Predicting optical performance requires more than evaluating a single metric. A complete assessment must consider the combined effects of diffraction, aberrations, distortion, relative illumination, image orientation, and polarization.
In Zemax OpticStudio, one of the most powerful tools for system-level performance evaluation is Image Simulation. This tool predicts real image formation by convolving an input bitmap scene with a grid of Point Spread Functions (PSFs) across the field of view.
The result is a realistic visual representation of how an optical system will actually image a scene—far beyond spot diagrams or MTF curves alone.
What Is Image Simulation?
Image Simulation models image formation by:
Sampling PSFs at multiple field points
Including:
Diffraction
Aberrations
Relative illumination
Polarization effects
Convolving these PSFs with a source bitmap image
This approach allows designers to visually inspect:
- Resolution loss
- Field-dependent blur
- Distortion
- Vignetting
- Contrast variation across the image
In many cases, default settings provide useful results. However, understanding the calculation steps is essential for correct interpretation and accurate prediction.
Example System: Fluorescence Detection Optics
In this example, we demonstrate Image Simulation using a fluorescence detection system with:
- Operating wavelength range: 440 nm – 770 nm
- Large field of view
- Multi-spectral performance requirements
Because Image Simulation references system field units, it is generally best to set: Field Type: Object Height
In this case:
Field size = 50.38 × 33.58 mm
The input scene can also be:
- Rotated
- Flipped
- Resampled
- Centered on any field point
This flexibility makes Image Simulation suitable for real detector and sample geometries.
When Image Simulation runs:
A grid of PSFs is computed across the input scene
The grid spans the entire field of view
Each PSF represents:
Local aberrations
Polarization
Relative illumination
The final image is produced via convolution
In this example, the central PSF is very well formed, indicating good on-axis performance.
Step-by-Step Image Simulation Workflow
1. Select the Input Scene
In Image Simulation Settings, set Input File to:MBS-overview-Image analysis-1080-720
This bitmap represents the object being imaged by the system.
2. Start with a Single PSF (Distortion Check)
To isolate distortion:
- Define and propagate a single on-axis PSF
- This makes the PSF grid effectively a delta function
Settings:
- Show As: Simulated Image
- Pixel Size, X-Pixels, Y-Pixels: set to 0 (default)
This allows you to observe geometric distortion only, without blur.
3. Detector Reference Selection
Using the Reference setting, you can choose:
- Chief Ray → Detector moves with the field point
- Image Surface Vertex → Detector remains fixed
These two choices produce visibly different results and should be selected based on whether you want:
- Field-centric imaging
- Fixed detector analysis
You can directly compare the effect of each reference mode.
4. Choose PSF Calculation Type
Select Geometric or Diffraction based on system performance:
Use Geometric if RMS spot radius ≫ Airy disk
Use Diffraction if:
Spot radius ≈ Airy radius
System is diffraction-limited over part of the field
In this example:
- RMS spot ≈ 10 µm
- Airy disk ≈ 0.96 µm
→ Geometric PSF is appropriate.
5. Define the PSF Grid Density
Set PSF-X Points and PSF-Y Points carefully:
- Increase values until results converge
- If changing values does not alter the image noticeably, sampling is sufficient
If a PSF grid point spans only one pixel:
- The PSF is too small relative to bitmap pixel size
- Reduce bitmap resolution or PSF sampling
- Ensure each PSF spans multiple pixels
Performance and Speed
Image Simulation is:
- Fully multi-threaded
- Uses all available CPU cores
- Provides excellent signal-to-noise
- Extremely fast, even for large images
This makes it practical for design iteration, system trade-offs, and customer demonstrations.
Why Image Simulation Matters
Image Simulation allows prediction of:
- Aberrations
- Distortion
- Diffraction blur
- Illumination fall-off
- Polarization effects
- Real image appearance
All in one intuitive visual result, bridging the gap between analytical metrics and real-world imaging.
References