An adaptive tree-based progressive audio compression scheme

Stefan Strahl, Huan Zhou, Alfred Mertins


A fine-grain scalable and efficient audio compression scheme based on adaptive significance-trees is presented. Common approaches for 2-D image compression like EZW (embedded wavelet zero tree) and SPIHT (set partitioning in hierarchical trees) use a fixed significance-tree that captures well the inter- and intraband correlations of wavelet coefficients. For 1-D audio signals, such rigid coefficient correlations are not present. We address this problem by dynamically selecting an optimal significance-tree for the actual audio frame from a given set of possible trees. Experimental results are given, showing that this coding scheme outperforms single-type tree coding schemes and performs comparable to the MPEG AAC coder while additionally achieving fine-grain scalability.

Original languageEnglish
Title of host publicationIEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2005
Number of pages4
Publication date01.12.2005
Article number1540209
ISBN (Print)0-7803-9154-3
Publication statusPublished - 01.12.2005
Event2005 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics - New Paltz, United States
Duration: 16.10.200519.10.2005
Conference number: 68220


Dive into the research topics of 'An adaptive tree-based progressive audio compression scheme'. Together they form a unique fingerprint.

Cite this