https://github.com/tsvikas/image-phase-registration
Image registration with rotation, using Phase Correlation Method
https://github.com/tsvikas/image-phase-registration
Last synced: 12 months ago
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Image registration with rotation, using Phase Correlation Method
- Host: GitHub
- URL: https://github.com/tsvikas/image-phase-registration
- Owner: tsvikas
- Created: 2025-04-30T12:14:45.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-30T13:32:18.000Z (about 1 year ago)
- Last Synced: 2025-05-19T11:11:34.280Z (about 1 year ago)
- Language: Jupyter Notebook
- Size: 1.41 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Image Registration (Rotation + Translation) via Phase Correlation
This repository demonstrates how to register two images when one is a rotated and translated version of the other.
## Overview
The method uses **[Phase Correlation](https://en.wikipedia.org/wiki/Phase_correlation)**,
extended to handle rotation by analyzing the **[Fourier Transform (FFT)](https://en.wikipedia.org/wiki/Fast_Fourier_transform)**
in **[polar coordinates](https://en.wikipedia.org/wiki/Polar_coordinate_system)**.
This approach is effective even for images without image features.
## Code & Explanation
**All the code, step-by-step explanations, and examples are in the [Jupyter Notebook](notebook.ipynb)**
Please refer to the notebook for detailed algorithm steps, visualizations, and usage examples.
## Setup & Dependencies
This project uses [`uv`](https://github.com/astral-sh/uv) for managing dependencies and the virtual environment.
Dependencies are listed in the `pyproject.toml` file.
## Usage
1. **Clone the repository:**
```bash
git clone github.com/tsvikas/image-phase-registration.git
cd image-phase-registration
```
1. **Run with JupyterLab:**
```bash
uv run jupyter lab notebook.ipynb
```