Lidars are very promising instruments for the remote-sensing of the Earth, and are eagerly awaited for operational missions, particularly in the observation of the atmosphere. However, spaceborne lidars are still in their early development and there have been many setbacks associated with their technology. The high energy of the laser beam contributes to the formation of contamination deposit on laser optics, leading to the degradation of the lidar performance and eventual failure of the instrument. This high energy requirement can partially or totally be offset by a larger telescope and / or a lower orbit, with the implication of a greater drag force acting on the satellite. This work investigates the options for satellite and lidar telescope configuration which minimise their contribution to drag while maximising the telescope aperture diameter for lidar performance. A MATLAB/Simulink trajectory model is developed to establish the propulsion requirements for drag compensation. Parametric models are used to size the satellite, its subsystem and the lidar. This study elaborates the conditions under which a lidar mission might work in a low altitude orbit. In particular, it explores the feasibility and applicability of four concepts against the requirements of some challenging lidar missions. The model developed also identifies that past studies may have under-estimated the electric propulsion requirements for lidar missions in low altitudes.

The rapid growth in the volume of visual information, e.g. image, and video can overwhelm users’ ability to find and access the specific visual information of interest to them. In recent years, ontology knowledge-based (KB) image information retrieval techniques have been adopted into in order to attempt to extract knowledge from these images, enhancing the retrieval performance. A KB framework is presented to promote semi-automatic annotation and semantic image retrieval using multimodal cues (visual features and text captions). In addition, a hierarchical structure for the KB allows metadata to be shared that supports multi-semantics (polysemy) for concepts. The framework builds up an effective knowledge base pertaining to a domain specific image collection, e.g. sports, and is able to disambiguate and assign high level semantics to ‘unannotated’ images. Local feature analysis of visual content, namely using Scale Invariant Feature Transform (SIFT) descriptors, have been deployed in the ‘Bag of Visual Words’ model (BVW) as an effective method to represent visual content information and to enhance its classification and retrieval. Local features are more useful than global features, e.g. colour, shape or texture, as they are invariant to image scale, orientation and camera angle. An innovative approach is proposed for the representation, annotation and retrieval of visual content using a hybrid technique based upon the use of an unstructured visual word and upon a (structured) hierarchical ontology KB model. The structural model facilitates the disambiguation of unstructured visual words and a more effective classification of visual content, compared to a vector space model, through exploiting local conceptual structures and their relationships. The key contributions of this framework in using local features for image representation include: first, a method to generate visual words using the semantic local adaptive clustering (SLAC) algorithm which takes term weight and spatial locations of keypoints into account. Consequently, the semantic information is preserved. Second a technique is used to detect the domain specific ‘non-informative visual words’ which are ineffective at representing the content of visual data and degrade its categorisation ability. Third, a method to combine an ontology model with xi a visual word model to resolve synonym (visual heterogeneity) and polysemy problems, is proposed. The experimental results show that this approach can discover semantically meaningful visual content descriptions and recognise specific events, e.g., sports events, depicted in images efficiently. Since discovering the semantics of an image is an extremely challenging problem, one promising approach to enhance visual content interpretation is to use any associated textual information that accompanies an image, as a cue to predict the meaning of an image, by transforming this textual information into a structured annotation for an image e.g. using XML, RDF, OWL or MPEG-7. Although, text and image are distinct types of information representation and modality, there are some strong, invariant, implicit, connections between images and any accompanying text information. Semantic analysis of image captions can be used by image retrieval systems to retrieve selected images more precisely. To do this, a Natural Language Processing (NLP) is exploited firstly in order to extract concepts from image captions. Next, an ontology-based knowledge model is deployed in order to resolve natural language ambiguities. To deal with the accompanying text information, two methods to extract knowledge from textual information have been proposed. First, metadata can be extracted automatically from text captions and restructured with respect to a semantic model. Second, the use of LSI in relation to a domain-specific ontology-based knowledge model enables the combined framework to tolerate ambiguities and variations (incompleteness) of metadata. The use of the ontology-based knowledge model allows the system to find indirectly relevant concepts in image captions and thus leverage these to represent the semantics of images at a higher level. Experimental results show that the proposed framework significantly enhances image retrieval and leads to narrowing of the semantic gap between lower level machinederived and higher level human-understandable conceptualisation.

