Resources for phase recovery (also called phase imaging, phase retrieval, or phase reconstruction)
physical optics: integrated modeling, phase retrieval, segmented systems, polynomials and fitting, sequential raytracing...
Python package for high-performance spatial light modulator (SLM) control and holography. Supports features from aberration-corrected 3D point clouds to automated Fourier-domain calibrations.
This is the open source repository for our SIGGRAPH 2018 paper "Megapixel Adaptive Optics: Towards Correcting Large-scale Distortions in Computational Cameras".
Tools for Optical Simulations
Python tools for JWST Wavefront Sensing Software
Phase diversity method for atmospheric wavefront sensing from a pair of images (in focus and out of focus).
reference implementation of contemporary "forward-reverse" or "iterative transform" phase retrieval algorithms
A comprehensive sensor library for Shack-Hartmann Wavefront Sensors
Graphical user interface for wavefront measurement using spatial-carrier fringe-pattern analysis.
Implements a diffuser-based wavefront sensor
Orthogonal polynomials for optics analysis
Solutions to the Transport-of-Intensity Equation (Speckle-Tracking, Paganin Algorithm etc.,)
Software for Nature Photonics publication on Wavefront shaping in complex media with a 350 kHz modulator via a 1D-to-2D transform
End-to-end AO pipeline: SH-WFS centroiding (127x C speedup) → CNN/MMSE reconstruction (Strehl 0.9987) → LQG closed-loop control → SLODAR turbulence profiling | BAH 2026 Challenge #9
Python toolkit for synchronized SLM pupil segmentation and image acquisition.
ResNet based CNN model for WFS developed by Pranjal
Utility functions for image-based phase retrieval
Fast Shack-Hartmann wavefront sensor pipeline: real-time wavefront reconstruction, atmospheric turbulence characterization (Fried parameter r0, coherence time τ0), and deformable-mirror actuator maps with inter-actuator coupling. Self-contained C real-time core (~0.3 ms/frame) + Python toolkit. ISRO BAH 2026 - Problem Statement 9.
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