Dr. Daniel Wegner Profile

Dr. Daniel Wegner

Research fellow at Fraunhofer-IOSB

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Author

Publications (18)

Proceedings Article | 23 October 2023 Paper

Impact of motion blur on recognition rates of CNN-based TOD classifier models

Daniel Wegner, Stefan Keßler

Proceedings Volume 12737, 127370L (2023) https://doi.org/10.1117/12.2684366

KEYWORDS: Motion models, Motion blur, Signal to noise ratio, Zoom lenses, Cameras, Imaging systems, Target recognition, Sensors, Performance modeling

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SPIE Journal Paper | 20 April 2023 Open Access

Comparison of algorithms for contrast enhancement based on triangle orientation discrimination assessments by convolutional neural networks

Daniel Wegner, Stefan Keßler

OE, Vol. 62, Issue 04, 048103, (April 2023) https://doi.org/10.1117/12.10.1117/1.OE.62.4.048103

KEYWORDS: Signal to noise ratio, Education and training, Data modeling, Detection and tracking algorithms, Image enhancement, Databases, RGB color model, Optical engineering, Forward looking infrared, Performance modeling

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Proceedings Article | 2 November 2022 Presentation + Paper

Comparison of algorithms for contrast enhancement based on TOD assessments by convolutional neural networks

Daniel Wegner, Stefan Keßler

Proceedings Volume 12271, 122710H (2022) https://doi.org/10.1117/12.2638539

KEYWORDS: Signal to noise ratio, Data modeling, Detection and tracking algorithms, Sensors, Image processing, Cameras, RGB color model, Visual process modeling, Imaging systems, Image contrast enhancement

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Proceedings Article | 2 November 2022 Presentation + Paper

Influence of turbulence on active compressive sensing imaging

Gabriela Paunescu, Peter Lutzmann, Daniel Wegner

Proceedings Volume 12272, 122720E (2022) https://doi.org/10.1117/12.2637774

KEYWORDS: Turbulence, Sensors, Modulation, Compressed sensing, Imaging systems, Staring arrays, Digital micromirror devices, Continuous wave operation, Optical components

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Proceedings Article | 2 November 2022 Presentation + Paper

Simulation of caustics caused by high-energy laser reflection from melting metallic targets adapted by a machine learning approach

Daniel Wegner, Adrian Azarian, Michael Henrichsen, Gregor Franz, Stefan Keßler

Proceedings Volume 12273, 1227305 (2022) https://doi.org/10.1117/12.2636218

KEYWORDS: Reflection, Metals, Nominal ocular hazard distance, Laser safety, Neural networks, Beam propagation method, Laser beam propagation, Optical simulations, Image analysis, Wave propagation

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Proceedings Article | 13 September 2021 Presentation + Paper

Towards atmospheric turbulence simulation using a conditional variational autoencoder

Stefan Kessler, José Pérez, Daniel Wegner, Gregor Franz

Proceedings Volume 11866, 118660G (2021) https://doi.org/10.1117/12.2600271

KEYWORDS: Turbulence, Point spread functions, Data modeling, Modulation transfer functions, Imaging systems, Computer simulations, Computer programming, Atmospheric turbulence, Statistical analysis, Artificial neural networks, Atmospheric modeling, Machine learning

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Proceedings Article | 12 September 2021 Presentation + Paper

Turbulence simulation for anisoplanatic imaging based on phase screens with experimental validation of differential tilt variances

Daniel Wegner

Proceedings Volume 11866, 118660H (2021) https://doi.org/10.1117/12.2600330

KEYWORDS: Turbulence, Point spread functions, Modulation transfer functions, Light emitting diodes, Data modeling, Cameras, Wave propagation, Atmospheric modeling

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Air turbulence can be a major impairment source for long-range imaging applications. There is great interest in the assessment of turbulence mitigation techniques based on machine learning models. In general such models require lots of image data for robust training and validation. Experimental acquisition of image data in field trials is time-consuming and environmental conditions such as daytime and weather cannot be specifically controlled. Several methods for turbulence simulation have been proposed in recent years. Many of these are based on phase screens or models turbulent point spread functions (PSFs). Often simple turbulence models such as the Kolmogorov or Von Karman spectrum are used. Therefore these methods cannot provide insight in the influence and relevance of other turbulence parameters such as inner scale and (non-)Kolmogorov power slope. In this work a data fitting procedure for the determination of turbulence model parameters based on experimental data is shown. Hereby the Generalized modified Von Karman spectrum (GMVKS) is used. Differential tilt variances (DTV) are calculated from centroid displacements in video sequences of a recorded LED grid. Then the experimental data is fitted to theoretical expressions of DTV by numerical integration over the turbulence model. Image data was acquired in field trials on several days at the same location. Then a beam propagation method using Markov GMVKS phase screens with determined model parameters is used to generate a grid of PSF images which represent degradation for different viewing angles. For validation, DTVs based on centroid displacements of the simulated PSFs are calculated and compared with the corresponding measured data of LED centroid displacements and theoretical data. Cumulative distribution functions of the model parameters for all recording dates are provided to show the diversity of turbulence conditions. These can be used as prior knowledge for future turbulence simulations to include various model parameters and hence different conditions of image degradation. Finally the extensibility of the data fitting approach to other turbulence spectra, e.g. anisotropic spectra, is discussed.

