Fast In-Memory Data Compression Algorithm (inline C/C++) 480+MB/s compress, 2800+MB/s decompress, ratio% better than LZ4, Snappy, and Zstd@-1

🗜️ Library and application for lossless, format-preserving, two-pass optimization and repair of Vorbis data, reducing its size without altering any audio information.

TinyZZZ includes GZIP, LZ4, ZSTD, LZMA compression algorithms written in C language, unlike the official code, this code mainly focuses on simplicity and easy to understand.

An online .txt file compressor, de-compressor tool which uses Huffman Coding for Lossless data compression.

A tool to generate optimized hardware files for univariate functions.

A tool to generate optimized hardware files for univariate functions.

Really High Efficient File Optimizer will losslessly recompress files as much as possible according to their mime-types

Lossless audio encoding based in Golomb Rice Coding algorithm.

Simple tool to compress the entire set of photos and videos in a directory.

Huffman Coding implementation in Java for lossless data compression and decompression using a priority queue-based Huffman tree.

Experimental Hrust compressor with 8bits buffer. Forked from https://gitlab.com/eugene77/optimal-hrust-compressor

Nuxt3 | Shadcn | TailwindCSS | InspiraUI | File-comression app using ffmpeg scripts

FLAC lossless audio encoder-decoder for education purposes

MATLAB implementation of lossless image compression techniques for preserving image quality.

Lossless data compression algorithm, aimed at fast decompression speeds and better compression ratios than LZ4HC and other speed-oriented algorithms

A lossless compression algorithm combining data compression with cryptographic properties, achieving 50% compression ratio with basic data security. Built in C and Python.

Fast & free image compression tool that actually works

CLI tool for video processing (H.265/HEVC encoding & QuickTime compatibility) using FFmpeg, and batch lossless image compression with format preservation.

Serialize + compress Pandas DataFrames.

This project focuses on lossless compression techniques optimizing space, time, and energy for multiplications between binary (or ternary) matrix formats and real-valued vectors.