Optimized imaging using non-rigid registration

The extraordinary improvements of modern imaging devices offer access to data with unprecedented information content. However, widely used image processing methodologies fall far short of exploiting the full breadth of information offered by numerous types of scanning probe, optical, and electron microscopies. In many applications, it is necessary to keep measurement intensities below a desired threshold. We propose a methodology for extracting an increased level of information by processing a series of data sets suffering, in particular, from high degree of spatial uncertainty caused by complex multiscale motion during the acquisition process. An important role is played by a nonrigid pixel-wise registration method that can cope with low signal-to-noise ratios. This is accompanied by formulating objective quality measures which replace human intervention and visual inspection in the processing chain. Scanning transmission electron microscopy of siliceous zeolite material exhibits the above-mentioned obstructions and therefore serves as orientation and a test of our procedures

Solutions to linear problems in aberrated optical systems

Linear problems are possibly the kindest problems in physics and mathematics. Given sufficient information, the linear equations describing such problems are intrinsically solvable. The solution can be written as a vector having undergone a linear transformation in a vector space; extracting the solution is simply a matter of inverting the transformation. In an ideal optical system, the problem of extracting the object under investigation would be well defined, and the solution trivial to implement. However, real optical systems are all aberrated in some way, and these aberrations obfuscate the information, scrambling it and rendering it inextricable. The process of detangling the object from the aberrated system is no longer a trivial problem or even a uniquely solvable one, and represents one of the great challenges in optics today. This thesis provides a review of the theory behind optical microscopy in the presence of absent information, an architecture for the modern physical and computational methods used to solve the linear inversion problem, and three distinct application spaces of relevance. I hope you find it useful

Multiframe Super-Resolution of Color Image Sequences Using a Global Motion Model

The development of efficient software tools capable of super- resolving multi-spectral image sequences on-the-fly is an important step toward the production of imaging systems capable of acquiring vital imagery of hostile environments at an affordable price. A number of image processing tools already available for use in target recognition and identification rely on the availability of high-resolution imagery which cannot be safely acquired at a reasonable price. This thesis investigates the use of multiframe super-resolution as a tool to increase the spatial resolution of image sequences acquired with sensors commonly used in consumer video cameras. Multiframe super-resolution is the branch of imaging science which tries to restore high-resolution estimates of a scene utilizing a sequence of under-sampled images of that scene. Although a number of algorithms have already been developed to deal with this problem, they have unfortunately not been extended to deal with multi-spectral images acquired from moving imaging platforms. This thesis performs such extension for one of the most successful super-resolution algorithm and demonstrates that it can be used to improve the performance of common multi-spectral imaging systems utilizing Color Filter Arrays to acquire spectral data

Light-sheet microscopy: a tutorial

This paper is intended to give a comprehensive review of light-sheet (LS) microscopy from an optics perspective. As such, emphasis is placed on the advantages that LS microscope configurations present, given the degree of freedom gained by uncoupling the excitation and detection arms. The new imaging properties are first highlighted in terms of optical parameters and how these have enabled several biomedical applications. Then, the basics are presented for understanding how a LS microscope works. This is followed by a presentation of a tutorial for LS microscope designs, each working at different resolutions and for different applications. Then, based on a numerical Fourier analysis and given the multiple possibilities for generating the LS in the microscope (using Gaussian, Bessel, and Airy beams in the linear and nonlinear regimes), a systematic comparison of their optical performance is presented. Finally, based on advances in optics and photonics, the novel optical implementations possible in a LS microscope are highlighted.Peer ReviewedPostprint (published version

Computational Depth-resolved Imaging and Metrology

In this thesis, the main research challenge boils down to extracting 3D spatial information of an object from 2D measurements using light. Our goal is to achieve depth-resolved tomographic imaging of transparent or semi-transparent 3D objects, and to perform topography characterization of rough surfaces. The essential tool we used is computational imaging, where depending on the experimental scheme, often indirect measurements are taken, and tailored algorithms are employed to perform image reconstructions. The computational imaging approach enables us to relax the hardware requirement of an imaging system, which is essential when using light in the EUV and x-ray regimes, where high-quality optics are not readily available. In this thesis, visible and infrared light sources are used, where computational imaging also offers several advantages. First of all, it often leads to a simple, flexible imaging system with low cost. In the case of a lensless configuration, where no lenses are involved in the final image-forming stage between the object and the detector, aberration-free image reconstructions can be obtained. More importantly, computational imaging provides quantitative reconstructions of scalar electric fields, enabling phase imaging, numerical refocus, as well as 3D imaging

Image Restoration

This book represents a sample of recent contributions of researchers all around the world in the field of image restoration. The book consists of 15 chapters organized in three main sections (Theory, Applications, Interdisciplinarity). Topics cover some different aspects of the theory of image restoration, but this book is also an occasion to highlight some new topics of research related to the emergence of some original imaging devices. From this arise some real challenging problems related to image reconstruction/restoration that open the way to some new fundamental scientific questions closely related with the world we interact with