OBHS: An Optimized Block Huffman Scheme for Real-Time Audio Compression

TL;DR

OBHS is a real-time lossless audio compression algorithm that uses block-wise Huffman coding with canonical codes, achieving high compression ratios and low computational complexity suitable for streaming.

Contribution

Introduces OBHS, a novel block Huffman scheme with canonical codes and fallback mechanisms, optimized for real-time audio compression.

Findings

Achieves up to 93.6% compression for silence-rich audio.

Maintains competitive performance across various audio types.

Operates with linear time complexity O(n).

Abstract

In this paper, we introduce OBHS (Optimized Block Huffman Scheme), a novel lossless audio compression algorithm tailored for real-time streaming applications. OBHS leverages block-wise Huffman coding with canonical code representation and intelligent fallback mechanisms to achieve high compression ratios while maintaining low computational complexity. Our algorithm partitions audio data into fixed-size blocks, constructs optimal Huffman trees for each block, and employs canonical codes for efficient storage and transmission. Experimental results demonstrate that OBHS attains compression ratios of up to 93.6% for silence-rich audio and maintains competitive performance across various audio types, including pink noise, tones, and real-world recordings. With a linear time complexity of O(n) for n audio samples, OBHS effectively balances compression efficiency and computational demands, making it highly suitable for resource-constrained real-time audio streaming scenarios.