Joint photometric and geometric image registration in the total least square sense
| Autor: | Bart Goossens, Aleksandra Piurica, Wilfried Philips, Hiep Luong |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
business.industry
Image registration Sense (electronics) Artificial Intelligence Image alignment Signal Processing Metric (mathematics) Ordinary least squares Computer vision Computer Vision and Pattern Recognition Artificial intelligence Noise (video) business Joint (audio engineering) Algorithm Software Mathematics |
| Zdroj: | Pattern Recognition Letters. 32:2061-2067 |
| ISSN: | 0167-8655 |
| DOI: | 10.1016/j.patrec.2011.08.004 |
| Popis: | This paper presents a novel robust image alignment technique that performs joint geometric and photometric registration in the total least square (TLS) sense. Therefore, we employ the total least square metric instead of the ordinary least square (OLS) metric, which is commonly used in the literature. While the OLS model is sufficient to tackle geometric registration problems, it gives no mutually consistent estimates when dealing with photometric deformations. By introducing a new TLS model, we obtain mutually consistent parameters. Experimental results show that our method is indeed more consistent and accurate in presence of noise compared to existing joint registration algorithms. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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