A comparative study of audio compression based on compressed sensing and Sparse Fast Fourier transform (SFFT): Performance and challenges

Author

Kasem, Hossam M. ; El-Sabrouty, Maha

Author_Institution

Electron. & Commun. Eng., Egypt-Japan Univ. of Sci. & Technol. (EJUST), New Borg El-Arab, Egypt

fYear

2013

Abstract

Audio compression has become one of the basic multimedia technologies. Choosing an efficient compression scheme that is capable of preserving the signal quality while providing a high compression ratio is desirable in the different standards worldwide. In this paper we study the application of two highly acclaimed sparse signal processing algorithms, namely, Compressed Sensing (CS) and Sparse Fart Fourier transform, to audio compression. In addition, we present a Sparse Fast Fourier transform (SFFT)-based framework to compress audio signal. This scheme embeds the K-largest frequencies indices as part of the transmitted signal and thus saves in the bandwidth required for transmission.

Keywords

audio coding; compressed sensing; data compression; fast Fourier transforms; K-Iargest frequencies; SFFT; audio compression; compressed sensing; compression scheme; multimedia technologies; signal quality; sparse fast Fourier transform; sparse signal processing algorithms; Discrete Fourier transforms; Discrete wavelet transforms; Indexes; Iterative decoding; Minimization; Sensors; Time-frequency analysis; Audio signal; Compressed Sensing; Sparse Fast Fourier Transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Information Technology(ISSPIT), 2013 IEEE International Symposium on

Conference_Location

Athens

Type

conf

DOI

10.1109/ISSPIT.2013.6781923

Filename

6781923