The exploration of large information spaces has remained a challenging task even though the proliferation of database management systems and the state-of-the art retrieval algorithms is becoming pervasive. Signi cant research attention in the multimedia domain is focused on nding automatic algorithms for organising digital image collections into meaningful structures and providing high-semantic image indices. On the other hand, utilisation of graphical and interactive methods from information visualisation domain, provide promising direction for creating e cient user-oriented systems for image management. Methods such as exploratory browsing and query, as well as intuitive visual overviews of image collection, can assist the users in nding patterns and developing the understanding of structures and content in complex image data-sets. The focus of the thesis is combining the features of automatic data processing algorithms with information visualisation. The rst part of this thesis focuses on the layout method for displaying the collection of images indexed by low-level visual descriptors. The proposed solution generates graphical overview of the data-set as a combination of similarity based visualisation and random layout approach. Second part of the thesis deals with problem of visualisation and exploration for hierarchical organisation of images. Due to the absence of the semantic information, images are considered the only source of high-level information. The content preview and display of hierarchical structure are combined in order to support image retrieval. In addition to this, novel exploration and navigation methods are proposed to enable the user to nd the way through database structure and retrieve the content. On the other hand, semantic information is available in cases where automatic or semi-automatic image classi ers are employed. The automatic annotation of image items provides what is referred to as higher-level information. This type of information is a cornerstone of multi-concept visualisation framework which is developed as a third part of this thesis. This solution enables dynamic generation of user-queries by combining semantic concepts, supported by content overview and information ltering. Comparative analysis and user tests, performed for the evaluation of the proposed solutions, focus on the ways information visualisation a ects the image content exploration and retrieval; how e cient and comfortable are the users when using di erent interaction methods and the ways users seek for information through di erent types of database organisation.

There is an increasing demand for sensors in extreme environments, i.e. high temperature and radiation environments, where conventional sensors lose their functionality and reliability because of the environmental impact. The dependence on electricity makes conventional sensor susceptible to extreme accident situation and demanding frequent maintenance which could be even more costly in those extreme environments. To overcome this problem, this thesis reports the development of a remote optically actuated and interrogated resonant sensor with a micro corner cube retroreflector (CCR) structure. The proposed sensor takes the advantage of MEMS scaling to enable optical actuation and remote interrogation. It does not rely on any local electrical power or electric elements therefore it is more resistant to high temperature and radiation impact. In this thesis, a micro paddle resonant sensor is theoretically shown to be able to get actuated without using electrical power or electric element. The remote actuation with optical method was analytically modelled and simulated. A simple and impact optical interrogation system is designed by combining the micro paddle resonator with a micro CCR structure which allows interrogating light source and detecting photodiode to be placed in the same place utilising the retroreflection of the CCR. The fabrication methods of the paddle mirror and micro CCR sidewalls were demonstrated respectively. Finally, a completed fabrication plan is provided.

