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This note presents the Clean Image Set command as taken from
the Mira Pro User's Guide. This feature is available only in Mira
Pro and Mira MX.
Mira Pro and Mira MX provide an exceptional tool for removing
transient artifacts such as cosmic rays and other radiation
events as well as sporadic hot pixels. The Clean Image Set
command compares the members of an image set to determine
statistically what pixels are transient and should be corrected.
Several detection and correction options are available. The results
can be superior to that obtaining using any other method.
The Clean Image Set command identifies and,
optionally, repairs artifacts which are caused by a variety of
sources including cosmic rays and ionizing radiation events. In this
context, the term "event" means any pixel value in one image that is
not persistent, within the noise, throughout the image set. This
technique therefore detects "events" that occur in only 1, 2, or a
few images (depending upon the size of the image set). As a result,
a field of view must be aligned through the image set so that events
can be separated from persistent features. You also can use this
command to clean cosmic rays from long exposure, weakly illuminated
flat field calibration frames that are not aligned, since the
persistent flat field structure is automatically aligned. When an
image set is
registered before cleaning, poorly corrected hot or cold pixels
shift around and appear as events, and the method detects them the
same as true radiation events. For a demonstration, see the
Example, below.
Overview
This method detects outlier pixels by comparing
the values at the same pixel location in a series of images.
In comparison, most
cosmic ray detection algorithms use information from neighboring
pixels within the same image. Using neighboring pixels within the
same image makes it difficult to separate outliers from sharp
features, such as the peaks of stars. The current method is not
sensitive to pixel values in the neighborhood of the target pixel
because the sample of pixel values used for rejection is tracked
through the image set. However, this makes the requirement that the
images must be registered in software, using the
Register Images tool, the
Align by WCS command or the images must have been aligned when
acquired.
This method differs from contrast-based methods
that are used for single images, such as the
Apply Cosmic Ray Filter image calibration method and the "Cosmic Ray
Filter" option in the
Spatial Filters command. The term "contrast" refers to the value
of a pixel relative to its neighbors. The present method detects
events using information from variations in the same pixel
throughout the image set, whereas a contrast-based method detects
events as outliers relative to pixels in the surrounding
neighborhood. A contrast method has difficulty separating outlying
pixel values from rapid changes in the brightness of persistent
features such as stars.
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Note:
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This method will detect a varying or
moving object as an "event" and reject it from the
images. Do not use this method if the image set contains a
target
object or feature that is varying in intensity or position
between the members of the image set.
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Cleaning also can be done when images are
combined using Sigma Clipping, Alpha Clipping, the Median, or
some other
image combining methods. The present command does not combine
the images but instead it identifies and, optionally, repairs the
events occurring in the separate images. If you want to combine the
cleaned images, use the
Combine Images command. In the present command, most
Repair Method options fix the event
pixels but the "Set Pixel to Zero" option prepares the images for
combining by the Masked Mean Value method (the "Mean - Masked by 0"
option in the
Combine Images command).
This method will identify outlying pixel values
regardless of what causes them. Therefore, you can use it to clean
cosmic rays and other radiation events as well as dead pixels and
under corrected hot pixels. For many applications, you do not want
to repair too many pixels. The Verbose Summary
option lists not only the number of events detected but also
the number of events as a percentage of the total pixel count. In
the example below, cleaning was done using settings shown above,
which resulted in a percentage of 0.2 to almost 1%. These values
would be quite high for 2 minute exposures if all the events were
caused by ionizing radiation of some type. In these images, the
algorithm is also detecting a number of pixels having poorly
corrected dark current.
Using the Clean Image Set command
Parameters of the Clean Image Set command
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Image Set to be Cleaned
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Select the
Image window containing the
image set to process. This command only works with image
sets and the list is updated as each new image window is
created, so be sure the target image window you want to
process is selected.
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Statistical Aggressiveness
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Controls the statistical cutoff for the
probability that an outlier pixel is actually a bad pixel. A
lower setting rejects pixel values that are more deviant
from the others and a higher setting rejects pixels that are
less deviant from the others.
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Sigma Rejection Strategy
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Controls whether more or fewer outlying
values are rejected and whether they are rejected
symmetrically about the mean.
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Repair Method
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Select the method to apply to the detected
outlier pixels. The Replace with Zero
method replaces the outlying pixels with a value of 0 for
combining using the "Mean - Masked by 0" method.
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Verbose Summary
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Check this box to give a verbose listing
of results in a Mira Text Editor window.
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Create Undo Copies
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Check this box to create Undo copies of
the image set, You can then use the
Undo (Ctrl+Z) command to
recover the original images, perhaps to try a new selection
of parameters. Not using this method helps conserve memory
if you are combining a large set of large images which use
most of the available memory.
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List Rejected Pixels
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Check this box to list the coordinates of
the rejected pixels. The listing is in a format which could
be saved to a
Pixel Mask file for additional processing.
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Display Rejection Map Image
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Check this box to display an image showing
the rejected pixels. The image has a zero background and is
encoded with a value that corresponds to the sequence number
of the image where that pixel was rejected. For example, a
pixel value of 3 means that the pixel was rejected from the
3rd image of the image set.
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Example
Below is a comparison between images before (top)
and after (bottom) cleaning. This comparison shows a single image
from the image set, not a combination of the cleaned images.
In the upper image, notice the radiation event
about 1/4 the way inward from the lower left corner, which falls
upon a star. In the lower image, notice how it was effectively
repaired while preserving the star. This would be difficult to
achieve by using just a single image since, in that case,
neighborhood pixels are used to determine what is an outlying pixel
relative to a "normal" pixel.
Image 1 before cleaning:
Image 1 after cleaning:
Below is the pixel rejection map image that is
produced when Display Rejection Map Image
is checked. The Map Image contains a pixel value that is the index
of the image in which the event was detected. For example, a value
of 1 indicates a pixel rejected in image 1 of the image set. Near
the upper right of the image, notice the moving blob which
corresponds to the minor plant Xanthippe that was moving during the
acquisition of the image set. The trail has values ranging from 1,
at the lower right, to 9 at the upper left, which corresponds to
images 1 through 9 of the image set. This illustrates the limitation
of the method: it will detect the pixels of a "significantly"
variable object or transient object as an "event" and reject it. How
significant is "too significant" depends upon the image properties
and your particular application.
Rejection map Image:
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