MWAIC - CCDStack Presentation

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MWAIC 2008 A CCDStack Processing
Workflow Saturday, June 21, 2008 Neil
Fleming (www.flemingastrophotography.com)
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What is CCDStack?

• CCDStack is one of the leading image processing
  programs
• Used to take your basic data and perform
  important pre-Photoshop tasks
• These include
• Prepare calibration masters bias/darks/flats
• Load and calibrate your subs
• Digital Data Processing (DDP)
• Bloom rejection
• Image registration
• Data normalization
• Data rejection
• Channel master combines

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Why Do I Like It?

• Separates the various steps in the workflow well
  for excellent control
• Ability to make blooms transparent, in addition
  to imputing data
• Hot/Cold Pixel rejection
• A wide range of data rejection techniques which
  make it easy to eliminate satellite/airplane
  trails
• Easy-to-use DDP
• Easy-to-use Positive Constraint deconvolution
• Pseudo LAB treatment for LRGB combines

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Processing Workflow

• Prepare calibration masters bias/darks/flats
• Load and calibrate your subs
• Apply DDP, and evaluate the quality of the subs
• Bloom rejection
• Registration
• Normalization
• Data rejection
• Channel master combines

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Calibration Masters

• Dark Frames
• These are used to subtract out the effects of
  hot pixels
• Optimally, these are taken at the same duration
  and camera temperature as your light frames
• Bias Frames
• Zero-duration dark frames used to time scale
  darks, and as a proxy dark frame for flats
• Flat Frames
• Used to accommodate light fall-off at the edges,
  as well as to eliminate dust motes
• Prepare calibration masters bias/darks/flats
• I try to get 25-30 subs for each type of master
• Use some sort of sigma rejection or clip min/max,
  don't use mean
• This eliminates the impact of outliers like
  cosmic ray hits (all three types) and stars (for
  the flats)
• Bias-subtract your flats when you create your
  flat master to accommodate differing temperatures

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Dark Frame Master Sample
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Flat Frame Master Sample
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Load and Calibrate Your Subs

• Load all of your subs into CCDStack
• Under Process, select Calibrate
• Select your appropriate dark, bias, and flat
  masters
• Apply to all

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Sample Uncalibrated Sub
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Sample Calibrated Sub
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Evaluate Sub Quality

• Rotate all of the subs to the same orientation
• Carefully evaluate your data!
• CCDInspector for contrast, aspect ratio, and FWHM
  evaluation
• Mark I eyeball as a second step, especially if
  your data is undersampled, for gradients and star
  aspect ratio
• Good / Marginal / Bad
• I discard the Bad subs, and keep the Good
  along with a few of the Marginal
• The larger the stack of good subs, the more of
  the marginal I can include

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The Good, the Bad, and the Ugly
Bad
Good
Marginal
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Bloom Rejection

• Process, Data Reject, Procedures
• Select, Reject Blooms
• Set appropriate upper limit, e.g., 30000 ADU
• Apply to All
• Impute Rejected Pixels
• I use 0.2 pixels, with 3 iterations
• Apply to All

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Bloom Rejection
Before
Rejected Bloom
Pixels Imputed
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Image Registration

• I often image the same object over multiple
  nights
• This results in a little offset or a slight extra
  rotation between subs from each night
• Go under, Stack, Register

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Image Registration

• Under the Star Snap tab, Select Reference
  Stars
• I pick 3 to 4 widely spaced, medium sized stars
• I then click on, Align All
• Blink through the stack to ensure that all subs
  are well-registered
• Sometimes I first try a pass with two closely
  spaced bright stars, then do a second pass with
  the 3 to 4 widely spaced, medium sized stars
  (Dual-pass method)
• When aligned, move to the Apply tab and select
  a method for registration, like Quadratic
  B-Spline, and click, Apply to All

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Image Registration
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Image Registration
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Image Registration
Unregistered
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Image Registration
Registered
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Image Normalization

• This is used to balance the individual subs
  contribution to the final combine, as well as to
  adjust the brightness levels to match from
  sub-to-sub
• The higher quality subs will contribute more,
  while the lower quality subs will contribute less
• Go to, Stack, Normalize, Auto, and click,
  OK

