視頻監控通常是指為了管理、引導和保護人們，通過電子設備監視和人們有關的行為、活動或者信息變化，例如使用閉路電視或者攔截遠距離電子傳輸的信息，如網絡流量，手機通信。視頻監控的潛在應用包括國土安全，反犯罪，交通控製，小孩、老人和病人的遠程看護。視頻監控技術為打擊恐怖主义和异常事件提供一小重要的防護。通過使用闭路电視摄像机等廉份的現代电子技朮使得視頻監控可成為可能。但是，除非一直監視著來自這些攝像機的反饋，否則它們提供僅僅是一些心理上安全。僱用足夠的人員來監督這些成千上萬的屏幕是不現實的，然而使用具有高度智能的現代自動化系統可以彌補這一空缺。 / 對于全天候地準確地管理成千上萬地攝像機，人工智能化的視頻監控是非常必要而且重要的。通常來說，智能監控包括以下部分: 1 信息獲取，如利用一個或者多個攝像機或者熱感成像或深度成像攝像機; 2 視頻分析，如目標檢測，識別，跟蹤，再識別或分割。3 存儲和傳輸，如編碼，分類和製片。在本文中，我們構建一個智能監控系統，其包括三個相互協作的摄像機用來估計感興趣物體的3D位置並且進行研究和跟蹤。為了識別物體，我們提出級聯頭肩檢測器尋找人臉區域進行識別。感興趣物體分割出來用于任意形狀物體編碼器對物體進行壓縮。 / 在第一部分中，我們討論如何使多個攝像頭在一起工作。在我們系統中，兩個固定的攝像機像人眼一樣註視著整個監控場景，搜尋非正常事件。如果有警報被非正常事件激活， PTZ攝像機會用來處理該事件，例如去跟蹤或者調查不明物體。利用相機標定技術，我們可以估計出物體的3D信息并將其傳輪到三個攝像機。 / 在第二部分中，我們提出級聯頭肩檢測器來檢測正面的頭肩并進行高級別的物體分析，例如識別和異常行為分析。在檢測器中，我們提出利用級聯結構融閤兩種強大的特徵， Harar-like 特微和HOG特徽，他們能有傚的檢測人臉和行人。利用Harr-like特徵，頭肩檢測器能夠在初期用有限的計算去除非頭肩區域。檢測的區域可以用來識別和分割。 / 在第三部分中，利用訓練的糢型，人臉區域可以從檢測到的頭肩區域中提取。利用CAMshift對人臉區域進行細化。在視頻監控的環境中，人臉識別是十分具有挑戰性的，因為人臉圖像受到多種因素的影響，例如在不均勻光綫條件下變化姿態和非聚焦糢糊的人臉。基于上述觀測，我們提出一種使用OLPF特微結閤AGMM糢型的人臉識別方法，其中OLPF特徵不僅不受糢糊圖像的影響，而且對人臉的姿態很魯棒。AGMM能夠很好地構建多種人臉。對標準測試集和實際數據的實驗結果證明了我們提出的方法一直地优于其它最先進的人臉識別方法。 / 在第四部分中，我們提出一種自動人體分割系統。首先，我們用檢測到的人臉或者人體對graph cut分割模型初始化并使用max-flow /min-cut算法對graph進行優化。針對有缺點的檢測目標的情況，采用一種基于coarse-to-fine的分割策略。我們提出抹除背景差別技術和自適應初始化level set 技術來解決存在于通用模型中的讓人頭疼的分割問題，例如發生在高差別的物體邊界區域或者在物體和背景中存在相同顏色的錯誤分割。實驗結果證明了我們的人體分割系統在實時視頻圖像和具有復雜背景的標準測試序列中都能很好的運作。 / 在最后部分中，我們專註于怎么樣對視頻內容進行智能的壓縮。在最近幾十年里，視頻編碼研究取得了巨大的成就，例如H.264/AVC標準和下一代的HEVC標準，它們的壓縮性能大大的超過以往的標準，高于50% 。但是相對于MPEG-4 ，在最新的編碼標準中缺少了壓縮任意形狀物體的能力。雖然在現在的H.264/AVC 中提供了片組結構和彈性模塊組閤技術，但是它仍然不能準確地高效地處理任意形狀區域。為了解決H.264/AVC 的這一缺點，我們提出基于H.264/AVC編碼框架的任意形狀物體編碼，它包括二值圖像編碼，運動補償和紋理編碼。在我們系統里，我們采用了1) 用新的運動估計改進的二值圖像編碼，它對二值塊的預測很有用。2) 在紋理編碼中，采用新的任意形狀整型變換來壓縮紋理信息，它是一種從4x4的ICT衍生出來的變換。3)和一些讓該編碼器勻新的框架兼容的相關編碼技術。我們把編碼器應用到高清視頻序列並且從客觀方便和主觀方面對編碼器進行評估。實驗結果證明了我們的編碼器遠遠超越以前的物體編碼方法並且十分接近H.264/AVC 的編碼性能。 / Surveillance is the process of monitoring the behaviour, activities, or changing information, usually of people for the purpose of managing, directing or protecting by means of electronic equipment, such as closed-circuit television (CCTV) camera or interception of electronically transmitted information from a distance, such as Internet or phone calls. Some potential surveillance applications are homeland security, anti-crime, traffic control, monitoring children, elderly and patients at a distance. Surveillance technology provides a shield against terrorism and abnormal event, and cheap modern electronics makes it possible to implement with CCTV cameras. But unless the feeds from those cameras are constantly monitored, they only provide an illusion of security. Finding enough observers to watch thousands of screens simply is impractical, yet modern automated systems can solve the problems with a surprising degree of intelligence. / Surveillance with intelligence is necessary and important to accurately mange the information from millions of sensors in 7/24 hours. Generally, intelligent surveillance includes: 1. information acquirement, like a single or the collaboration of multiple cameras, thermal or depth camera; 2. video analysis, like object detection, recognition, tracking, re-identification and segmentation; 3. storage and transmission, like coding, classification, and footage. In this thesis, we build an intelligent surveillance system, in which three cameras working collaboratively to estimate the position of the object of interest (OOI) in 3D space, investigate and track it. In order to identify the OOI, Cascade Head-Shoulder Detector is proposed to find the face region for recognition. The object can be segmented out and compressed by arbitrarily shaped object coding (ASOC). / In the first part, we discuss how to make the multiple cameras work together. In our system, two stationary cameras, like human eyes, are focusing on the whole scene of the surveillance region to observe abnormal events. If an alarm is triggered by abnormal instance, a PTZ camera will be assigned to deal with it, such as tracking orinvestigating the object. With calibrated cameras, the 