Tutorial: Introduction to Source
Extraction
This tutorial shows you how use the Source
Extraction Package to detect and measure the properties of
sources in one or more images. The
Source Extraction package is accessed using the
Measure >
Extract Sources command for an Image Window. The
Source Extraction Package is immensely powerful and has a great
number of important and varied applications. In this tutorial it is
used simply to examine the FWHM values for many stars in a small
region of an astronomical image. A quick overview of the extraction
procedure is also described in
Running the Source Extraction Pipeline.
Overview
Source extraction involves the detection and
measurement of all sources brighter than a threshold value. This
processing uses a chain of operations called a "pipeline". Each
step in the pipeline involves Properties that control its
operation. Because Mira allows so many variations for the steps
used in the pipeline, a Profile control is used to manage the
procedure. The pipeline is operated from the
Source
Extraction Properties. After you have choose a profile or set
your Properties, you run the pipeline by clicking the [Process] button.
The source extraction pipeline creates a procedure
for each selected processing step. The steps you select are applied
in a specific order, hence the term "pipeline" to describe a single
direction of flow in the processing. The first step in source
extraction involves determining the background level. Knowing the
background at each point, each pixel can be tested against the
threshold above background; if the pixel exceeds the threshold, it
is tagged as a source candidate. All candidate pixels are then
collected into sources completely separated from others by a
boundary at the specified threshold level. In this way, the sources
are like islands poking above sea level. Source properties such as
intensity, ellipticity, area, and others are then computed. The
final processing step involves filtering this source list to retain
only the sources that meet criteria such as being within a certain
range of area or ellipticity. The list of sources extracted from
the image(s) may then be further analyzed using Mira tools or saved
for analysis by other software.
Getting Started
To begin, use the File > Open command to
load the Open dialog. As shown below, select the sample image
BL-CAM.fts. Before opening the image,
be sure the "Flip FITS Image" option is not checked in the
Options list at the bottom of the
Open dialog. Then click [Open]
to display the image in Mira.
After opening the image, click on the ,main toolbar or use the Measure
>
Extract
Sources command in the menu. This opens the Source
Extraction Toolbar which operates all the commands of the
Source Extraction package. As typical in Mira, the toolbar
opens on the left border of the image window with marking mode
active:
Use the
Image Cursor Properties dialog to adjust the
Image Cursor as shown above, to a size of 250 x 200
pixels and centered at coordinate (431,241).
The toolbar commands are described below. In this
tutorial, the only buttons you will use are the first and last
ones:
Notice that this toolbar has no "marking mode", as
is usually the top-most button on the toolbar. Source extraction
does not involve an interactive marking mode. However, the top-most
button does open the
Source
Extraction Properties which you use to automatically identify
and extract the source information.
Loading the Tutorial Properties
Next, we will load the extraction Properties to be
used in this tutorial. On the toolbar, click the button to open the "Source Extraction" dialog.
Now you need to set the values on all the pages of the dialog. The
Profile control makes this easy. The tutorial Properties have been
pre-defined and stored in the profile named "Tutorial". At the top
of the dialog, click the drop arrow and select "Tutorial" as shown
below. Be certain the Use Cursor ROI
box is checked so that only the cursor is searched for sources.
When the profile is loaded, Mira sets all the
Properties on on all dialog pages to those values stored in the
profile. To see what all dialogs should look like for this
tutorial,
click here. Note that, in this tutorial, you
will not be using the Multiple
Images options (Matching and Difference) because
only a single image has been loaded. If you double click on
Multiple Images to open its options, you will see all options
disabled with X marks. As a consequence, the Properties on the Match
and Diff pages are not used.
Running the Extraction Pipeline
Next, you will run the pipeline using the
"Tutorial" profile. With the Source Extraction pipeline dialog
open, click [Process]. After a
moment, the pipeline finishes and the Source Extraction
Messages window opens as shown below:
The Messages window was created because the
Verbose box was checked on the
Procedure page. This is a standard Mira
Text Editor window, so the results listed here can be
edited or saved for your records.
There are a number of things to be learned from the
Messages window. The first interesting point is that 930
sources were identified inside the rectangular region of the image
cursor but setting a minimum area of 4 pixels discarded 826 of
them, leaving 104 sources 4 pixels or larger. At this very low
threshold above background, a large number of hot pixels were
detected. You could verify this by re-running the pipeline after
unchecking Min Area and setting
Max Area = 2 pixels on the
Filter page. Second, the Finding, Detecting,
and Filtering steps required negligible time to complete, but 0.51
seconds was required to compute the Precision FWHM in the
post-processing step. If you re-run the pipeline to count the
number of tiny bumps, the "computationally expensive" FWHM step is
not necessary and should be turned off.
