Abstract
In this paper, we focus on image deconvolution and image reconstruction problems where a sought image is recovered from degraded observed data. The solution is defined to be the minimizer of an objective function combining a data-fidelity term and a edge-preserving, convex regularization term. Our objective is to speed up the calculation of the solution in a wide range of situations. To this end, we propose a method applying pertinent preconditioning to an adapted half-quadratic equivalent form of the objective function. The optimal solution is then found using an alternating minimization (AM) scheme. We focus specifically on Huber regularization. We exhibit the possibility get very fast calculations while preserving the edges in the solution. Preliminary numerical results are reported to illustrate the effectiveness of our method.
Original language | English |
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Title of host publication | Proceedings of 2001 International Conference on Image Processing, ICIP 2001 |
Publisher | IEEE |
Pages | 277-280 |
Number of pages | 4 |
ISBN (Print) | 0780367251 |
DOIs | |
Publication status | Published - 7 Aug 2001 |
Event | 2001 IEEE International Conference on Image Processing, ICIP 2001 - Thessaloniki, Greece Duration: 7 Oct 2001 → 10 Oct 2001 https://ieeexplore.ieee.org/xpl/conhome/7594/proceeding |
Publication series
Name | Proceedings of International Conference on Image Processing |
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Conference
Conference | 2001 IEEE International Conference on Image Processing, ICIP 2001 |
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Country/Territory | Greece |
City | Thessaloniki |
Period | 7/10/01 → 10/10/01 |
Internet address |
Scopus Subject Areas
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering