PyTorch library for solving imaging inverse problems using deep learning

Scientific computing library for optics, computer graphics and visual perception

Modular and scalable computational imaging in Python with GPU/out-of-core computing.

Scientific Computational Imaging COde

(Tensorflow Version) D-Flat is a forward and inverse design framework for flat optics. Although specially geared for the design of metasurface optics, it may be used for any end-to-end imaging and sensing task.

Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with rigorous, distribution-free uncertainty quantification.

Compressed Sensing: From Research to Clinical Practice with Data-Driven Learning

Keras Implementation of the paper Residual Feature Distillation Network for Lightweight Image Super-Resolution

[CVPR'19] End-to-end Projector Photometric Compensation

3D reconstructions of mm-scale objects from sequences of phone camera images

Repository for ptychography software

Clinically-Interpretable Radiomics [MICCAI'22, CMPB'21]

[ICCV'19] CompenNet++: End-to-end Full Projector Compensation

Tools for designing x-ray phantoms and experiments.

Demo for single-pixel imaging using Hadamard functions as sensing basis. Matlab/Python implementations

Python Implementation of the CoLlAGe radiomics descriptor. CoLlAGe captures subtle anisotropic differences in disease pathologies by measuring entropy of co-occurrences of voxel-level gradient orientations on imaging computed within a local neighborhood.

Learning a probabilistic strategy for computational imaging sensor selection (cosense)

The code repository for the 2023 ICCP Paper: Polarization Multi-Image Synthesis with Birefringent Metasurfaces

This repository is the official PyTorch implementation of "Mosaic Convolution-Attention Network for Demosaicing Multispectral Filter Array Images" (TCI 2021)

I use U-net to reconstruct the fresnel diffraction images.