Optimal sparse representations for blind source separation and blind deconvolution: A learning approach
Bronstein MM, Bronstein AM, Zibulevsky M, Zeevi YY. 2001. Optimal sparse representations for blind source separation and blind deconvolution: A learning approach. 2004 International Conference on Image Processing. ICIP: International Conference on Image Processing.
Download
No fulltext has been uploaded. References only!
Conference Paper
| Published
| English
Scopus indexed
Author
Bronstein, M.M.;
Bronstein, Alex M.ISTA 
;
Zibulevsky, M.;
Zeevi, Y.Y.
;
Zibulevsky, M.;
Zeevi, Y.Y.Abstract
We present a generic approach, which allows to adapt sparse blind deconvolution and blind source separation algorithms to arbitrary sources. The key idea is to bring the problem to the case in which the underlying sources are sparse by applying a sparsifying transformation on the mixtures. We present simulation results and show that such transformation can be found by training. Properties of the optimal sparsifying transformation are highlighted by an example with aerial images.
Publishing Year
Date Published
2001-10-30
Proceedings Title
2004 International Conference on Image Processing
Publisher
IEEE
Conference
ICIP: International Conference on Image Processing
Conference Location
Singapore, Singapore
Conference Date
2004-10-24 – 2004-10-27
ISBN
ISSN
IST-REx-ID
Cite this
Bronstein MM, Bronstein AM, Zibulevsky M, Zeevi YY. Optimal sparse representations for blind source separation and blind deconvolution: A learning approach. In: 2004 International Conference on Image Processing. IEEE; 2001. doi:10.1109/icip.2004.1421428
Bronstein, M. M., Bronstein, A. M., Zibulevsky, M., & Zeevi, Y. Y. (2001). Optimal sparse representations for blind source separation and blind deconvolution: A learning approach. In 2004 International Conference on Image Processing. Singapore, Singapore: IEEE. https://doi.org/10.1109/icip.2004.1421428
Bronstein, M.M., Alex M. Bronstein, M. Zibulevsky, and Y.Y. Zeevi. “Optimal Sparse Representations for Blind Source Separation and Blind Deconvolution: A Learning Approach.” In 2004 International Conference on Image Processing. IEEE, 2001. https://doi.org/10.1109/icip.2004.1421428.
M. M. Bronstein, A. M. Bronstein, M. Zibulevsky, and Y. Y. Zeevi, “Optimal sparse representations for blind source separation and blind deconvolution: A learning approach,” in 2004 International Conference on Image Processing, Singapore, Singapore, 2001.
Bronstein MM, Bronstein AM, Zibulevsky M, Zeevi YY. 2001. Optimal sparse representations for blind source separation and blind deconvolution: A learning approach. 2004 International Conference on Image Processing. ICIP: International Conference on Image Processing.
Bronstein, M. M., et al. “Optimal Sparse Representations for Blind Source Separation and Blind Deconvolution: A Learning Approach.” 2004 International Conference on Image Processing, IEEE, 2001, doi:10.1109/icip.2004.1421428.
Google Scholar
ISBN Search