This repository contain two part：1.Code about how to use matlab connect the Zemax 2. Image reconstruction model bulid used the learnable physical priors and frequency domain attention
1.)Matlab 2021a. Too early versions cannot be used.
2.)zemax 18.9. Version 19 has compatibility issues and does not work well.
3.)python3
NVIDIA GPU + CUDA cuDNN
pytorch 1.7 or 1.9, the code is slightly different.
requirements： numpy ~= 1.14.3
scipy ~= 1.0.1
future ~= 0.16.0
matplotlib ~= 2.2.2
pillow ~= 5.0.0
opencv-python ~= 3.4.0
scikit-image ~= 0.14.0
pyaml
easygui
1 Matlab connection zemax
Zemax Optic Studio open a file, Click 'Programming'、'Interactive Extension' connect to the ZOS-API. Use Matlab open 'MATLABZOSConnection.m' and run it.
2 Use the genetic algorithm to dynamic optimization the phase mask
Use Matlab open 'MATLABStandaloneApplication.m' and add code to the '% Add your custom code here...'
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Use psf which obtained by simulation or real photography to generate the encoded data. Or you can use a Optical System with phase mask get the encoded data, but it is a little hard to complete thousands of pictures.
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Prepare the train and val data
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Train the model, and test it
（Recently we are preparing the thesis, the specific code will be released after streamlining and organizing. If you need it, contact me and I'll speed things up.）
We list the core code below and explain it:
- As I note in Step 2, at the '% Add your custom code here...' need add the code. The step see "Code of optimized phase mask".
- Code about the 3 modules (Plug-and-play module), see "Code of our model".
- Loss function of our model.
If you use this code for your research, please cite our papers "Wavefront coding image reconsturction via physical prior and feequency attention" [https://opg.optica.org/oe/fulltext.cfm?uri=oe-31-20-32875&id=538461]