DSB Seminar - Acoustic imaging of sparse sources with Orthogonal Matching Pursuit and clustering of basis vectors. Presenter: Trond Bergh

Title: Acoustic imaging of sparse sources with Orthogonal Matching Pursuit and clustering of basis vectors.

Presenter: Trond Bergh

Affiliation: DSB-group (Digital signal processing and image analysis) / Squarehead

Abstract: This talk is to be presented at the Int Conf Acoust Speech Sign Proc New Orleans, March 2017. 

We have devised a greedy method for finding solutions to the sparse Deconvolution Approach for the Mapping of Acoustic Sources inverse problem using a variant of Orthogonal Matching Pursuit. The algorithm has two stages, wherein the first stage consists of selecting a subset of the basis vectors iteratively via a regularized inverse of the point spread function, and the second stage consists of constructing point source solutions using this basis subset and its coefficients via hierarchical agglomerative clustering. We have evaluated the algorithm on both synthetic and real data, and show that the overall accuracy in terms of direction of arrival and reconstructed source power is better than four other state of the art methods.

Published Feb. 9, 2017 2:06 PM - Last modified Feb. 9, 2017 2:06 PM