quadtree-image-processing

QuadTree image processing project for CS 211 at the University of Oregon

A Python implementation of a QuadTree data structure for efficiently representing and reconstructing binary images.
Built as part of the University of Oregon CS 211 course, this project demonstrates recursive data structures, object-oriented programming, and image processing.

Features

• Reads binary image files and converts them into a recursive QuadTree structure
• Efficiently represents images with large uniform regions
• Supports reconstruction of images at various resolution levels
• Provides a string representation of the QuadTree for debugging
• Visualizes original and reconstructed images using Python plotting

Technologies & Skills

• Python 3.10+
• Object-Oriented Programming (OOP)
• Recursion & Data Structures (QuadTree)
• Image Processing & Visualization (Matplotlib, NumPy)
• Git & GitHub

Project Structure

project_6/ ├── Template/ │ ├── QuadTree.py # Main QuadTree class and reconstruction logic │ ├── binary_matrix.py # Helper functions for reading/manipulating matrices │ ├── images/ # Sample binary images │ │ └── fisherman.txt │ └── README.md

6. How to Run

1. Clone the repository:

   git clone https://github.com/05ashton/quadtree-image-processing.git

2. Navigate to the project folder: cd project_6/Template

3. Run the program: python3 QuadTree.py

4. The program will read the sample image, construct a QuadTree, and display the reconstructed image.

Author

Ashton Curl – University of Oregon, Computer Science
GitHub | [LinkedIn (https://www.linkedin.com/in/ashton-curl-a7b804371/)