Creating Synthetic Images

Creating Synthetic Images in MiraThe Create Synthetic Image command provides a valuable asset for precision imaging in science, engineering, and industrial applications, allowing you to create exact images containing all sources of noise with known properties. This tool is a critical asset for testing of algorithms and numeric analyses leading to improved modeling and evaluation of techniques.

For use in astronomy, biomedical methods such as FISH, and numerous other applications, the synthetic image can include a distribution of Gaussian point sources randomized in both location and luminance/intensity space (see the zoomed synthetic image set displayed at lower right). The pre-noise properties of each source are listed to create a record of the input values for comparison purposes. This leads to realistic emulation of model images that would be obtained using real instrumentation acquiring real data.

Synthetic Image

Application Examples

  • Test algorithms and numerical techniques.
  • Compare cameras and other instrumentation with expected noise performance.
  • Evaluate scripted algorithms in real-world simulations.


The image below was created with background=1000.0 DN, gain=2.0, readout noise=8.0e-, FWHM=2.5 pixels, extra base noise=0.0, and 10,000 stars. The full-scale screenshot allows the noise behavior to be seen. Stars are placed randomly in position and selected randomly from a stellar luminosity function.

Synthetic Image

Shown below is the output list of stars created for the synthetic image shown above. This output option is provided as a record of the exact initial values before applying the noise model, making it a valuable tool for evaluating algorithms, particularly as an adjunct to script development..

Synthetic image log

To center the image window on a particular object in the list, right-click on its table entry and select "Go to Object" as shown below:

Synthetic image menu

Notice the "Scatter Plot" command in the menu above. The next two pictures show the result of plotting X versus Y coordinates and Intensity versus X coordinate.

Scatter plot X vs Y

Objects in the scatter plot above show the random placement of stars in the field. The scatter plot below shows how the stellar luminosity function increases the star density toward fainter limits.

Scatter plot Intensity vs X


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