Adaptive constraints by morphological operations for single-shot digital holography

Area of Science:

• Optics and Photonics
• Image Reconstruction
• Wave Phenomena

Background:

• Digital holography enables quantitative measurement of complex wave fields, crucial for wave-matter interaction studies.
• Iterative phase retrieval methods solve inverse imaging problems using intensity data and physical constraints.
• Current methods face limitations in reconstruction accuracy and convergence due to imprecise constraints.

Purpose of the Study:

• To develop an advanced iterative phase retrieval framework for single-shot in-line digital holography.
• To enhance reconstruction accuracy, convergence speed, and achieve twin-image-free results.
• To incorporate adaptive constraints for improved performance and noise immunity.

Main Methods:

• Proposed an advanced iterative phase retrieval framework incorporating adaptive constraints.
• Utilized morphological operations for object structure extraction and noise/artifact removal.
• Implemented adaptive constraints for accurate estimation and automatic updating of the support region during iterations.

Main Results:

• Achieved optimized convergence behavior and high-fidelity reconstruction.
• Demonstrated twin-image-free reconstruction capabilities.
• Validated improved reconstruction performance and noise immunity through numerical simulations and experimental results.

Conclusions:

• The proposed adaptive constraint framework significantly improves single-shot in-line digital holography.
• This flexible and versatile method offers promising applications in biomedicine, X-ray coherent diffractive imaging, and wavefront sensing.