Since the Label step was checked in the procedure,
the result of the extraction pipeline looks like the image below,
with the final sources marked and tagged with a number. This image
was zoomed 2x to give better separation between markers.
Using the magnify mode or your mouse thumb wheel,
zoom the image to 4X so it looks like the picture below. You can
now see the kinds of sources that were detected. Notice how bright
the faintest sources are compared with the sky noise. This makes it
apparent how well Mira's centroiding algorithm works for faint
sources. For example, see sources 44 and 45 in the image below.
Since we selected Report
Method = "No Report" on the
Procedure page, the source properties extracted from
BL-CAM-2.fts were not listed anywhere.
Choosing not to display the results can save time if a large number
of sources are detected, especially if you do not know if you want
to save the results (Hint: You can maximize the scrolling speed of
the report window by keeping Auto-optimizing the column widths).
However, you can view the information after the fact. In this case,
only 83 sources passed the filtering and that is quick to display
in a Report window. Click to open the
Source
Extraction Properties and select the
Procedure page. Click the [List] button and the
Report window opens as in the picture below (this is
shown scrolled down to source 66). Close the Properties
dialog so you can continue using the other windows.
If you want to save the se results, make sure the
Report window is top-most and use the File > Save
As command.
Analyzing the Extraction Data
You can do many things with the tabular data in a
Report window, including saving it to a text file,
copying onto the Windows Clipboard, or rearranging the columns and
sorting the rows to make comparisons (see
Grid Controls). In addition, you can create a
Create Plot from Grid to examine relationships
between the source properties.
Make the Source Extraction Report the
top-most window and click the View >
Create Plot from Grid command in the menu. You
can also access commands like Create Plot from Grid by
right-clicking inside the Report window to open the
Grid Context Menu. The Create Plot from Grid
command opens a setup dialog like this:
In the Create Plot from Grid dialog, you
select which columns of report data to plot on the horizontal and
vertical axes. Optionally, you can also set a title and select
columns containing data to be used as error bars. It would be
interesting to examine whether the FWHM value depends on the
Ellipticity of the star. To do this, use the two left-hand list
boxes to select "Ellip" as the X Axis
Variable and "FWHM" as the Y Axis
Variable. This will produce a graph showing FWHM versus
Ellipticity for all the extracted sources. Click [Plot] to create the graph like this:
We can see that the typical FWHM is around 3.2
pixels and shows no obvious trend as a function of the
Ellipticity.
Previously sources 44 and 45 were mentioned as
being quite faint. What is the faintest source detected? To get an
answer, select the Source Extraction report window and click the
Lum column header to sort the table by Luminosity. This puts
Source 29 at the top of the list as being the faintest source. To
locate this source in the image, right-click the table row of the
Source 29 to open the window's context menu. Select Go to Object as shown here:
The Go To Object
command shifts the displayed image to the coordinates of the source
who's table row was clicked (note: this is different from the
Go to Object command in the Coordinates menu). If you expose the
Image Window containing the BL-CAM.fts image, you will see it centered as
shown below. The magnification value was set on the
Procedure page of the
Source
Extraction Properties.
What is the FWHM value for this source? Hold down
the Shift key and click the mouse
pointer on source 29 in the Image Window. This moves the
Image Cursor to Source 29. Right click on the image
to open the Image Context menu and select the Plot > Radial Profile command to create a
Radial Profile Plot like the one shown
below.
The FWHM of 3.958 for the incredibly faint Source
29 is slightly larger than the average for the sources
detected.
In this Tutorial you have learned how to setup and
use the Source Extraction Package to detect and extract
information about sources in an image. Using a similar strategy but
with different Properties such as filtering limits, one can use the
Measure > Extract Sources command
and other Mira tools to do such varied projects as counting bad
pixels, characterizing optical aberrations across the field of
view, or hunting for galaxies using their higher ellipticity and
lower values of CI or their higher FWHM as classification
criteria.
Related Topics
Contents
Tutorials
Getting Started
Extracting Sources from Images
Source
Extraction Properties
Running the Source Extraction Pipeline
Mira Pro x64 User's Guide, Copyright Ⓒ 2023 Mirametrics, Inc. All
Rights Reserved.
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