Journal: Optical Engineering

Abbreviation

Opt. Eng.

Publisher

SPIE

Journal Volumes

ISSN

0091-3286
1560-2303

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Publications 1 - 10 of 12
  • Effect of light coherence on depth of focus in head-mounted retinal projection displays
    Item type: Conference Paper
    Waldkirch, Marc von; Lukowicz, Paul; Tröster, Gerhard (2004)
    Optical Engineering
  • Denoising of continuous-wave time-of-flight depth images using confidence measures
    Item type: Journal Article
    Frank, Mario; Plaue, Matthias; Hamprecht, Fred A. (2009)
    Optical Engineering
  • Experimental methods to predict dynamic vision sensor event camera performance
    Item type: Journal Article
    McReynolds, Brian; Zenhas Graça, Rui Pedro; Delbrück, Tobias (2022)
    Optical Engineering
    Dynamic vision sensors (DVS) represent a promising new technology, offering low power consumption, sparse output, high temporal resolution, and wide dynamic range. These features make DVS attractive for new research areas including scientific and space-based applications; however, more precise understanding of how sensor input maps to output under real-world constraints is needed. Often, metrics used to characterize DVS report baseline performance by measuring observable limits but fail to characterize the physical processes at the root of those limits. To address this limitation, we describe step-by-step procedures to measure three important performance parameters: (1) temporal contrast threshold, (2) cutoff frequency, and (3) refractory period. Each procedure draws inspiration from previous work, but links measurements sequentially to infer physical phenomena at the root of measured behavior. Results are reported over a range of brightness levels and user-defined biases. The threshold measurement technique is validated with test-pixel node voltages, and a first-order low-pass approximation of photoreceptor response is shown to predict event cutoff temporal frequency to within 9% accuracy. The proposed method generates lab-measured parameters compatible with the event camera simulator v2e, allowing more accurate generation of synthetic datasets for innovative applications.
  • Ultrafast laser-induced crystallization of amorphous silicon films
    Item type: Journal Article
    Choi, Tae Y; Hwang, David J.; Grigoropoulos, Costas P. (2003)
    Optical Engineering
  • Reconstruction of combustion temperature and gas concentration distributions using line-of-sight tunable diode laser absorption spectroscopy
    Item type: Journal Article
    Zhang, Zhirong; Sun, Pengshuai; Pang, Tao; et al. (2016)
    Optical Engineering
  • Theoretical and experimental error analysis of continuous-wave time-of-flight range cameras
    Item type: Journal Article
    Frank, Mario; Plaue, Matthias; Rapp, Holger; et al. (2009)
    Optical Engineering
  • Simultaneous distance measurement at multiple wavelengths using the intermode beats from a femtosecond laser coherent supercontinuum
    Item type: Journal Article
    Salido-Monzú, David; Wieser, Andreas (2018)
    Optical Engineering
  • Tradeoffs of vertical-cavity surface emitting lasers modeling for the development of driver circuits in short distance optical links
    Item type: Journal Article
    Sialm, Gion; Erni, Daniel; Vez, Dominique; et al. (2005)
    Optical Engineering
  • Classification of material and surface roughness using polarimetric multispectral LiDAR
    Item type: Journal Article
    Han, Yu; Salido Monzú, David; Wieser, Andreas (2023)
    Optical Engineering
    Multispectral light detection and ranging (LiDAR) is an emerging active remote sensing technique that combines distance and spectroscopy measurements. The reflectance spectrum is known to enable material classification. However, the spectrum also depends on other surface parameters, particularly roughness. Herein, we propose an extension of multispectral to polarimetric multispectral LiDAR and introduce unpolarized and linearly polarized reflectance spectra as additional features for classifying materials and roughness. Using a bench-top prototype instrument, we demonstrate the feasibility and benefit of acquiring unpolarized and linearly polarized reflectance spectra. We analyze and interpret the spectra obtained with two different spectral resolutions (10 and 40 nm) from measurements on test specimens consisting of five different materials with two different levels of surface roughness. Using a linear support vector machine, we demonstrate the potential of the different features for enabling material and roughness classification. We find that the unpolarized reflectance spectrum is well suited for classifying materials, and the linearly polarized one for classifying roughness. In both cases, the performance is much better than using a standard reflectance spectrum offered by multispectral LiDAR. We identify polarimetric multispectral LiDAR as a technology that may significantly enhance surface and material probing capabilities for remote sensing applications.
  • High-precision hyperspectral laser scanning for improved radiometric correction of backscatter intensity
    Item type: Journal Article
    Ray, Pabitro; Medic, Tomislav; Salido Monzú, David; et al. (2024)
    Optical Engineering
    Radiometric information offers valuable insights into the surface and material properties of remote targets. Such information can be obtained along with the surface geometry by laser scanning. However, local variations in the surface geometry and orientation can introduce a bias in the radiometric data, related to the angle of incidence (AoI). We demonstrate a supercontinuum-based hyperspectral laser scanning approach for high-precision distance measurements, and its applicability to mitigate the AoI effect by enabling an enhanced data-driven radiometric correction of the acquired intensities. Our experiments utilize a supercontinuum (SC) spectrally broadened to 570 to 970 nm from a 780 nm frequency comb. Distance measurements are derived from the differential phase delay of the intermode beat notes, while the backscattered reflection spectrum is captured using a commercial spectrometer over the spectral range of the SC output. We obtain hyperspectral point clouds with sub-mm range noise on natural targets (gypsum board and leaves of a plant used herein) placed at a distance of 5 m. The high-precision range measurements allow for correctly estimating the surface orientation and modeling the impact of the AoI on the acquired radiometric data. The estimated model is applied to correct the acquired hyperspectral signatures, which are further exploited to compute various vegetation indices commonly used as plant health indicators. Our results illustrate enhanced information content on the direct three-dimensional mapping of such spectral data of plant leaves with a reduced AoI bias. These results highlight new opportunities for future research into remote sensing of vegetation and material probing with increased sensitivity.
Publications 1 - 10 of 12