Title :
DCT-compressive sampling of multifrequency sparse audio signals
Author :
Moreno-Alvarado, R.G. ; Martinez-Garcia, Mauricio ; Nakano, Mariko ; Perez, Hector M.
Author_Institution :
Fac. de Ing., Univ. La Salle, Mexico City, Mexico
Abstract :
In this paper, we propose to apply the discrete cosine transform (DCT) and the compressive sampling (CS) techniques to audio signal compression. Using spectral analysis and the properties of the DCT, we can treat audio signals as sparse signals in the frequency domain. This is especially true for sounds representing tones. Thus, we propose the use of DCT as a preprocessor in order to sparsely represent a signal in the frequency domain, combined with CS to obtain an efficient representation of the signals. We show that the subsequent application of CS represents our signals with less information than the well-known sampling theorem.
Keywords :
audio signals; compressed sensing; discrete cosine transforms; spectral analysis; DCT; audio signal compression; compressive sampling; discrete cosine transform; multifrequency sparse audio signals; spectral analysis; Compressed sensing; Discrete cosine transforms; Frequency-domain analysis; Image reconstruction; Multiple signal classification; Speech; Audio signals; Compression; Compressive sampling; Discrete Cosine Transform; Frequency sparse;
Conference_Titel :
Communications (LATINCOM), 2014 IEEE Latin-America Conference on
Conference_Location :
Cartagena de Indias
Print_ISBN :
978-1-4799-6737-7
DOI :
10.1109/LATINCOM.2014.7041859