3D information of the object can be estimated and communicated among the three cameras. / In the second part, cascade head-shoulder detector (CHSD) is proposed to detect the frontal head-shoulder region in the surveillance videos. The high-level object analysis will be performed on the detected region, e.g., recognition and abnormal behaviour analysis. In the detector, we propose a cascading structure that fuses the two powerful features: Haar-like feature and HOG feature, which have been used to detect face and pedestrian efficiently. With the Haar-like feature, CHSD can reject most of non-headshoulder regions in the earlier stages with limited computations. The detected region can be used for recognition and segmentation. / In the third part, the face region can be extracted from the detected head-shoulder region with training the body model. Continuously adaptive mean shift (CAMshift) is proposed to refine the face region. Face recognition is a very challenging problem in surveillance environment because the face image suffers from the concurrence of multiple factors, such as a variant pose with out-of-focused blurring under non-uniform lighting condition. Based on this observations, we propose a face recognition method using overlapping local phase feature (OLPF) feature and adaptive Gaussian mixture model (AGMM). OLPF feature is not only invariant to blurring but also robust to pose variations and AGMM can robustly model the various faces. Experiments conducted on standard dataset and real data demonstrate that the proposed method consistently outperforms the state-of-art face recognition methods. / In the forth part, we propose an automatic human body segmentation system. We first initialize graph cut using the detected face/body and optimize the graph by maxflow/ min-cut. And then a coarse-to-fine segmentation strategy is employed to deal with the imperfectly detected object. Background contrast removal (BCR) and selfadaptive initialization level set (SAILS) are proposed to solve the tough problems that exist in the general graph cut model, such as errors occurred at object boundary with high contrast and similar colors in the object and background. Experimental results demonstrate that our body segmentation system works very well in live videos and standard sequences with complex background. / In the last part, we concentrate on how to intelligently compress the video context. In recent decades, video coding research has achieved great progress, such as inH.264/AVC and next generation HEVC whose compression performance significantly exceeds previous standards by more than 50%. But as compared with the MPEG-4, the capability of coding arbitrarily shaped objects is absent from the following standards. Despite of the provision of slice group structures and flexible macroblock ordering (FMO) in the current H.264/AVC, it cannot deal with arbitrarily shaped regions accurately and efficiently. To solve the limitation of H.264/AVC, we propose the arbitrarily shaped object coding (ASOC) based on the framework H.264/AVC, which includes binary alpha coding, motion compensation and texture coding. In our ASOC, we adopt (1) an improved binary alpha Coding with a novel motion estimation to facilitate the binary alpha blocks prediction, (2) an arbitrarily shaped integer transform derivative from the 4×4 ICT in H.264/AVC to code texture and (3) associated coding techniques to make ASOC more compatible with the new framework. We extent ASOC to HD video and evaluate it objectively and subjectively. Experimental results prove that our ASOC significantly outperforms previous object-coding methods and performs close to the H.264/AVC. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Liu, Qiang. / "November 2012." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 123-135). