Title :
Joint entropy-scalable coding of audio signals
Author :
Movassagh, Mahmood ; Thiemann, Joachim ; Kabal, Peter
Author_Institution :
Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, QC, Canada
Abstract :
A fine grain scalable coding for audio signals is proposed where the entropy coding of the quantizer outputs is made scalable. By constructing a Huffman-like coding tree where internal nodes can be mapped to reconstruction points, we can prune the tree to control the distortion of the quantizer. Our results show the proposed method improves existing similar work and significantly outperforms scalable coding based on reconstruction error quantization as used in practical systems, eg. MPEG-4 audio.
Keywords :
Huffman codes; audio signal processing; encoding; entropy codes; error analysis; trees (mathematics); Huffman-like coding tree; audio signals; entropy-scalable coding; fine grain scalable coding; quantizer outputs; reconstruction error quantization; Bit rate; Distortion measurement; Entropy coding; Laplace equations; Merging; Quantization; Entropy coding; Quantization; Scalable coding;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
Conference_Location :
Kyoto
Print_ISBN :
978-1-4673-0045-2
Electronic_ISBN :
1520-6149
DOI :
10.1109/ICASSP.2012.6288537
