Image Decomposition using Independent Component Analysis (ICA)

University project. This notebook demonstrates how to use Independent Component Analysis (ICA) to separate an image into independent components.

Prerequisites

Before running the notebook, make sure you have the following dependencies installed:

• Python 3.x
• NumPy
• Matplotlib
• scikit-learn

You can install the required packages by running the following command: pip install -r requirements.txt

Getting Started

1. Clone or download the repository to your local machine.

2. Ensure that the mixed.jpg file is in the same directory as the notebook.

3. Run the notebook using a Jupyter Notebook environment or an integrated development environment (IDE) that supports Jupyter notebooks.

4. The notebook will load the mixed.jpg image, apply ICA to separate the image into foreground and background components, and display the results.

This notebook can also be tried in Google Colab here. Note that you need to upload your own mixed.jpg file.

License

Feel free to modify and use the code according to your needs.

Acknowledgments

This notebook was inspired by Laurent de Vito's project, which can be found here: https://github.com/ldv1/ICA_for_demixing_images. The implementation utilizes the scikit-learn library for ICA and other data preprocessing tasks. Please note that the image may be subject to copyright.

Note

This method of image decomposition might not always produce good results.