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Convolutional group-sparse coding and source localization - Poster
- Citation Author(s):
- Submitted by:
- Pol del Aguila Pla
- Last updated:
- 5 May 2022 - 9:10am
- Document Type:
- Poster
- Document Year:
- 2018
- Event:
- Presenters:
- Pol del Aguila Pla
- Paper Code:
- 2142
- Categories:
- Keywords:
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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.