Blind Suppression of Nonstationary Diffuse Acoustic Noise Based on Spatial Covariance Matrix Decomposition

We propose methods for blind suppression of nonstationary diffuse noise based on decomposition of the observed spatial covariance matrix into signal and noise parts. In modeling noise to regularize the ill-posed decomposition problem, we exploit spatial invariance (isotropy) instead of temporal inva...

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Bibliographic Details
Published in:	Journal of Signal Processing Systems Vol. 79; no. 2; pp. 145 - 157
Main Authors:	Ito, Nobutaka, Vincent, Emmanuel, Nakatani, Tomohiro, Ono, Nobutaka, Araki, Shoko, Sagayama, Shigeki
Format:	Journal Article
Language:	English
Published:	Boston Springer Science and Business Media LLC 01.05.2015 Springer US
Subjects:	[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing Circuits and Systems Computer Imaging Diffuse noise Electrical Engineering Engineering Image Processing and Computer Vision Least squares estimation Maximum likelihood estimation Noise suppression Pattern Recognition Pattern Recognition and Graphics Signal,Image and Speech Processing Spatial covariance matrix Vision Diffuse noise Maximum likelihood estimation Spatial covariance matrix Least squares estimation Noise suppression
ISSN:	1939-8018, 1939-8115
Online Access:	Get full text
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