The dominant noise source in aLIGO is Brownian thermal noise, due to mechanical losses in the atomic structure of the amorphous titania doped tantala end test-mass mirror coatings. This thesis investigates the structural source of these losses. The effect of titania doping and thermal annealing upon the atomic structure of amorphous tantalum pentoxide coating preparations are studied using advanced electron diffraction techniques. Significant differences between the coating atomic structures have been identified for the first time in detail. The tantala based coatings studied have been demonstrated as better described by a heterogeneous phase separated model, rather than the continuous random network model for covalently bonded amorphous metal-oxides. The short-range ordering (SRO) of the coating atomic structures was investigated using pair-distribution function analyses, with an upper limit found to be ~4 Å. Correlations spanned ~9 Å, and have been related to model structures; between 4 - 5 Å, correlations were identified as signatures for 3D structural ordering. Fluctuation Electron Microscopy (FEM) was employed to investigate the MRO of the coating atomic structures. A novel approach to FEM was developed by the author during this PhD, in which the structural variance was computed using normalised cross-correlation coefficients. This made absolute intensity irrelevant, with the shape and the spatial distribution of the diffracted intensity taking precedence. The method is insensitive to poor SNR, illumination conditions, slight differences in experimental facility, and slight thickness variations in the samples. Virtual Dark-Field (VDF) imaging was adapted to amorphous structures in novel ways for the first time in this thesis. Simultaneous representation of the FEM data in real and reciprocal space, spatially resolved the structures responsible for the FEM signal. Correlation analyses were performed between VDF images of the structural ordering that relate to specific atom-pair correlations, including the use of novel annular variance images. The images and correlations clearly highlight the heterogeneous ordering and phase separation within the structures. Mechanisms responsible for the coating mechanical losses have been proposed, relating to the MRO, tensile-stress, as well as its reduction by titanium doping.

The research undertaken unites two distinct areas of quantum information processing: single ions stored in radio-frequency traps and single photons in optical fibres. Strings of ions are presently the most successful implementation of quantum computing, with elementary quantum algorithm and quantum simulations realised. The principal challenge in the field is to enhance the quantum processing power by scaling up current devices to larger systems. We pursue one of the most promising strategies: distributed quantum computation in which multiple small-scale ion processors are interlinked by exchanging photonic quantum bits via optical fibres. This requires a coherent quantum interface between ions and photons, mapping ionic to photonic quantum states and vice versa. To maximise fidelity and the success rate of the scheme, the interaction of ions and photons must take place in a microscopic optical cavity with high finesse. To this end, single 40Ca+ were trapped in a radio-frequency ion trap whose trapping electrodes are hollow cylinders. Optical fibres with mirrors machined on the facets are inserted into the electrodes to form a Fabry-Pérot cavity. Because the fibres are shielded by the electrodes the detrimental distortion of the trapping field due to their presence is suppressed and ions can be trapped for several hours. 40Ca+ has a -type energy level scheme wherein the ion is cooled on the 42P1/2 ⇔ 42S1/2 transition and the cavity is tuned to the 42P1/2 ⇔ 32D3/2 transition. This thesis reports the successful coupling of single ions to a high finesse optical fibre based cavity, with coupling strength g = 2π · 4:6 MHz. The cavity has length 367 μm, finesse of 40,000 and linewidth 2k = 2π · 9:4 MHz. In this coupling regime, the enhancement of the ion's emission rate through the Purcell effect was observed. Further, anti-correlation was observed in the emission rates between the P1/2 ⇔ D3/2 and P1/2 ⇔ S1/2 transitions with an effective emission rate suppression of up to 60% in the latter transition. The built system offers greater promises. Once the position in the cavity mode has been optimised we expect to reach the long-sought after strong coupling regime with (g, k, y) = 2π · (12:2; 4:7; 11:2) MHz.

