Selected Topics in Bayesian Image/Video Processing

In this dissertation, three problems in image deblurring, inpainting and virtual content insertion are solved in a Bayesian framework.;Camera shake, motion or defocus during exposure leads to image blur. Single image deblurring has achieved remarkable results by solving a MAP problem, but there is no perfect solution due to inaccurate image prior and estimator. In the first part, a new non-blind deconvolution algorithm is proposed. The image prior is represented by a Gaussian Scale Mixture(GSM) model, which is estimated from non-blurry images as training data. Our experimental results on a total twelve natural images have shown that more details are restored than previous deblurring algorithms.;In augmented reality, it is a challenging problem to insert virtual content in video streams by blending it with spatial and temporal information. A generic virtual content insertion (VCI) system is introduced in the second part. To the best of my knowledge, it is the first successful system to insert content on the building facades from street view video streams. Without knowing camera positions, the geometry model of a building facade is established by using a detection and tracking combined strategy. Moreover, motion stabilization, dynamic registration and color harmonization contribute to the excellent augmented performance in this automatic VCI system.;Coding efficiency is an important objective in video coding. In recent years, video coding standards have been developing by adding new tools. However, it costs numerous modifications in the complex coding systems. Therefore, it is desirable to consider alternative standard-compliant approaches without modifying the codec structures. In the third part, an exemplar-based data pruning video compression scheme for intra frame is introduced. Data pruning is used as a pre-processing tool to remove part of video data before they are encoded. At the decoder, missing data is reconstructed by a sparse linear combination of similar patches. The novelty is to create a patch library to exploit similarity of patches. The scheme achieves an average 4% bit rate reduction on some high definition videos

GliaMorph: A modular image analysis toolkit to quantify Müller glial cell morphology

Cell morphology is critical for all cell functions. This is particularly true for glial cells as they rely on complex shape to contact and support neurons. However, methods to quantify complex glial cell shape accurately and reproducibly are lacking. To address this, we developed the image analysis pipeline "GliaMorph". GliaMorph is a modular analysis toolkit developed to perform (i) image pre-processing, (ii) semi-automatic region-of-interest (ROI) selection, (iii) apicobasal texture analysis, (iv) glia segmentation, and (v) cell feature quantification. Müller Glia (MG) have a stereotypic shape linked to their maturation and physiological status. We here characterized MG on three levels, including (a) global image-level, (b) apicobasal texture, and (c) regional apicobasal vertical-to-horizontal alignment. Using GliaMorph we quantified MG development on a global and single-cell level, showing increased feature elaboration and subcellular morphological rearrangement in the zebrafish retina. As proof-of-principle, we analysed expression changes in a mouse glaucoma model, identifying subcellular protein localization changes in MG. Together, GliaMorph enables an in-depth understanding of MG morphology in the developing and diseased retina

LANDSAT-D investigations in snow hydrology

Work undertaken during the contract and its results are described. Many of the results from this investigation are available in journal or conference proceedings literature - published, accepted for publication, or submitted for publication. For these the reference and the abstract are given. Those results that have not yet been submitted separately for publication are described in detail. Accomplishments during the contract period are summarized as follows: (1) analysis of the snow reflectance characteristics of the LANDSAT Thematic Mapper, including spectral suitability, dynamic range, and spectral resolution; (2) development of a variety of atmospheric models for use with LANDSAT Thematic Mapper data. These include a simple but fast two-stream approximation for inhomogeneous atmospheres over irregular surfaces, and a doubling model for calculation of the angular distribution of spectral radiance at any level in an plane-parallel atmosphere; (3) incorporation of digital elevation data into the atmospheric models and into the analysis of the satellite data; and (4) textural analysis of the spatial distribution of snow cover

Ultra-fast Imaging of Two-Phase Flow in Structured Monolith Reactors; Techniques and Data Analysis

This thesis will address the use of nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) techniques to probe the “monolith reactor”, which consists of a structured catalyst over which reactions may occur. This reactor has emerged as a potential alternative to more traditional chemical engineering systems such as trickle bed and slurry reactors. However, being a relatively new design, its associated flow phenomena and design procedures are not rigorously understood, which is retarding its acceptance in industry. Traditional observations are unable to provide the necessary information for design since the systems are opaque and dynamic. Therefore, NMR is proposed as an ideal tool to probe these systems in detail. The theory of NMR is summarised and the development of novel NMR techniques is presented. Novel techniques are validated in simple systems, and tested in more complex systems to ascertain their quantitative nature, and to find their limitations. These techniques are improvements over existing techniques in that they either decrease the acquisition time (allowing the observation of dynamically-changing systems) or allow us to probe systems in different ways to extract useful information. The goal of this research is to better understand the flow phenomena present in such systems, and to use this information to design better, more efficient, more controllable industrial reactors. The analysis of the NMR data acquired is discussed in detail, and several novel image-processing techniques have been developed to aid in the quantification of features within the images, and also to measure quantities such as holdup and velocity. These novel techniques are validated, and then applied to the systems of interest. Various configurations of monolith reactor, ranging from low flow rate systems to more challenging (and more industrially relevant) turbulent systems, are probed using these methods, and the contrasting flow phenomena and performance of these systems are discussed, with a view to optimisation of the choice of design parameters

Radially dependent stray field signature of chiral magnetic skyrmions

Magnetic skyrmions are topological spin structures that arise in chiral magnetic systems which exhibit broken inversion symmetry and high spin-orbit coupling resulting in a sizable Dzyaloshinskii-Moriya interaction. Understanding the local spin texture of skyrmions is a vital metrological step in the development of skyrmionic technologies required for novel logic or storage devices in addition to providing fundamental insight into the nanoscale chiral interactions inherent to these systems. Here, we propose that there exists a radially dependent stray field signature that emanates from magnetic skyrmions. We employ quantitative magnetic force microscopy to experimentally explore this stray field signature. To corroborate the experimental observations a semianalytical model is developed which is validated against micromagnetic simulations. This unique approach provides a route to understand the unique radially dependent field signature from skyrmions, which allows an understanding of the underlying local magnetization profile to be obtained. From a practical standpoint, our results provide a rapid approach to validate outputs from numerical or micromagnetic simulations. This approach could be employed to optimize the complex matrix of magnetic parameters required for fabricating and modeling skyrmionic systems, in turn accelerating the technology readiness level of skyrmionic based devices

Image processing in the human visual system

Journal ArticleThis work extends the multiplicative visual model to include image texture as suggested by experiments [Campbell, Weisel] linking a low resolution Fourier analysis with neurons in certain parts of the visual cortex. The new model takes image texture into account in the sense that weak texture is accentuated and strong, high contrast texture is attenuated. This model is then used as the basis for an improved image enhancement scheme and an unusually successful method for restoring blurred images. In addition, it is suggested how the model may provide new insights into the problem of finding a quantitatively correct image fidelity criterion. The structure of this model is described in relation to visual neurophysiology and examples are presented of images processed by the new techniques. The research described here also shows how the retinex [Land] can be implemented in a new way which allows the required computations to be carried out on a rectangualr grid