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Convolutional group-sparse coding and source localization - Poster

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Citation Author(s):
Pol del Aguila Pla, Joakim Jaldén
Submitted by:
Pol del Aguila Pla
Last updated:
5 May 2022 - 9:10am
Document Type:
Poster
Document Year:
2018
Event:
Presenters Name:
Pol del Aguila Pla
Paper Code:
2142

Abstract 

Abstract: 

In this paper, we present a new interpretation of non-negatively constrained convolutional coding problems as blind deconvolution problems with spatially variant point spread function. In this light, we propose an optimization framework that generalizes our previous work on non-negative group sparsity for convolutional models. We then link these concepts to source localization problems that arise in scientific imaging, and provide a visual example on an image derived from data captured by the Hubble telescope.

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Dataset Files

Poster_ICASSP2018.pdf

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