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Modified BTC Algorithm for Audio Signal Coding
Author(s) -
Stefan Tomić,
Zoran Perić,
Jeleikolić
Publication year - 2016
Publication title -
advances in electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 23
eISSN - 1844-7600
pISSN - 1582-7445
DOI - 10.4316/aece.2016.04005
Subject(s) - computer science , speech coding , sub band coding , algorithm , coding (social sciences) , audio signal , speech recognition , audio signal processing , anti aliasing , mathematics , statistics
This paper describes modification of a well-known image coding algorithm, named Block Truncation Coding (BTC) and its application in audio signal coding. BTC algorithm was originally designed for black and white image coding. Since black and white images and audio signals have different statistical characteristics, the application of this image coding algorithm to audio signal presents a novelty and a challenge. Several implementation modifications are described in this paper, while the original idea of the algorithm is preserved. The main modifications are performed in the area of signal quantization, by designing more adequate quantizers for audio signal processing. The result is a novel audio coding algorithm, whose performance is presented and analyzed in this research. The performance analysis indicates that this novel algorithm can be successfully applied in audio signal coding

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