Title
Robust Depth Estimation for Light Field Microscopy.
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.
Year
DOI
Venue
2019
10.3390/s19030500
SENSORS
Keywords
Field
DocType
depth estimation,light field,microscope,stereo matching,defocus
Computer vision,Filter (signal processing),Light field,Electronic engineering,Exploit,Fourier transform,Microscope,Cost aggregation,Artificial intelligence,Microscopy,Depth map,Engineering
Journal
Volume
Issue
ISSN
19
3.0
1424-8220
Citations 
PageRank 
References 
0
0.34
12
Authors
6
Name
Order
Citations
PageRank
Luca Palmieri100.68
Gabriele Scrofani201.01
Nicolò Incardona300.34
Genaro Saavedra4156.70
Manuel Martinez-Corral544.58
Reinhard Koch62038170.17