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Data Rejection

• Data Rejection
• CCDStack allows you to reject poor data like
  satellite trails, cosmic ray hits, and airplane
  trails independently of the combine method!
• You do not have to rely on mean, median, etc., to
  get rid of these pests!
• Options include
• STD Sigma
• Poisson Sigma
• Each of these methods will throw out the
  outliers and average the remaining pixel values
• I often use the Poisson Sigma reject, with 1.6
  to 2 standard deviations (sigma multiplier), or
  clip min/max for deep stacks
• Larger stacks can take tighter tolerances

• Linear Factor
• Clip Min/Max

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Rejected Data a Good Subexposure
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Rejected Data a Lower Quality Subexposure
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Subs Rejected Pixels
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Channel Master Combine

• Data combine
• You can do any of the following
• Sum
• Mean
• Median
• Minimum
• Maximum
• I almost always use, Mean for complete data
  sets
• Ill use Sum if utilizing data sets in further
  combine steps

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Mean Combine the Subs
Single Sub
Master Combine
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DDP to Taste

• Digital Development Processing (DDP) offers both
  a non-linear stretch of the data as well as
  sharpening
• I do utilize the stretch at this point
• I save the sharpening until later (usually in
  Photoshop)

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DDP to Taste - Before
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DDP to Taste - After
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DDP to Taste - Comparison
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Hot/Cold Pixel Rejection

• If I am working with noisy data or a thin stack,
  Ill use the Hot/Cold Pixel rejection facility in
  CCDStack
• I worry more about where data is lacking (dark
  pixels) than I do for hot pixels
• First, I select a dark area of the image to
  determine the mean value of the dark area

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Hot/Cold Pixel Rejection

• I then go under Process/Data Reject and choose
  Reject Hot/Cold Pixels
• For the upper limit ADU, I set a value just
  above that of the mean of the dark areas, 150 in
  this case
• For Strength, I just play until I get what I
  feel is an appropriate number of rejected pixels

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Hot/Cold Pixel Rejection
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Impute the Hot/Cold Pixels

• Impute Rejected Pixels
• I again use 0.2 pixels, with 3 iterations
• Apply to this

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Deconvolution

• I prefer the Positive Constraint algorithm,
  with 25 iterations
• Choose a medium star on a dark background

Original
Deconvolved
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The OIII Channel Master is All Done
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Do the Other Channel(s)

• Now do the Ha and the SII (if you have it) via
  similar processing steps
• After calibration and rotation, when I start
  registration, I re-load the OIII master and use
  that one to register the Ha and SII subs
• This allows for only one destructive
  registration step to be applied, not two!
• I then do a final tweak with DDP to maximize the
  presentation of the object
• You now have your Ha, and OIII masters

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Our Final Channels
Ha
OIII
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Preparation for Photoshop

• Save each channel master as a 16-bit scaled TIF
• I open each TIF in PS, and closely examine the
  histogram to make sure I have not clipped the
  data at either end
• I find the scaling process in CCDStack will
  usually clip just a bit on the dark end of the
  histogram
• So, I will go back into CCDStack, lower the dark
  value cutoff a bit, and re-save the scaled TIF
  until I am satisfied

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Initial Color Combines

• Although I usually do this in Photoshop, after
  some additional channel optimization, your color
  combines can be done in CCDStack
• Load in all of your color channel masters
• Go under Color, Create
• If you know your appropriate filter combine
  ratio, enter it now
• Click on Create

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Initial Color Combines

• Your initial color combine will clearly
  illustrate filter ratio imperfections

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Initial Color Combines

• Select an area that you know should be neutral,
  and click on OK

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Initial Color Combines

• You can continue to adjust the balance and
  saturation in the Adjust Color Window

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Initial Color Combines

• Now, youre well on your way, adjustments can be
  done in Photoshop

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Questions?
MWAIC 2008 A CCDStack Processing
Workflow Saturday, June 21, 2008 Neil
Fleming (www.flemingastrophotography.com)