Development of a Full-Field Time-of-Flight Range Imaging System

A full-field, time-of-flight, image ranging system or 3D camera has been developed from a proof-of-principle to a working prototype stage, capable of determining the intensity and range for every pixel in a scene. The system can be adapted to the requirements of various applications, producing high precision range measurements with sub-millimetre resolution, or high speed measurements at video frame rates. Parallel data acquisition at each pixel provides high spatial resolution independent of the operating speed. The range imaging system uses a heterodyne technique to indirectly measure time of flight. Laser diodes with highly diverging beams are intensity modulated at radio frequencies and used to illuminate the scene. Reflected light is focused on to an image intensifier used as a high speed optical shutter, which is modulated at a slightly different frequency to that of the laser source. The output from the shutter is a low frequency beat signal, which is sampled by a digital video camera. Optical propagation delay is encoded into the phase of the beat signal, hence from a captured time variant intensity sequence, the beat signal phase can be measured to determine range for every pixel in the scene. A direct digital synthesiser (DDS) is designed and constructed, capable of generating up to three outputs at frequencies beyond 100 MHz with the relative frequency stability in excess of nine orders of magnitude required to control the laser and shutter modulation. Driver circuits were also designed to modulate the image intensifier photocathode at 50 Vpp, and four laser diodes with a combined power output of 320 mW, both over a frequency range of 10-100 MHz. The DDS, laser, and image intensifier response are characterised. A unique method of measuring the image intensifier optical modulation response is developed, requiring the construction of a pico-second pulsed laser source. This characterisation revealed deficiencies in the measured responses, which were mitigated through hardware modifications where possible. The effects of remaining imperfections, such as modulation waveform harmonics and image intensifier irising, can be calibrated and removed from the range measurements during software processing using the characterisation data. Finally, a digital method of generating the high frequency modulation signals using a FPGA to replace the analogue DDS is developed, providing a highly integrated solution, reducing the complexity, and enhancing flexibility. In addition, a novel modulation coding technique is developed to remove the undesirable influence of waveform harmonics from the range measurement without extending the acquisition time. When combined with a proposed modification to the laser illumination source, the digital system can enhance range measurement precision and linearity. From this work, a flexible full-field image ranging system is successfully realised. The system is demonstrated operating in a high precision mode with sub-millimetre depth resolution, and also in a high speed mode operating at video update rates (25 fps), in both cases providing high (512 512) spatial resolution over distances of several metres

Optical Communication

Optical communication is very much useful in telecommunication systems, data processing and networking. It consists of a transmitter that encodes a message into an optical signal, a channel that carries the signal to its desired destination, and a receiver that reproduces the message from the received optical signal. It presents up to date results on communication systems, along with the explanations of their relevance, from leading researchers in this field. The chapters cover general concepts of optical communication, components, systems, networks, signal processing and MIMO systems. In recent years, optical components and other enhanced signal processing functions are also considered in depth for optical communications systems. The researcher has also concentrated on optical devices, networking, signal processing, and MIMO systems and other enhanced functions for optical communication. This book is targeted at research, development and design engineers from the teams in manufacturing industry, academia and telecommunication industries

Variational image fusion

The main goal of this work is the fusion of multiple images to a single composite that offers more information than the individual input images. We approach those fusion tasks within a variational framework. First, we present iterative schemes that are well-suited for such variational problems and related tasks. They lead to efficient algorithms that are simple to implement and well-parallelisable. Next, we design a general fusion technique that aims for an image with optimal local contrast. This is the key for a versatile method that performs well in many application areas such as multispectral imaging, decolourisation, and exposure fusion. To handle motion within an exposure set, we present the following two-step approach: First, we introduce the complete rank transform to design an optic flow approach that is robust against severe illumination changes. Second, we eliminate remaining misalignments by means of brightness transfer functions that relate the brightness values between frames. Additional knowledge about the exposure set enables us to propose the first fully coupled method that jointly computes an aligned high dynamic range image and dense displacement fields. Finally, we present a technique that infers depth information from differently focused images. In this context, we additionally introduce a novel second order regulariser that adapts to the image structure in an anisotropic way.Das Hauptziel dieser Arbeit ist die Fusion mehrerer Bilder zu einem Einzelbild, das mehr Informationen bietet als die einzelnen Eingangsbilder. Wir verwirklichen diese Fusionsaufgaben in einem variationellen Rahmen. Zunächst präsentieren wir iterative Schemata, die sich gut für solche variationellen Probleme und verwandte Aufgaben eignen. Danach entwerfen wir eine Fusionstechnik, die ein Bild mit optimalem lokalen Kontrast anstrebt. Dies ist der Schlüssel für eine vielseitige Methode, die gute Ergebnisse für zahlreiche Anwendungsbereiche wie Multispektralaufnahmen, Bildentfärbung oder Belichtungsreihenfusion liefert. Um Bewegungen in einer Belichtungsreihe zu handhaben, präsentieren wir folgenden Zweischrittansatz: Zuerst stellen wir die komplette Rangtransformation vor, um eine optische Flussmethode zu entwerfen, die robust gegenüber starken Beleuchtungsänderungen ist. Dann eliminieren wir verbleibende Registrierungsfehler mit der Helligkeitstransferfunktion, welche die Helligkeitswerte zwischen Bildern in Beziehung setzt. Zusätzliches Wissen über die Belichtungsreihe ermöglicht uns, die erste vollständig gekoppelte Methode vorzustellen, die gemeinsam ein registriertes Hochkontrastbild sowie dichte Bewegungsfelder berechnet. Final präsentieren wir eine Technik, die von unterschiedlich fokussierten Bildern Tiefeninformation ableitet. In diesem Kontext stellen wir zusätzlich einen neuen Regularisierer zweiter Ordnung vor, der sich der Bildstruktur anisotrop anpasst

