On global and local convergence of half-quadratic algorithms.
other · Level V
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Abstract
This paper provides original results on the global and local convergence properties of half-quadratic (HQ) algorithms resulting from the Geman and Yang (GY) and Geman and Reynolds (GR) primal-dual constructions. First, we show that the convergence domain of the GY algorithm can be extended with the benefit of an improved convergence rate. Second, we provide a precise comparison of the convergence rates for both algorithms. This analysis shows that the GR form does not benefit from a better convergence rate in general. Moreover, the GY iterates often take advantage of a low cost implementation. In this case, the GY form is usually faster than the GR form from the CPU time viewpoint.
Medical subject headings
- Algorithms
- Artificial Intelligence
- Image Enhancement
- Image Interpretation, Computer-Assisted
- Imaging, Three-Dimensional
- Information Storage and Retrieval