This repository contains MATLAB, Python, and ImageJ/Fiji implementations of Deblurring by Pixel Reassignment (DPR), an image resolution enhancement method described in the publication below.
If you use this software or method in your research, please cite:
Zhao, B. & Mertz, J. Resolution enhancement with deblurring by pixel reassignment (DPR). Advanced Photonics 5(6), 066004 (2023).
🔗 10.1117/1.AP.5.6.066004
Deblurring by pixel reassignment (DPR) performs PSF sharpening by reassigning pixel intensities after image acquisition. The pixel reassignment step size depends on the local log-image gradient. See the paper for the scientific method, assumptions, and validation.
Python/: CPU and NVIDIA GPU Python implementations.MatLab/: MATLAB scripts and functions.ImageJ/: ImageJ/Fiji plugin source code.imgs/: documentation images.
To begin using the tools provided in this repository, please navigate to the specific directory of interest:
- Python implementations: Python/README.md.
- Python NVIDIA GPU implementation: Python/dpr_python_nvidia/README.md.
- MATLAB implementation: MatLab/README.md.
- ImageJ/Fiji plugin: ImageJ/README.md.
These individual README files will provide you with detailed instructions on setting up and running the applications.
Contributions are highly welcome! If you have enhancements, bug fixes, or improvements, please feel free to fork the repository and submit a pull request. You can also open an issue for bugs you might find or for feature requests.
Your feedback helps guide our development and improvements. Please take a moment to fill out the DPR Algorithm User Feedback questionnaire to help us better understand your needs and further improve DPR.
This project is made available under the MIT License. For more details, see the LICENSE file.
If you have any comments, suggestions, or questions, please do contact us at byzhao@bu.edu.