The current approach to data analysis for the Laser Interferometry Space Antenna (LISA) depends on the time delay interferometry observables (TDI) which have to be generated before any weak signal detection can be performed. These are linear combinations of the raw data with appropriate time shifts that lead to the cancellation of the laser frequency noises. This is possible because of the multiple occurrences of the same noises in the different raw data. Originally, these observables were manually generated starting with LISA as a simple stationary array and then adjusted to incorporate the antenna's motions. However, none of the observables survived the flexing of the arms in that they did not lead to cancellation with the same structure. The principal component approach is another way of handling these noises that was presented by Romano and Woan which simplified the data analysis by removing the need to create them before the analysis. This method also depends on the multiple occurrences of the same noises but, instead of using them for cancellation, it takes advantage of the correlations that they produce between the different readings. These correlations can be expressed in a noise (data) covariance matrix which occurs in the Bayesian likelihood function when the noises are assumed be Gaussian. Romano and Woan showed that performing an eigendecomposition of this matrix produced two distinct sets of eigenvalues that can be distinguished by the absence of laser frequency noise from one set. The transformation of the raw data using the corresponding eigenvectors also produced data that was free from the laser frequency noises. This result led to the idea that the principal components may actually be time delay interferometry observables since they produced the same outcome, that is, data that are free from laser frequency noise. The aims here were (i) to investigate the connection between the principal components and these observables, (ii) to prove that the data analysis using them is equivalent to that using the traditional observables and (ii) to determine how this method adapts to real LISA especially the flexing of the antenna. For testing the connection between the principal components and the TDI observables a 10x 10 covariance matrix containing integer values was used in order to obtain an algebraic solution for the eigendecomposition. The matrix was generated using fixed unequal arm lengths and stationary noises with equal variances for each noise type. Results confirm that all four Sagnac observables can be generated from the eigenvectors of the principal components. The observables obtained from this method however, are tied to the length of the data and are not general expressions like the traditional observables, for example, the Sagnac observables for two different time stamps were generated from different sets of eigenvectors. It was also possible to generate the frequency domain optimal AET observables from the principal components obtained from the power spectral density matrix. These results indicate that this method is another way of producing the observables therefore analysis using principal components should give the same results as that using the traditional observables. This was proven by fact that the same relative likelihoods (within 0.3%) were obtained from the Bayesian estimates of the signal amplitude of a simple sinusoidal gravitational wave using the principal components and the optimal AET observables. This method fails if the eigenvalues that are free from laser frequency noises are not generated. These are obtained from the covariance matrix and the properties of LISA that are required for its computation are the phase-locking, arm lengths and noise variances. Preliminary results of the effects of these properties on the principal components indicate that only the absence of phase-locking prevented their production. The flexing of the antenna results in time varying arm lengths which will appear in the covariance matrix and, from our toy model investigations, this did not prevent the occurrence of the principal components. The difficulty with flexing, and also non-stationary noises, is that the Toeplitz structure of the matrix will be destroyed which will affect any computation methods that take advantage of this structure. In terms of separating the two sets of data for the analysis, this was not necessary because the laser frequency noises are very large compared to the photodetector noises which resulted in a significant reduction in the data containing them after the matrix inversion. In the frequency domain the power spectral density matrices were block diagonals which simplified the computation of the eigenvalues by allowing them to be done separately for each block. The results in general showed a lack of principal components in the absence of phase-locking except for the zero bin. The major difference with the power spectral density matrix is that the time varying arm lengths and non-stationarity do not show up because of the summation in the Fourier transform.

