Single-shot structured-light-field three-dimensional imaging

2020 ◽  
Vol 45 (12) ◽  
pp. 3256
Author(s):  
Zewei Cai ◽  
Giancarlo Pedrini ◽  
Wolfgang Osten ◽  
Xiaoli Liu ◽  
Xiang Peng
Keyword(s):  
Light Field ◽  
Structured Light ◽  
Three Dimensional ◽  
Single Shot ◽  
Three Dimensional Imaging

Single-shot three-dimensional imaging with a scattering layer [Invited]

2021 ◽  
Vol 60 (10) ◽  
pp. B32
Author(s):  
Guowei Li ◽  
Wanqing Yang ◽  
Yaoming Bian ◽  
Haichao Wang ◽  
Guohai Situ
Keyword(s):  
Three Dimensional ◽  
Single Shot ◽  
Scattering Layer ◽  
Three Dimensional Imaging

scholarly journals Robust Depth Estimation for Light Field Microscopy

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 500 ◽  
Author(s):  
Luca Palmieri ◽  
Gabriele Scrofani ◽  
Nicolò Incardona ◽  
Genaro Saavedra ◽  
Manuel Martínez-Corral ◽  
...  
Keyword(s):  
Light Field ◽  
Three Dimensional ◽  
Depth Map ◽  
Depth Estimation ◽  
Fourier Integral ◽  
Single Shot ◽  
Natural Scene ◽  
Multi Scale ◽  
Depth Maps ◽  
New Applications

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.

scholarly journals Single-shot three-dimensional imaging of dilute atomic clouds

2014 ◽  
Vol 39 (18) ◽  
pp. 5317 ◽  
Author(s):  
Kaspar Sakmann ◽  
Mark Kasevich
Keyword(s):  
Three Dimensional ◽  
Single Shot ◽  
Three Dimensional Imaging

scholarly journals A compact structured light based otoscope for three dimensional imaging of the tympanic membrane

2015 ◽  
Author(s):  
Anshuman J. Das ◽  
Julio C. Estrada ◽  
Zhifei Ge ◽  
Sara Dolcetti ◽  
Deborah Chen ◽  
...  
Keyword(s):  
Tympanic Membrane ◽  
Structured Light ◽  
Three Dimensional ◽  
Three Dimensional Imaging

scholarly journals Virtual phase conjugation based optical tomography for single-shot three-dimensional imaging

2018 ◽  
Vol 26 (4) ◽  
pp. 3779 ◽  
Author(s):  
Yuta Goto ◽  
Atsushi Okamoto ◽  
Atsushi Shibukawa ◽  
Kazuhisa Ogawa ◽  
Akihisa Tomita
Keyword(s):  
Phase Conjugation ◽  
Optical Tomography ◽  
Three Dimensional ◽  
Single Shot ◽  
Three Dimensional Imaging

scholarly journals Efficient and Accurate Disparity Estimation from MLA-Based Plenoptic Cameras

2021 ◽  
Author(s):  
Luca Palmieri
Keyword(s):  
Light Field ◽  
Three Dimensional ◽  
Microlens Array ◽  
Depth Estimation ◽  
Calibration Method ◽  
Optimization Method ◽  
Disparity Estimation ◽  
Future Research ◽  
Single Shot ◽  
Estimation Algorithms

Microlens-array based plenoptic cameras capture the light field in a single shot, enabling new potential applications but also introducing additional challenges. A plenoptic image consists of thousand of microlens images. Estimating the disparity for each microlens allows to render conventional images, changing the perspective and the focal settings, and to reconstruct the three-dimensional geometry of the scene. The work includes a blur-aware calibration method to model plenoptic cameras, an optimization method to accurately select the best microlenses combination for disparity estimation, an overview of the different types of plenoptic cameras, an analysis of the disparity estimation algorithms, and a robust depth estimation approach for light field microscopy. The research led to the creation of a full framework for plenoptic cameras, which contains the implementation of the algorithms discussed in the work and datasets of both real and synthetic images for comparison, benchmarking and future research.

Using wrapped phases for light-field three-dimensional imaging

2019 ◽  
Author(s):  
Jiawei Chen ◽  
Zewei Cai ◽  
Xiaoli Liu ◽  
Giancarlo Pedrini ◽  
Wolfgang Osten ◽  
...  
Keyword(s):  
Light Field ◽  
Three Dimensional ◽  
Three Dimensional Imaging

Wavefront Reconstruction for Structured Light based Microscopic Three-dimensional Imaging

2020 ◽  
Author(s):  
Taichu Shi ◽  
Yang Qi ◽  
Haoshuo Chen ◽  
Nicolas K. Fontaine ◽  
Roland Ryf ◽  
...  
Keyword(s):  
Structured Light ◽  
Three Dimensional ◽  
Three Dimensional Imaging ◽  
Wavefront Reconstruction
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