Open AccessA theoretical performance model for single image depth from defocus
Author(s) -
Pauline Trouvé-Peloux,
Frédéric Champagnat,
Guy Le Besnerais,
Jérôme Idier
Publication year - 2014
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
DOI - 10.1364/xx.99.099999
Subject(s) - image (mathematics) , artificial intelligence , computer vision , computer science , geology
International audienceIn this paper we present a performance model for depth estimation using Single Image Depth From Defocus (SIDFD). Our model is based on an original expression of the Cramér Rao Bound (CRB) in this context. We show that this model is consistent with the expected behavior of SIDFD. We then study the influence on the performance of the optical parameters of a conventional camera such as the focal length, the aperture and the position of the in-focus plane. We derive an approximate analytical expression of the CRB away from the in-focus plane and we propose an interpretation of the SIDFD performance in this domain. Finally, we illustrate the predictive capacity of our performance model on experimental data comparing several settings of a consumer camera