This thesis describes the improvements to the image replicating imaging spectrometer (IRIS) and the development of novel applications in the field of oximetry. IRIS is a snapshot multispectral device with a high transmission output and no need of inversion for data recovering, hence, with high signal-to-noise ratio (SNR). IRIS shows great versatility due to the possibility of choosing multiple contiguous or non-contiguous wavelengths inside its free spectral range. IRIS uses a set of waveplates and Wollaston prisms to demultiplex the spectral information of an object and replicate the image of such object in different wavelengths. The birefringent nature of IRIS means that different wavelengths are separated by the Wollaston prisms with different angles, introducing multiple images of the same object. In addition, the spectral transmission function shows multiple spectral sidelobes that contaminate each IRIS band with light belonging to other wavelengths. These issues can lower the performance of IRIS as a multispectral imaging device. In this thesis, these problems were assessed with the introduction of a filter plate array placed in the image plane of the optical system. This filter array is a set of narrow-band filters (Full Width Half Maximum (FWHM) =10 ± 2 nm ) that removes undesired wavelengths from each IRIS band. Since the spectral transmission of IRIS is replicated along the free spectral range, the filters can be designed to match any of the present spectral lobes in IRIS. The design and fabrication of a filter array enhance the performance of IRIS as a multispectral imaging device: it allows wavelength selection and improves spectral and spatial image quality. The design and manufacture of the corresponding filter holder and camera adapter were critical in terms of offering an easy filter-camera implementation. The filter plate allowed the removal of other dispersed wavelengths by the Wollaston prisms, improving image registration between the set of spectral images created by IRIS, and so, improving the quality of the registered spectral 3-D cube. The implemented improvements on IRIS allow high quality, calibration-free oximetry using eight different wavelengths optimised for oximetry. Two main experiments were performed: 1) Using an inverted microscopy interfaced with IRIS and a linear spectral unmixing technique, we measured the deoxygenation of single horse red blood cells (RBC) in vitro in real time. The oximetry was performed with a subcellular spatial resolution of 0.5 μ m , a temporal resolution of 30 Hz, and an accuracy (standard error of the mean) of ± 1.1% in oxygen saturation. 2) Eight-wavelength calibration-free retinal oximetry performed in nine healthy subjects demonstrated an increase in the stability of the oxygen saturation measurements along retinal vessels when compared with more traditional analysis methods such as two wavelengths oximetry. The stability was measured as the standard deviation along the retinal vessels of the nine subjects and was found to be ∼ 3% in oxygen saturation for eight-wavelengths oximetry and ∼ 5% in oxygen saturation for two-wavelengths oximetry. A modified physical model was used to improve the characterization of light propagation through the eye, retina, and blood vessels by applying a set of feasible physiological assumptions. This model was optimised by an algorithm which solves for the different variables involved in the retinal vessels transmissions in order to accurately calculate the oxygen saturation. The oximetry algorithm was applied in retinal vessels, in collaboration in vivo on rat spinal cord to assess hypoxia in inflammatory diseases such as multiple sclerosis and rheumatoid arthritis and on mice legs to assess hypoxia on autoimmune diseases. A third experiment using a microscope interfaced with IRIS was performed. The experiment aimed to replicate laminar flow conditions observed in retinal vessels and to calculate oxygen diffusion between adjacent streams of blood with different oxygen saturation. For this purpose a PDMS multichannel flow cell with cross sections of 40x100 μm was designed and fabricated allowing us to replicate conditions found in retinal blood vessels. Laminar flow was replicated but the experiment failed in calculating oxygen diffusion due to flaws in the experiment. The experiment with the results and recommendations on how to improve it can be found in Apendix B for future researchers.

In this thesis, I investigate fibre optical parametric amplifiers (OPA) and oscillators (OPO), in terms of their potential for efficient large frequency-shift wavelength conversion. The underlying physical mechanism of fibre four wave mixing (FWM) offers simultaneous up-conversion and down-conversion in frequency to arbitrary wavelengths, determined by the pump wavelength and chromatic dispersion of the fibre. Using optical pulses from an ytterbium-doped fibre master-oscillator power-amplifier (MOPA), at a wavelength of 1080 nm, I experimentally and numerically evaluate the suitability of various fibres for frequency up-conversion towards the visible spectrum. The use of an Yb-doped fibre source allows for all-fibre integration with fibre optical parametric devices, potentially making it a viable alternative to expensive bulk sources currently employed in the sub-1-μm spectral region. To accommodate an all-fibre configuration, the first part of the thesis numerically investigates polarization maintaining (PM) as well as higher-order mode fibres for phase-matched FWM at relatively modest