Linear search applied to global motion estimation |
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Authors: | Shlomo Greenberg Daniel Kogan |
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Affiliation: | (1) Communication Systems Engineering Department, Ben-Gurion University of the Negev, P.O.B. 653, Beer-Sheva, 84105, Israel;(2) Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev, P.O.B. 653, Beer-Sheva, 84105, Israel |
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Abstract: | Gradient-based algorithms for global motion estimation are effective in many image-processing tasks. However, when analytical estimation of derivatives of objective function is not possible, linear search based algorithms such as Powell perform better than the gradient-based ones. In this paper we propose global motion estimation algorithm that exploits linear search based algorithm, particularly Powell, instead of commonly used gradient-based one. We also introduce a new approach for extracting global motion parameters called Two Step Powell-based GME. Using this approach we further improve the Powell-based GME. The proposed Powell-based GME outperforms Gauss–Newton algorithm (gradient-based) in terms of PSNR. The proposed Two Step Powell GME algorithm outperforms Powell-based GME in terms of PSNR and computational time. |
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Keywords: | Global motion estimation Optimization Gradient-based Linear search |
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