Huffman Image Compressor

Overview

This project is an image compression tool implemented in Java that uses Huffman Coding to compress and decompress PNG images. Huffman Coding is a lossless data compression algorithm that assigns variable-length codes to input characters, with shorter codes assigned to more frequent characters. This project provides a simple interface to open PNG images, create or update Huffman trees, compress images, and decompress Huffman-coded images.

Features

1. Open images: Load a locally stored images and render it. Accepted formats include ".png", ".bmp", and ".tiff".
2. Train Huffman Tree: Extract pixel information from the loaded image to create a new Huffman tree or update an existing one. The Huffman tree is saved in a .huff file.
3. Compress Image: Convert the loaded image into a Huffman-coded format, saving it as a new file with a custom extension .kabak.
4. Open Huffman Coded Image: Load and render a Huffman-coded image file.

How It Works

Huffman Coding

Huffman Coding is a method of compressing data by creating a binary tree of nodes. The steps are as follows:

1. Frequency Calculation: Calculate the frequency of each pixel value in the image.
2. Tree Construction: Build a Huffman tree where each leaf node represents a pixel value and its frequency. The tree is constructed by repeatedly combining the two nodes with the lowest frequencies into a new node until one node remains. This program implements delta encoding to minimize storage consumption.
3. Code Assignment: Traverse the Huffman tree to assign binary codes to each pixel value. More frequent pixels get shorter codes.
4. Compression: Replace each pixel in the image with its corresponding Huffman code.
5. Decompression: Use the Huffman tree to convert the binary codes back to the original pixel values.

Implementation Details

1. Opening images: The program uses Java's image processing libraries to load and display PNG images. After, image files are moved to the 'inputs' folder for better organization of files.
2. Training the Huffman Tree: The program reads the pixel data from the image, calculates the frequency of each pixel, and constructs the Huffman tree. The tree can be saved to a .huff file for later use.
3. Compressing Images: The program traverses the Huffman tree to generate codes for each pixel and writes the compressed data to a new file.
4. Decompressing Images: The program reads the Huffman-coded file and uses the Huffman tree to reconstruct the original image.

Repository Structure

• src/: Contains the Java source code.
  • Main.java: The main class that handles user input and program flow.
  • HuffmanCompressor.java: Implements the Huffman tree construction and traversal. Additionally, this handles image loading, compression, and decompression.
  • GUI.java: Creates the overall GUI design.
• assets/inputs/: Sample PNG images for testing.
• assets/output/: Directory where compressed and decompressed images are saved.
• README.md: This file.

Usage

1. For first time of use, select 'New' and choose an image.
2. Select 'Train' button to create a Huffman tree for the selected image file.
3. The 'Compress' button will create a compressed file using the Huffman codes from the huffman tree.
4. You may open the output image using the 'Open' button and see the comparison between the original file size and the Huffman-coded images.

Contributions are welcome! Please fork the repository and submit a pull request with your changes.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature)
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Acknowledgments

• This project was created as a part of CMSC 123 at University of the Philippines Tacloban College.
• Based on Huffman coding algorithm for efficient data compression.
• Huffman, D. A. (1952). "A Method for the Construction of Minimum-Redundancy Codes". Proceedings of the IRE.

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