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Robust depth estimation for light field microscopy

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Robust depth estimation for light field microscopy

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dc.contributor.author	Palmieri, Luca
dc.contributor.author	Scrofani, G.
dc.contributor.author	Incardona, Nicolò
dc.contributor.author	Saavedra Tortosa, Genaro
dc.contributor.author	Martínez Corral, Manuel
dc.contributor.author	Koch, Reinhard
dc.date.accessioned	2019-01-28T14:55:26Z
dc.date.available	2019-01-28T14:55:26Z
dc.date.issued	2019
dc.identifier.citation	Palmieri, Luca Scrofani, G. Incardona, Nicolò Saavedra Tortosa, Genaro Martínez Corral, Manuel Koch, Reinhard 2019 Robust depth estimation for light field microscopy Sensors 19 3 500
dc.identifier.uri	http://hdl.handle.net/10550/68743
dc.description.abstract	Light field technologies have seen a rise in recent years and microscopy is a field where such technology has had a deep impact. The possibility to provide spatial and angular information at the same time and in a single shot brings several advantages and allows for new applications. A common goal in these applications is the calculation of a depth map to reconstruct the three-dimensional geometry of the scene. Many approaches are applicable, but most of them cannot achieve high accuracy because of the nature of such images: biological samples are usually poor in features and do not exhibit sharp colors like natural scene. Due to such conditions, standard approaches result in noisy depth maps. In this work, a robust approach is proposed where accurate depth maps can be produced exploiting the information recorded in the light field, in particular, images produced with Fourier integral Microscope. The proposed approach can be divided into three main parts. Initially, it creates two cost volumes using different focal cues, namely correspondences and defocus. Secondly, it applies filtering methods that exploit multi-scale and super-pixels cost aggregation to reduce noise and enhance the accuracy. Finally, it merges the two cost volumes and extracts a depth map through multi-label optimization.
dc.language.iso	eng
dc.relation.ispartof	Sensors, 2019, vol. 19, num. 3, p. 500
dc.subject	Microscòpia
dc.subject	Òptica
dc.title	Robust depth estimation for light field microscopy
dc.type	journal article	es_ES
dc.date.updated	2019-01-28T14:55:27Z
dc.identifier.doi	10.3390/s19030500
dc.identifier.idgrec	129735
dc.rights.accessRights	open access	es_ES