In this thesis, I compare the performance of three different autofocus techniques for Synthetic Aperture Radar (SAR). The focusing is done by estimating phase errors in SAR data. The first one, the Phase Gradient Autofocus, is the most popular in the industry, it has been around for more than 20 years and it relies on the redundancy of the phase error in the SAR images. The second one, the Entropy-based minimization, uses measurements of image sharpness to focus the images and it has been available for about 10 years. The last, the Phase-space method, uses the Wigner transform and the ambiguity function of the SAR data to estimate the phase perturbations and it was recently introduced. Additionally, I develop a criteria for filtering the data for the cases in which the Phase-space method does not capture the entirety of the error.

Non-mechanical variable lenses are important for creating compact imaging devices. Various methods employing dielectrically actuated lenses, membrane lenses, and liquid crystal lenses were previously proposed [1-4]. In This dissertation the design, fabrication, and characterization of innovative flat tunable-focus liquid crystal diffractive lenses (LCDL) are presented. LCDL employ binary Fresnel zone electrodes fabricated on Indium-Tin-Oxide using conventional micro-photolithography. The light phase can be adjusted by varying the effective refractive index of a nematic liquid crystal sandwiched between the electrodes and a reference substrate. Using a proper voltage distribution across various electrodes the focal length can be changed between several discrete values. Electrodes are shunted such that the correct phase retardation step sequence is achieved. If the number of 2πzone boundaries is increased by a factor of m the focal length is changed from f to f/m based on the digitized Fresnel zone equation: f = rm²/2mλ, where r(m) is mth zone radius, and λ is the wavelength. The chromatic aberration of the diffractive lens is addressed and corrected by adding a variable fluidic lens. These LCDL operate at very low voltage levels (±2.5V ac input), exhibit fast switching times (20-150 ms), can have large apertures (>10 mm), and small form factor, and are robust and insensitive to vibrations, gravity, and capillary effects that limit membrane and dielectrically actuated lenses. Several tests were performed on the LCDL including diffraction efficiency measurement, switching dynamics, and hybrid imaging with a refractive lens. Negative focal lengths are achieved by adjusting the voltages across electrodes. Using these lenses in combination, magnification can be changed and zoom lenses can be formed. These characteristics make LCDL a good candidate for a variety of applications including auto-focus and zoom lenses in compact imaging devices such as camera phones. A business plan centered on this technology was developed as part of the requirements for the minor in entrepreneurship from the Eller College of Management. An industrial analysis is presented in this study that involves product development, marketing, and financial analyses (Appendix I).

In the context of the ESA BIOMASS mission in which for the first time, a P-Band SAR sensor isgoing to be mounted into a spaceborne system. With its penetration capability, it will contributeto the measurement of the biomass and carbon content in the Earth’s forests. An autofocusalgorithm is needed for the correction of phase errors introduced by the changing diffraction indexin the ionosphere. Because of the quickly changing nature of the ionosphere, defocusing has to bemeasured and corrected locally over several sections of a SAR capture.In this thesis, a deep introduction into phase errors is made having in mind that the ionosphereis expected to introduce time varying low frequency errors that can be constructed as a series ofquadratic curves. These quadratic phase errors introduce defocusing that is seen as blur and lossof contrast. An algorithm is proposed and tested for measuring this defocusing, while its strengthsand weaknesses are discussed.The idea of measuring defocusing is to try to recover the temporal phase function that introduceddefocusing in the first place. Here a method to recover this temporal phase function is introduced,and a thorough performance assessment of this retrieval is carried out. The variables involved thequality and reliability of this retrieval are studied one by one.

The main topic of this master thesis is creating, testing and implementation of algorithms for autofocus with Canon camera lens using CAN-EF interface, while one of the assignments is possibility to continuous focus to the vehicle in traffic monitoring. There are tested a number of criteria for the assessment if sharpness in the image and is designed automatic control system of the lens and camera.

