\$90)
   You can mix and match alignment methods as
desired
   Help file has good explanations
   “Apply” alternatives
   Nearest neighbor – image must be well-sampled,
   Quadratic B-Spline is a safer choice
Normalization
   Pick your best quality image in the stack
   Normalization is CRITICAL to data rejection
   It can be repeated multiple times if needed
Data Rejection Tips
   Try for 1-2% data rejection on this
reference image by adjusting the “factor”
and looking at the “Info” window
   STD Sigma Reject is a good all-purpose
choice
   Poisson Reject is well-suited for small
stacks or nasty problems
Color Combination Tips
   Create an LRGB composite
   Use the background adjustment option
   Boost the contrast for better visualization
   Choose a known-white object
   Select an entire spiral galaxy
   Very good starting point on color balance
CCDStack Help
   Version 2 includes much-improved help
   Context-sensitive help (F1)
   Expanded information on various processing
options
   CCDWare support forums are monitored
and used by program authors
References
   Streaming video tutorial:
http://www.ccdware.com/tutorials/ccdstack/overview.html
   Version 1 tutorial:
http://www.ccdware.com/Files/CCDStack%20Tutorial.pdf
   Original SIG presentation:
http://www.oc-aisig.org/docs/tutorials/

   Where to get CCDStack:
http://www.ccdware.com/

```
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