Abstract
The Richardson-Lucy algorithm is one of the most important algorithms in the image deconvolution area. However, one of its drawbacks is slow convergence. A very significant acceleration is obtained by the technique proposed by Biggs and Andrews (BA), which is implemented in the deconvlucy function of the Image Processing MATLAB toolbox. The BA method was developed heuristically with no proof of convergence. In this paper, we introduce the Heavy-Ball (H-B) method for Poisson data optimization and extend it to a scaled H-B method, which includes the BA method as a special case. The method has proof of the convergence rate of O(k-2), where k is the number of iterations. We demonstrate the superior convergence performance of the scaled H-B method on both synthetic and real 3D images.
| Original language | English |
|---|---|
| Title of host publication | Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| Pages | 1743-1746 |
| Number of pages | 4 |
| ISBN (Print) | 978-1-4577-1857-1 |
| DOIs | |
| Publication status | Published - May 2012 |
| Event | 9th IEEE International Symposium on Biomedical Imaging - Barcelona, Spain Duration: 02 May 2012 → 05 May 2012 |
Conference
| Conference | 9th IEEE International Symposium on Biomedical Imaging |
|---|---|
| Country | Spain |
| City | Barcelona |
| Period | 02/05/2012 → 05/05/2012 |
ASJC Scopus subject areas
- Biomedical Engineering
- Radiology Nuclear Medicine and imaging
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Cite this
Wang, H., & Miller, P. (2012). Scaled Heavy-Ball Acceleration of the Richardson-Lucy Algorithm. In Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on (pp. 1743-1746). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ISBI.2012.6235917