Welcome to the Compression Algorithms repository! This project contains implementations of various compression algorithms, designed to reduce the size of data without losing significant information. This is useful in numerous applications such as file storage, data transmission, and reducing bandwidth usage.
This repository includes implementations of the following compression algorithms:
- Huffman Coding: A popular method that uses variable-length codes to represent characters, with shorter codes assigned to more frequent characters.
- LZ77 (Lempel-Ziv 1977): A dictionary-based compression algorithm that replaces repeated occurrences of data with references to a single copy.
- LZ78 (Lempel-Ziv 1978): An improvement on LZ77, using a dictionary dynamically built during the encoding process.
- Run-Length Encoding (RLE): A simple compression method that replaces sequences of the same data values with a single data value and a count.
- Vector Quantization: A quantization technique often used in lossy compression where input data is divided into blocks, and each block is represented by the closest match from a predefined set of vectors (codebook).
- Predictive Coding: A compression method that uses the prediction of future data points based on past data to encode the difference between the predicted and actual values.