Dynamic Bit-Plane Arithmetic Coding Method for Quantized Spectral Coefficients in USAC
Seon‐Jae Kim, Byeongho Jo, Seungkwon Beack, Tae‐Jin Lee, Dongsan Jun · IEEE Journal of Selected Topics in Signal Processing · 2025
The increasing demand for high-quality audio content in applications such as media streaming and immersive audio services has driven the development of efficient audio coding techniques. Among these techniques, entropy coding is an essential component for the lossless compression of quantized spectral coefficients, which constitute the largest portion of the compressed audio bitstream. As the latest audio coding standard, Unified Speech and Audio Coding (USAC) has adopted ContextAdaptive Arithmetic Coding (CAAC) to employ its entropy coding method. Although CAAC can provide efficient lossless coding, it has several limitations, including bit overhead caused by variations in bit lengths between coefficients and considerable memory requirements for storing multiple context tables. To reduce excessive memory consumption, this study proposes Dynamic Bit-plane Arithmetic Coding (DBAC) as a new entropy coding method for quantized spectral coefficients. DBAC mitigates the bit overhead by using escape symbols for binarized coefficients and reduces memory usage while maintaining coding performance, even with marginal coding gains. In addition, the generation and selection methods of newly designed multiple contexts are also introduced to optimize arithmetic coding on the proposed dynamic bit-plane of DBAC. Experimental results demonstrate that the proposed method achieves 30% memory reduction with comparable coding performance compared to USAC.