The quality of clinical pathology is a critical index for evaluating a nation's healthcare level. Recently developed digital pathology techniques have the capability to transform pathological slides into digital whole slide images (WSI). This transformation facilitates data storage, online transmission, real-time viewing, and remote consultations, significantly elevating clinical diagnosis. The effectiveness and efficiency of digital pathology imaging often hinge on the precision and speed of autofocusing. However, achieving autofocusing of pathological images presents challenges under constraints including uneven focus distribution and limited Depth of Field (DoF). Current autofocusing methods, such as those relying on image stacks, need to use more time and resources for capturing and processing images. Moreover, autofocusing based on reflective hardware systems, despite its efficiency, incurs significant hardware costs and suffers from a lack of system compatibility. Finally, machine learning-based autofocusing can circumvent repetitive mechanical movements and camera shots. However, a simplistic end-to-end implementation that does not account for the imaging process falls short of delivering satisfactory focus prediction and in-focus image restoration. In this thesis, we present three distinct autofocusing techniques for defocus pathology images: (1) Aberration-aware Focal Distance Prediction leverages the asymmetric effects of optical aberrations, making it ideal for focus prediction within focus map scenarios; (2) Dual-shot Deep Autofocusing with a Fixed Offset Prior is designed to merge two images taken at different defocus distances with fixed positions, ensuring heightened accuracy in in-focus image restoration for fast offline situations; (3) Semi-blind Deep Restoration of Defocus Images utilizes multi-task joint prediction guided by PSF, enabling high-efficiency, single-pass scanning for offline in-focus image restoration. / Thesis / Doctor of Philosophy (PhD)

Synthetic aperture radar is an important tool in a wide range of civilian and military imaging applications. This is primarily due to its ability to image in all weather conditions, during both the day and the night, unlike optical imaging systems. A synthetic aperture radar system contains a step which is not present in an optical imaging system, this is image formation. This is required because the acquired data from the radar sensor does not directly correspond to the image. Instead, to form an image, the system must solve an inverse problem. In conventional scenarios, this inverse problem is relatively straight forward and a matched lter based algorithm produces an image of suitable image quality. However, there are a number of interesting scenarios where this is not the case. Scenarios where standard image formation algorithms are unsuitable include systems with data undersampling, errors in the system observation model and data that is corrupted by radio frequency interference. Image formation in these scenarios will form the topics of this thesis and a number of iterative algorithms are proposed to achieve image formation. The motivation for these proposed algorithms is primarily from the eld of compressed sensing, which considers the recovery of signals with a low-dimensional structure. The rst contribution of this thesis is the development of fast algorithms for the system observation model and its adjoint. These algorithms are required by large-scale gradient based iterative algorithms for image formation. The proposed algorithms are based on existing fast back-projection algorithms, however, a new decimation strategy is proposed which is more suitable for some applications. The second contribution is the development of a framework for iterative near- eld image formation, which uses the proposed fast algorithms. It is shown that the framework can be used, in some scenarios, to improve the visual quality of images formed from fully sampled data and undersampled data, when compared to images formed using matched lter based algorithms. The third contribution concerns errors in the system observation model. Algorithms that correct these errors are commonly referred to as autofocus algorithms. It is shown that conventional autofocus algorithms, which work as a post-processor on the formed image, are unsuitable for undersampled data. Instead an autofocus algorithm is proposed which corrects errors within the iterative image formation procedure. The proposed algorithm is provably stable and convergent with a faster convergence rate than previous approaches. The nal contribution is an algorithm for ultra-wideband synthetic aperture radar image formation. Due to the large spectrum over which the ultra-wideband signal is transmitted, there is likely to be many other users operating within the same spectrum. These users can produce signi cant radio frequency interference which will corrupt the received data. The proposed algorithm uses knowledge of the RFI spectrum to minimise the e ect of the RFI on the formed image.