Variational image fusion

The main goal of this work is the fusion of multiple images to a single composite that offers more information than the individual input images. We approach those fusion tasks within a variational framework. First, we present iterative schemes that are well-suited for such variational problems and related tasks. They lead to efficient algorithms that are simple to implement and well-parallelisable. Next, we design a general fusion technique that aims for an image with optimal local contrast. This is the key for a versatile method that performs well in many application areas such as multispectral imaging, decolourisation, and exposure fusion. To handle motion within an exposure set, we present the following two-step approach: First, we introduce the complete rank transform to design an optic flow approach that is robust against severe illumination changes. Second, we eliminate remaining misalignments by means of brightness transfer functions that relate the brightness values between frames. Additional knowledge about the exposure set enables us to propose the first fully coupled method that jointly computes an aligned high dynamic range image and dense displacement fields. Finally, we present a technique that infers depth information from differently focused images. In this context, we additionally introduce a novel second order regulariser that adapts to the image structure in an anisotropic way.Das Hauptziel dieser Arbeit ist die Fusion mehrerer Bilder zu einem Einzelbild, das mehr Informationen bietet als die einzelnen Eingangsbilder. Wir verwirklichen diese Fusionsaufgaben in einem variationellen Rahmen. Zunächst präsentieren wir iterative Schemata, die sich gut für solche variationellen Probleme und verwandte Aufgaben eignen. Danach entwerfen wir eine Fusionstechnik, die ein Bild mit optimalem lokalen Kontrast anstrebt. Dies ist der Schlüssel für eine vielseitige Methode, die gute Ergebnisse für zahlreiche Anwendungsbereiche wie Multispektralaufnahmen, Bildentfärbung oder Belichtungsreihenfusion liefert. Um Bewegungen in einer Belichtungsreihe zu handhaben, präsentieren wir folgenden Zweischrittansatz: Zuerst stellen wir die komplette Rangtransformation vor, um eine optische Flussmethode zu entwerfen, die robust gegenüber starken Beleuchtungsänderungen ist. Dann eliminieren wir verbleibende Registrierungsfehler mit der Helligkeitstransferfunktion, welche die Helligkeitswerte zwischen Bildern in Beziehung setzt. Zusätzliches Wissen über die Belichtungsreihe ermöglicht uns, die erste vollständig gekoppelte Methode vorzustellen, die gemeinsam ein registriertes Hochkontrastbild sowie dichte Bewegungsfelder berechnet. Final präsentieren wir eine Technik, die von unterschiedlich fokussierten Bildern Tiefeninformation ableitet. In diesem Kontext stellen wir zusätzlich einen neuen Regularisierer zweiter Ordnung vor, der sich der Bildstruktur anisotrop anpasst

Particle Physics Reference Library

This third open access volume of the handbook series deals with accelerator physics, design, technology and operations, as well as with beam optics, dynamics and diagnostics. A joint CERN-Springer initiative, the “Particle Physics Reference Library” provides revised and updated contributions based on previously published material in the well-known Landolt-Boernstein series on particle physics, accelerators and detectors (volumes 21A,B1,B2,C), which took stock of the field approximately one decade ago. Central to this new initiative is publication under full open acces

Laser-induced forward transfer (LIFT) of water soluble polyvinyl alcohol (PVA) polymers for use as support material for 3D-printed structures