pump peak powers (< 1 kW). Experiments using the PM fibre in an OPA configuration, and employing multiple seeding arrangements, are subsequently presented. Here, it is found that the influence of fibre inhomogeneity, coupled with a relatively small parametric bandwidth and competing nonlinear processes, severely impairs the conversion efficiency from the 1080 nm pump wave to the anti-Stokes wave at 840 nm. The work in the second part of the thesis reports on the use of higher-order dispersion phase-matching in a photonic crystal fibre (PCF). In the OPA configuration, this approach proves more efficient and demonstrates parametric conversion over 142 THz to an anti-Stokes wave at 715 nm. The PCF is also reconfigured into an all-fibre uni-directional ring-cavity OPO, for which the dependence on nonlinear converter length, out-coupling ratio, pump pulse duration and intra-cavity filtering are studied. Using a PCF length of 18 m and 800 ps pump pulses with sub-kW peak powers, this all-fibre OPO demonstrates, what is believed to be, a record in-fibre pump-to-anti-Stokes conversion efficiency in excess of 10% over 142 THz. Finally, computer simulations, aimed at realising a dispersion engineered PCF for an enhanced parametric gain bandwidth, is carried out for a pump wavelength around 1 μm. PCF designs of this type, using GeO2-doped core regions, are identified for arbitrary frequency-shift FWM. It is demonstrated that these fibres can enhance the parametric bandwidth by up to three orders of magnitude, which can lead to a significant reduction in the sensitivity of FWM to fibre inhomogeneities. An increased parametric bandwidth should furthermore enable the use of pump sources that are not currently considered to be viable. The fibres are finally also considered in terms of fabrication tolerances.

In this thesis, new methods for the efficient segmentation of images are presented. The proposed methods are based on the deformable model approach, and can be used efficiently in the segmentation of complex geometries from various imaging modalities. A novel deformable model that is based on a geometrically induced external force field which can be conveniently generalized to arbitrary dimensions is presented. This external force field is based on hypothesized interactions between the relative geometries of the deformable model and the object boundary characterized by image gradient. The evolution of the deformable model is solved using the level set method so that topological changes are handled automatically. The relative geometrical configurations between the deformable model and the object boundaries contributes to a dynamic vector force field that changes accordingly as the deformable model evolves. The geometrically induced dynamic interaction force has been shown to greatly improve the deformable model performance in acquiring complex geometries and highly concave boundaries, and give the deformable model a high invariance in initialization configurations. The voxel interactions across the whole image domain provides a global view of the object boundary representation, giving the external force a long attraction range. The bidirectionality of the external force held allows the new deformable model to deal with arbitrary cross-boundary initializations, and facilitates the handling of weak edges and broken boundaries. In addition, it is shown that by enhancing the geometrical interaction field with a nonlocal edge-preserving algorithm, the new deformable model can effectively overcome image noise. A comparative study on the segmentation of various geometries with different topologies from both synthetic and real images is provided, and the proposed method is shown to achieve significant improvements against several existing techniques. A robust framework for the segmentation of vascular geometries is described. In particular, the framework consists of image denoising, optimal object edge representation, and segmentation using implicit deformable model. The image denoising is based on vessel enhancing diffusion which can be used to smooth out image noise and enhance the vessel structures. The image object boundaries are derived using an edge detection technique which can produce object edges of single pixel width. The image edge information is then used to derive the geometric interaction field for optimal object edge representation. The vascular geometries are segmented using an implict deformable model. A region constraint is added to the deformable model which allows it to easily get around calcified regions and propagate across the vessels to segment the structures efficiently. The presented framework is ai)plied in the accurate segmentation of carotid geometries from medical images. A new segmentation model with statistical shape prior using a variational approach is also presented in this thesis. The proposed model consists of an image attraction force that propagates contours towards image object boundaries, and a global shape force that attracts the model towards similar shapes in the statistical shape distribution. The image attraction force is derived from gradient vector interactions across the whole image domain, which makes the model more robust to image noise, weak edges and initializations. The statistical shape information is incorporated using kernel density estimation, which allows the shape prior model to handle arbitrary shape variations. It is shown that the proposed model with shape prior can be used to segment object shapes from images efficiently.