La diffraction constitue une limite fondamentale en microscopie, mais souvent cette limite n'est même pas atteinte. Des imperfections dans la formation d'image, appelées aberrations, peuvent être induites par le microscope ou l'échantillon. Un élément actif, dit correcteur, est intégré au chemin optique pour leur compensation. Les paramètres de ce correcteur doivent être déterminés sans dommage excessif pour l'échantillon. Il faut comparer le gain en signal et/ou en résolution avec cet endommagement, surtout pour des échantillons biologiques fragiles. En première partie de cette thèse je présente une modalité particulière de la microscopie par cohérence optique (nommé deep-OCM). Ce développement a permis la mesure exacte et in vivo de l'indice de réfraction moyen du cerveau du rat. Cette valeur implique que la microscopie bi-photonique est limitée par des aberrations optiques à partir d'une profondeur de 200 µm dans ce type d'échantillon. Le deep-OCM est bien adapté à l'imagerie de fibres nerveuses myélinisées. Des fibres individuelles peuvent être visualisées in vivo dans le cerveau à des profondeurs auparavant inaccessibles, supérieures à 300 µm. Dans la deuxième partie de cette thèse je présente le développement d'un autofocus et auto-stigmateur (nommé MAPFoSt) pour le microscope électronique à balayage qui permet d'assurer la qualité maximale des images lors d'un changement d'échantillon ou pendant des séries d'acquisitions de longue durée. MAPFoSt permet de déterminer avec précision les trois paramètres du focus et du stigmatisme en utilisant seulement deux images de test

A Bussgang based blind deconvolution algorithm called self-correcting multi-channel Bussgang (SCMB) blind deconvolution algorithm was proposed. Unlike the original Bussgang blind deconvolution algorithm where the probability density function (pdf) of the signal being recovered is assumed to be completely known, the proposed SCMB blind deconvolution algorithm relaxes this restriction by parameterized the pdf with a Gaussian mixture model and expectation maximization (EM) algorithm, an iterative maximum likelihood approach, is employed to estimate the parameter side by side with the estimation of the equalization filters of the original Bussgang blind deconvolution algorithm. A feedback loop is also designed to compensate the effect of the parameter estimation error on the estimation of the equalization filters. Application of the SCMB blind deconvolution framework for binary image restoration, multi-pass synthetic aperture radar (SAR) autofocus and inverse synthetic aperture radar (ISAR) autofocus are exploited with great results.

The long-term goal of this research is to assist in the development of a fast, accurate, and low-cost nondestructive inspection prototype for solder joints in integrated circuits (IC). The goal of the work described in this thesis is to develop a fully automated system to maintain the signal strength of the vibrometer that would reduce the testing time while maintaining or improving the quality of the defect detection results. The ability to perform the inspections in an automated manner is very important in order to demonstrate the ability of the defect detection system to be used for online inspection without the need of an operator. The system was able to find the maximum signal strength (at a single point on the surface of a flip chip) nearly five times faster than Polytec's commercial system with a search time of approximately 2.1 sec. When integrated into the nondestructive inspection prototype, the system described in this work was found to approximately reduce the data acquisition time per test location by four times, with a minimum data acquisition time of 8.5 sec and an average time of 15.4 sec, while maintaining the same level of quality of results obtained by a skilled operator when manually maintaining the signal strength of the vibrometer. Hardware was developed that retrofitted a vibrometer's focusing head at the end of a fiber optic cable to a motorized linear stage. This stage controlled the standoff distance between the focusing head and the IC's surface with a fixed focal length, which allowed the spot size of the laser to be adjusted while searching for a desired signal strength. Numerous tests were conducted to determine the search parameters, which led to a search time of approximately 2.1 sec. This time was found to be dependent on the surface finish of the IC being inspected. It was also found that to achieve a desired signal intensity strength, not only does the standoff height of the focusing head, which determines the laser spot size, need to be controlled, but also the exact location on which the laser is reflecting off the IC.

This diploma thesis describes optimization of the experimental parameters for Laser-induced breakdown spectroscopy of plant samples. First part deals with the theoretical method of LIBS and explains the principles and terms. In the next part there is described device which was used for measurements. Main part of diploma thesis describes creation of program for measurement-automation. Main task of program was to solve the connection of autofocus on the sample with the sample automatic movement. Furthermore are described and elaborated specific measurements for optimization of the experimental parameters for Laser-induced breakdown spectroscopy of plant samples.