A Comparative Study of Audio Compression Based on Compressed Sensing and Sparse Fast Fourier Transform (SFFT): Performance and Challenges

摘要

Audio compression has become one of the basic multimedia technologies.Choosing an efficient compression scheme that is capable of preserving thesignal quality while providing a high compression ratio is desirable in thedifferent standards worldwide. In this paper we study the application of twohighly acclaimed sparse signal processing algorithms, namely, CompressedSensing (CS) and Sparse Fart Fourier transform, to audio compression. Inaddition, we present a Sparse Fast Fourier transform (SFFT)-based framework tocompress audio signal. This scheme embeds the K-largest frequencies indices aspart of the transmitted signal and thus saves in the bandwidth required fortransmission