Optical measurement methods are becoming increasingly important for high-precision production of components and quality assurance. The increasing demand can be met by modern imaging systems with advanced optics, such as light field cameras. This work explores their use in the deflectometric measurement of specular surfaces. It presents improvements in phase unwrapping and calibration techniques, enabling high surface reconstruction accuracies using only a single monocular light field camera.

In dieser Arbeit werden spektral kodierte multispektrale Lichtfelder untersucht, wie sie von einer Lichtfeldkamera mit einem spektral kodierten Mikrolinsenarray aufgenommen werden. Für die Rekonstruktion der kodierten Lichtfelder werden zwei Methoden entwickelt, eine basierend auf den Prinzipien des Compressed Sensing sowie eine Deep Learning Methode. Anhand neuartiger synthetischer und realer Datensätze werden die vorgeschlagenen Rekonstruktionsansätze im Detail evaluiert. -In this work, spatio-spectrally coded multispectral light fields, as taken by a light field camera with a spectrally coded microlens array, are investigated. For the reconstruction of the coded light fields, two methods, one based on the principles of compressed sensing and one deep learning approach, are developed. Using novel synthetic as well as a real-world datasets, the proposed reconstruction approaches are evaluated in detail.

The increasing use of automated laser welding processes causes high demands on process monitoring. This work demonstrates methods that use a camera mounted on the focussing optics to perform pre-, in-, and post-process monitoring of welding processes. The implementation uses machine learning methods. All algorithms consider the integration into industrial processes. These challenges include a small database, limited industrial manufacturing inference hardware, and user acceptance.

Deep learning is widely applied to sparse 3D data to perform challenging tasks, e.g., 3D object detection and semantic segmentation. However, the high performance of deep learning comes with high costs, including computational costs and the effort to capture and label data. This work investigates and improves the efficiency of deep learning for sparse 3D data to overcome the obstacles to the further development of this technology.

Advancement of Optical Methods & Digital Image Correlation in Experimental Mechanics, Volume 3 of the Proceedings of the 2019 SEM Annual Conference & Exposition on Experimental and Applied Mechanics, the third volume of six from the Conference, brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on a wide range of optical methods ranging from traditional photoelasticity and interferometry to more recent DIC and DVC techniques, and includes papers in the following general technical research areas: DIC Methods & Its Applications Photoelsticity and Interferometry ApplicationsMicro-Optics and Microscopic SystemsMultiscale and New Developments in Optical MethodsDIC and its Applications for Inverse Problems

This pioneering text/reference presents a detailed focus on the use of machine vision techniques in industrial inspection applications. An internationally renowned selection of experts provide insights on a range of inspection tasks, drawn from their cutting-edge work in academia and industry, covering practical issues of vision system integration for real-world applications. Topics and features: presents a comprehensive review of state-of-the-art hardware and software tools for machine vision, and the evolution of algorithms for industrial inspection; includes in-depth descriptions of advanced inspection methodologies and machine vision technologies for specific needs; discusses the latest developments and future trends in imaging and vision techniques for industrial inspection tasks; provides a focus on imaging and vision system integration, implementation, and optimization; describes the pitfalls and barriers to developing successful inspection systems for smooth and efficient manufacturing process.

The book offers a thorough introduction to machine vision. It is organized in two parts. The first part covers the image acquisition, which is the crucial component of most automated visual inspection systems. All important methods are described in great detail and are presented with a reasoned structure. The second part deals with the modeling and processing of image signals and pays particular regard to methods, which are relevant for automated visual inspection.

Laser-driven proton beams are still in their infancy but already have some outstanding attributes compared to those produced in conventional accelerators. One such attribute is the typically low beam emittance. This allows excellent resolution in imaging applications like proton radiography. This thesis describes a novel imaging technique - the proton streak camera - that the author developed and first used to measure both the spatial and temporal evolution of ultra-strong electrical fields in laser-driven plasmas. Such investigations are of paramount importance for the understanding of laser-plasma interactions and, thus, for optimization of laser-driven particle acceleration. In particular, the present work investigated micrometer-sized spherical targets after laser irradiation. The confined geometry of plasmas and fields was found to influence the kinetic energy and spatial distribution of accelerated ions. This could be shown both in experimental radiography images and and in numerical simulations, one of which was selected for the cover page of Physical Review Letters.

This book presents recent and important developments in the field of Photonics and Optoelectronics, with a particular focus on Laser Technology, Optical Communications, Optoelectronic Devices and Image Processing. At present, Photonics and Optoelectronics Technologies are pivotal to the future of laser, displays, sensors and communication technologies, and currently being developed at an extraordinary rate. This book details the theories underlying the mechanisms involved in the relevant Photonics and Optoelectronics. Devices such as laser diodes, photodetectors, and integrated optoelectronic circuits are investigated. The reviews by leading experts are of interest to researchers and engineers as well as advanced students.

The authors' innovative research ideas in power plant control are presented in this book. This book focuses on 1) cognition and reconstruction of the temperature field; 2) intelligent setting and learning of power plants; 3) energy efficiency optimization and intelligent control for power plants, and so on, using historical power plant operation data and creative methods such as reconstruction of the combustion field, deep reinforcement learning, and networked collaborative control. It could help researchers, industrial engineers, and graduate students in the areas of signal detection, image processing, and control engineering.