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Maximum Entropy
The Maximum Entropy Deconvolution method
sharpens an image while reducing noise. Maximum entropy processing
works best on images having high contrast and high signal to noise
ratio. See this
Example. The
High Pass Filter runs faster but creates more noise
for a given amount of sharpening.
Properties of Maximum Entropy
Deconvolution
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Initial FWHM
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The Full Width at Half Maximum (FWHM) of the point
spread function for the image, measured in pixels. This measures
the amount of smearing in the image. It is important not to
overestimate this value or this could lead to rings around point
sources and edge ripples. The value should not be less than about
2.0.
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Camera Noise
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For a CCD camera, this is the Readout Noise. This
quantity is measured in electrons (e). For example, if the readout
noise is 9.2e-, enter 9.2.
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Camera Gain
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The ratio of output signal number to input
electrons. This is a value like "2.8", meaning 2.8 electrons per
Digital Number ("DN", also called "Count" or "ADU").
Electronically, this is actually the "inverse gain" but is referred
to as the gain for a CCD camera.
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Max Iterations
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Specifies the maximum number of iterations of the
deconvolution. Mira will stop early if no change is detected.
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 Use Cursor ROI
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If checked, only the region inside the cursor is
deconvolved. Otherwise, the entire image is processed.
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Using Maximum Entropy Deconvolution
Maximum Entropy only works with intensity images.
It does not work with RGB images. If you want to process an RGB
image, you will need to
extract the channels and process them
separately. However, the dynamic range will be lower since each
channel of the RGB image will have been reduced to 256 levels. For
RGB images, it is best to perform Maximum Entropy processing on the
intensity images before merging then into RGB form.
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Tip
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When MaxEnt processing is active, you can break out
of the loop at any time using the [Esc] key.
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Choosing Properties
For best results, the Properties must be chosen
carefully. Mira's implementation of Maximum Entropy processing uses
3 Properties: FWHM, Camera Noise, and Camera
Gain. The dialog shows two sets of Properties:
Values in the right column are shown simply as a
guide in choosing the Properties that are used from the left
column.
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The number of Iterations defines how many cycles to refine the
deconvolution result. More cycles are not necessarily better. Using
too few iterations does not give MaxEnt a chance to converge to a
good solution, whereas giving too many cycles can go beyond the
optimum result and lead to an overly processed appearance full of
artificial rings, dimples, and ripples. The number of iterations
will change with images of different properties and according to
the other Properties used. An iteration count in the range 20 to
100 is typical.
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The ROI, or Region of Interest, is the enclosing
rectangle where MaxEnt will be applied. This rectangle is defined
by the Image Cursor. Choose the ROI so that it encloses only the
region that needs to be enhanced. Enhancing the background may be
of little value so it is not worth waiting on the extra computing
time.
Related Topics
Spatial Filter Commands
Example of Maximum Entropy Processing
High Pass Filter
Mira Pro x64 User's Guide, Copyright Ⓒ 2023 Mirametrics, Inc. All
Rights Reserved.
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