The additive microfabrication method of laser-induced forward transfer (LIFT) permits the creation of functional microstructures with feature sizes down to below a micrometre [1]. Compared to other additive manufacturing techniques, LIFT can be used to deposit a broad range of materials in a contactless fashion. LIFT features the possibility of building out of plane features, but is currently limited to 2D or 2½D structures [2–4]. That is because printing of 3D structures requires sophisticated printing strategies, such as mechanical support structures and post-processing, as the material to be printed is in the liquid phase. Therefore, we propose the use of water-soluble materials as a support (and sacrificial) material, which can be easily removed after printing, by submerging the printed structure in water, without exposing the sample to more aggressive solvents or sintering treatments. Here, we present studies on LIFT printing of polyvinyl alcohol (PVA) polymer thin films via a picosecond pulsed laser source. Glass carriers are coated with a solution of PVA (donor) and brought into proximity to a receiver substrate (glass, silicon) once dried. Focussing of a laser pulse with a beam radius of 2 µm at the interface of carrier and donor leads to the ejection of a small volume of PVA that is being deposited on a receiver substrate. The effect of laser pulse fluence , donor film thickness and receiver material on the morphology (shape and size) of the deposits are studied. Adhesion of the deposits on the receiver is verified via deposition on various receiver materials and via a tape test. The solubility of PVA after laser irradiation is confirmed via dissolution in de-ionised water. In our study, the feasibility of the concept of printing PVA with the help of LIFT is demonstrated. The transfer process maintains the ability of water solubility of the deposits allowing the use as support material in LIFT printing of complex 3D structures. Future studies will investigate the compatibility (i.e. adhesion) of PVA with relevant donor materials, such as metals and functional polymers. References: [1] A. Piqué and P. Serra (2018) Laser Printing of Functional Materials. Weinheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA. [2] R. C. Y. Auyeung, H. Kim, A. J. Birnbaum, M. Zalalutdinov, S. A. Mathews, and A. Piqué (2009) Laser decal transfer of freestanding microcantilevers and microbridges, Appl. Phys. A, vol. 97, no. 3, pp. 513–519. [3] C. W. Visser, R. Pohl, C. Sun, G.-W. Römer, B. Huis in ‘t Veld, and D. Lohse (2015) Toward 3D Printing of Pure Metals by Laser-Induced Forward Transfer, Adv. Mater., vol. 27, no. 27, pp. 4087–4092. [4] J. Luo et al. (2017) Printing Functional 3D Microdevices by Laser-Induced Forward Transfer, Small, vol. 13, no. 9, p. 1602553

Blind image deconvolution: nonstationary Bayesian approaches to restoring blurred photos

High quality digital images have become pervasive in modern scientific and everyday life — in areas from photography to astronomy, CCTV, microscopy, and medical imaging. However there are always limits to the quality of these images due to uncertainty and imprecision in the measurement systems. Modern signal processing methods offer the promise of overcoming some of these problems by postprocessing these blurred and noisy images. In this thesis, novel methods using nonstationary statistical models are developed for the removal of blurs from out of focus and other types of degraded photographic images. The work tackles the fundamental problem blind image deconvolution (BID); its goal is to restore a sharp image from a blurred observation when the blur itself is completely unknown. This is a “doubly illposed” problem — extreme lack of information must be countered by strong prior constraints about sensible types of solution. In this work, the hierarchical Bayesian methodology is used as a robust and versatile framework to impart the required prior knowledge. The thesis is arranged in two parts. In the first part, the BID problem is reviewed, along with techniques and models for its solution. Observation models are developed, with an emphasis on photographic restoration, concluding with a discussion of how these are reduced to the common linear spatially-invariant (LSI) convolutional model. Classical methods for the solution of illposed problems are summarised to provide a foundation for the main theoretical ideas that will be used under the Bayesian framework. This is followed by an indepth review and discussion of the various prior image and blur models appearing in the literature, and then their applications to solving the problem with both Bayesian and nonBayesian techniques. The second part covers novel restoration methods, making use of the theory presented in Part I. Firstly, two new nonstationary image models are presented. The first models local variance in the image, and the second extends this with locally adaptive noncausal autoregressive (AR) texture estimation and local mean components. These models allow for recovery of image details including edges and texture, whilst preserving smooth regions. Most existing methods do not model the boundary conditions correctly for deblurring of natural photographs, and a Chapter is devoted to exploring Bayesian solutions to this topic. Due to the complexity of the models used and the problem itself, there are many challenges which must be overcome for tractable inference. Using the new models, three different inference strategies are investigated: firstly using the Bayesian maximum marginalised a posteriori (MMAP) method with deterministic optimisation; proceeding with the stochastic methods of variational Bayesian (VB) distribution approximation, and simulation of the posterior distribution using the Gibbs sampler. Of these, we find the Gibbs sampler to be the most effective way to deal with a variety of different types of unknown blurs. Along the way, details are given of the numerical strategies developed to give accurate results and to accelerate performance. Finally, the thesis demonstrates state of the art results in blind restoration of synthetic and real degraded images, such as recovering details in out of focus photographs