SPIE Journal Paper | 6 January 2021 Open Access

Detecting vibration features from remote objects based on high-speed imagery

Gabriela Paunescu, Peter Lutzmann, Daniel Wegner, Benjamin Göhler

OE, Vol. 60, Issue 01, 013102, (January 2021) https://doi.org/10.1117/12.10.1117/1.OE.60.1.013102

KEYWORDS: Cameras, Vibrometry, High speed imaging, Mid-IR, Turbulence, Sensors, Optical engineering, Short wave infrared radiation, Doppler effect, Signal detection

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Proceedings Article | 14 May 2020 Presentation + Paper

Imager assessment by classification of geometric primitives

D. Wegner, E. Repasi

Proceedings Volume 11406, 1140608 (2020) https://doi.org/10.1117/12.2558572

KEYWORDS: Cameras, Data modeling, Image classification, Imaging systems, Image quality, Infrared imaging, Projection systems, Motion models, Mid-IR

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Proceedings Article | 10 October 2019 Paper

SWIR imaging through strong atmospheric turbulence: comparing a focal-plane-array camera and a compressive sensor

Gabriela Paunescu, Daniel Wegner, Peter Lutzmann

Proceedings Volume 11160, 111600B (2019) https://doi.org/10.1117/12.2533093

KEYWORDS: Atmospheric turbulence, Turbulence, Compressed sensing, Sensors, Staring arrays, Image acquisition, Image resolution, Short wave infrared radiation, Computational imaging, Image restoration

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Proceedings Article | 9 October 2019 Paper

ECOMOS software structure and key features

R. J. M. ten Hove, E. Repasi, P. Bijl, S. Keßler, L. Labarre, D. Wegner, W. Wittenstein, H. Buersing

Proceedings Volume 11159, 111590K (2019) https://doi.org/10.1117/12.2536425

KEYWORDS: Performance modeling, Data modeling, Instrument modeling, Visual process modeling, Computer simulations, Imaging systems, Infrared imaging, Thermography, Thermal modeling, Atmospheric modeling

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Proceedings Article | 9 October 2018 Presentation + Paper

Compressive sensing for active imaging in SWIR spectral range

Gabriela Paunescu, Peter Lutzmann, Daniel Wegner

Proceedings Volume 10796, 107960A (2018) https://doi.org/10.1117/12.2325377

KEYWORDS: Sensors, Short wave infrared radiation, Pulsed laser operation, Modulation, Compressed sensing, Digital micromirror devices, Imaging systems, Signal detection

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Proceedings Article | 9 October 2018 Paper

Testbed for thermal imager characterization using an infrared scene projector

Michael Koerber, Bastian Schwarz, Daniel Wegner, Stefan Kessler, Bernd Eberle, Gunnar Ritt

Proceedings Volume 10795, 107950K (2018) https://doi.org/10.1117/12.2325106

KEYWORDS: Projection systems, Thermography, Cameras, Infrared imaging, Calibration, Infrared radiation, Nonuniformity corrections, Image enhancement

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Proceedings Article | 26 April 2018 Presentation + Paper

Optronic System Imaging Simulator (OSIS): imager simulation tool of the ECOMOS project

D. Wegner, E. Repasi

Proceedings Volume 10625, 106250M (2018) https://doi.org/10.1117/12.2304386

KEYWORDS: Sensors, Imaging systems, Image sensors, Cameras, Digital signal processing, Image processing, Optical transfer functions, Electro optical modeling, Optoelectronics, Computer simulations

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Proceedings Article | 22 May 2017 Presentation + Paper

Workbench for the computer simulation of underwater gated viewing systems

K. Braesicke, D. Wegner, E. Repasi

Proceedings Volume 10186, 101860B (2017) https://doi.org/10.1117/12.2262415

KEYWORDS: Image sensors, Scattering, Modulation transfer functions, Pulsed laser operation, Reflectivity, Cameras, Computer simulations, Imaging systems, Computing systems, Sensors, Water, Systems modeling, Image enhancement, Device simulation, Optical simulations

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Proceedings Article | 3 May 2017 Paper

Noise-insensitive no-reference image blur estimation by convolutional neural networks

D. Wegner, M. Koerber, E. Repasi

Proceedings Volume 10178, 101780G (2017) https://doi.org/10.1117/12.2268080

KEYWORDS: Neural networks, Digital image processing, Image processing, Data modeling, Motion estimation, Image analysis, Image quality, Digital cameras, Thermography, Image sensors, Databases, Distortion, RGB color model, Convolutional neural networks, Motion models, Image filtering

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Proceedings Article | 3 May 2016 Paper

Image based performance analysis of thermal imagers

D. Wegner, E. Repasi

Proceedings Volume 9820, 982016 (2016) https://doi.org/10.1117/12.2223629

KEYWORDS: Cameras, Sensors, Image processing, Image enhancement, Image sensors, Thermography, Projection systems, Image quality, Modulation transfer functions, Detection and tracking algorithms

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Proceedings Article | 16 October 2015 Paper

Comparison of high speed imaging technique to laser vibrometry for detection of vibration information from objects

Gabriela Paunescu, Peter Lutzmann, Benjamin Göhler, Daniel Wegner

Proceedings Volume 9649, 96490D (2015) https://doi.org/10.1117/12.2194753

KEYWORDS: High speed imaging, Vibrometry, Doppler effect, Cameras, High speed cameras, Video, Sensors, Signal detection, Detection and tracking algorithms, Information visualization

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Showing 5 of 18 publications

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