Paper Info
Title
Sparse denoising of audio by greedy time-frequency shrinkage
Abstract
Matching Pursuit (MP) is a greedy algorithm that iteratively builds a sparse signal representation. This work presents an analysis of MP in the context of audio denoising. By interpreting the algorithm as a simple shrinkage approach, we identify the factors critical to its success, and propose several approaches to improve its performance and robustness. We present experimental results on a wide range of audio signals, and show that the method is able to yield results thats are competitive with other audio denosing approaches. Notably, the proposed approach retains a small percentage of the transform signal coefficients in building a denoised representation, i.e., it produces very sparse denoised results.
Year
DOI
Venue
2014
10.1109/ICASSP.2014.6854130
Acoustics, Speech and Signal Processing
Keywords
Field
DocType
audio signal processing,greedy algorithms,iterative methods,signal denoising,time-frequency analysis,audio signal denoising,greedy time-frequency shrinkage,matching pursuit algorithm,sparse denoising,Audio Denoising,Greedy Search,Matching Pursuit,Simple Shrinkage,Sparse Representation
Matching pursuit,Audio signal,Pattern recognition,Computer science,Sparse approximation,Signal-to-noise ratio,Greedy algorithm,Robustness (computer science),Artificial intelligence,Time–frequency analysis,Audio signal processing
Conference
ISSN
Citations 
PageRank 
1520-6149
2
0.39
References 
Authors
6
2
Name
Order
Citations
PageRank
Gautam Bhattacharya1626.98
Philippe Depalle296.60