# kqwang/phase-recovery

Resources for phase recovery (also called phase imaging, phase retrieval, or phase reconstruction)

Repository: https://github.com/kqwang/phase-recovery
Canonical: https://ross.abutalabs.com/products/phase-recovery
Homepage: https://doi.org/10.1038/s41377-023-01340-x
License: MIT
License Family: permissive
Topics: computational-imaging, deep-learning, holography, interferometry, phase-imaging, phase-retrieval, wavefront-sensing, phase-reconstruction, phase-recovery, ptychography
Last push: 2026-06-11T08:51:45+00:00

## Health v2 (maintenance only)
Score: 68/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 87, release rhythm 35, longevity 85
- inputs: {"age_days": 1190, "days_push": 83, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1212, forks 74 (observed 2026-08-28T04:04:00.253807+00:00)

## What it is
A curated resource list accompanying the review paper 'On the use of deep learning for phase recovery' (Light: Science & Applications, 2024). It catalogs research groups, companies, workshops, papers, books, and theses covering conventional and deep-learning-based phase recovery techniques such as holography, interferometry, TIE, wavefront sensing, and ptychography.

## Use cases
- find papers on deep learning for phase retrieval
- learn about holography and interferometry techniques
- survey deep learning approaches for quantitative phase imaging
- find research groups working on computational imaging
- get references for phase unwrapping and aberration correction
- prepare a literature review on ptychography
- find tutorials and courses on wavefront sensing

## When to choose
- starting research on phase recovery or phase retrieval
- building a literature review for computational imaging
- looking for deep learning methods applied to optics
- finding active research groups or companies in phase imaging

## When to avoid
- you need runnable software or code implementations
- you want a general computer vision resource list
- you need production imaging tools rather than references

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, image-processing, computer-vision, documentation
- domain: computer-vision, image-processing, artificial-intelligence, deep-learning, tutorials, awesome-lists
- platform: cross-platform
- tags: phase-recovery, phase-retrieval, computational-imaging, holography, interferometry, ptychography, wavefront-sensing, quantitative-phase-imaging, curated-list, research-papers

## Member repositories
- kqwang/phase-recovery (main) score 68

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:00.253807+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:18:00.397541+00:00, confidence not recorded.
  - readme: https://github.com/kqwang/phase-recovery (fetched 2026-08-28T04:04:00.253807+00:00, sha 4370ac712628)
  - homepage: https://doi.org/10.1038/s41377-023-01340-x (fetched 2026-08-29T12:26:16.329527+00:00, sha 902869727e28)
- Data as of 2026-08-30T08:39:29.467469+00:00.