OBHS实现高效率低延迟音频无损压缩，适合实时流媒体。
OBHS: An Optimized Block Huffman Scheme for Real-Time Audio Compression
- 分块哈夫曼编码+规范码表，提升压缩效率
- 静音音频压缩率达93.6%，全类型音频表现稳定
- 线性时间复杂度，适合嵌入式实时场景
本文提出一种面向实时流媒体的新型无损音频压缩算法OBHS（Optimized Block Huffman Scheme）。该算法采用分块哈夫曼编码，结合规范码表示与智能降级机制，在保持低计算复杂度的同时实现高压缩比。系统将音频数据划分为固定大小的块，为每块构建最优哈夫曼树，并使用规范码进行高效存储与传输。实验表明，对于富含静音的音频，OBHS可达到最高93.6%的压缩率，且在粉噪声、纯音及真实录音等多种音频类型上均表现良好。算法时间复杂度为O(n)，其中n为音频样本数，有效平衡了压缩效率与计算开销，适用于资源受限的实时音频流传输场景。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。