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Abstracts in English and Chinese. / Dedication --- p.ii / Acknowledgments --- p.iii / Abstract --- p.vii / Publications --- p.x / Nomenclature --- p.xii / Contents --- p.xviii / List of Figures --- p.xxii / List of Tables --- p.xxiii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation and objectives --- p.1 / Chapter 1.2 --- A brief review of camera calibration --- p.2 / Chapter 1.3 --- Object detection --- p.5 / Chapter 1.3.1 --- Face detection --- p.5 / Chapter 1.3.2 --- Pedestrian detection --- p.7 / Chapter 1.4 --- Recognition --- p.8 / Chapter 1.5 --- Segmentation --- p.10 / Chapter 1.5.1 --- Thresholding-based methods --- p.11 / Chapter 1.5.2 --- Clustering-based methods --- p.11 / Chapter 1.5.3 --- Histogram-based methods --- p.12 / Chapter 1.5.4 --- Region-growing methods --- p.12 / Chapter 1.5.5 --- Level set methods --- p.13 / Chapter 1.5.6 --- Graph cut methods --- p.13 / Chapter 1.5.7 --- Neural network-based methods --- p.14 / Chapter 1.6 --- Object-based video coding --- p.14 / Chapter 1.7 --- Organization of thesis --- p.16 / Chapter 2 --- Cameras Calibration --- p.18 / Chapter 2.1 --- Introduction --- p.18 / Chapter 2.2 --- Basic Equations --- p.21 / Chapter 2.2.1 --- Parameters of Camera Model --- p.22 / Chapter 2.2.2 --- Two-view homography induced by a Plane --- p.22 / Chapter 2.3 --- Pair-wise pose estimation --- p.23 / Chapter 2.3.1 --- Homography estimation --- p.24 / Chapter 2.3.2 --- Calculation of n and λ --- p.24 / Chapter 2.3.3 --- (R,t) Estimation --- p.25 / Chapter 2.4 --- Distortion analysis and correction --- p.27 / Chapter 2.5 --- Feature detection and matching --- p.28 / Chapter 2.6 --- 3D point estimation and evaluation --- p.30 / Chapter 2.7 --- Conclusion --- p.34 / Chapter 3 --- Cascade Head-Shoulder Detector --- p.35 / Chapter 3.1 --- Introduction --- p.35 / Chapter 3.2 --- Cascade head-shoulder detection --- p.36 / Chapter 3.2.1 --- Initial feature rejecter --- p.37 / Chapter 3.2.2 --- Haar-like rejecter --- p.39 / Chapter 3.2.3 --- HOG feature classifier --- p.40 / Chapter 3.2.4 --- Cascade of classifiers --- p.45 / Chapter 3.3 --- Experimental results and analysis --- p.46 / Chapter 3.3.1 --- CHSD training --- p.46 / Chapter 3.4 --- Conclusion --- p.49 / Chapter 4 --- A Robust Face Recognition in Surveillance --- p.50 / Chapter 4.1 --- Introduction --- p.50 / Chapter 4.2 --- Cascade head-shoulder detection --- p.53 / Chapter 4.2.1 --- Body model training --- p.53 / Chapter 4.2.2 --- Face region refinement --- p.54 / Chapter 4.3 --- Face recognition --- p.56 / Chapter 4.3.1 --- Overlapping local phase feature (OLPF) --- p.56 / Chapter 4.3.2 --- Fixed Gaussian Mixture Model (FGMM) --- p.59 / Chapter 4.3.3 --- Adaptive Gaussian mixture model --- p.61 / Chapter 4.4 --- Experimental verification --- p.62 / Chapter 4.4.1 --- Preprocessing --- p.62 / Chapter 4.4.2 --- Face recognition --- p.63 / Chapter 4.5 --- Conclusion --- p.66 / Chapter 5 --- Human Body Segmentation --- p.68 / Chapter 5.1 --- Introduction --- p.68 / Chapter 5.2 --- Proposed automatic human body segmentation system --- p.70 / Chapter 5.2.1 --- Automatic human body detection --- p.71 / Chapter 5.2.2 --- Object Segmentation --- p.73 / Chapter 5.2.3 --- Self-adaptive initialization level set --- p.79 / Chapter 5.2.4 --- Object Updating --- p.86 / Chapter 5.3 --- Experimental results --- p.87 / Chapter 5.3.1 --- Evaluation using real-time videos and standard sequences --- p.87 / Chapter 5.3.2 --- Comparison with Other Methods --- p.87 / Chapter 5.3.3 --- Computational complexity analysis --- p.91 / Chapter 5.3.4 --- Extensions --- p.93 / Chapter 5.4 --- Conclusion --- p.93 / Chapter 6 --- Arbitrarily Shaped Object Coding --- p.94 / Chapter 6.1 --- Introduction --- p.94 / Chapter 6.2 --- Arbitrarily shaped object coding --- p.97 / Chapter 6.2.1 --- Shape coding --- p.97 / Chapter 6.2.2 --- Lossy alpha coding --- p.99 / Chapter 6.2.3 --- Motion compensation --- p.102 / Chapter 6.2.4 --- Texture coding --- p.105 / Chapter 6.3 --- Performance evaluation --- p.108 / Chapter 6.3.1 --- Objective evaluations --- p.108 / Chapter 6.3.2 --- Extension on HD sequences --- p.112 / Chapter 6.3.3 --- Subjective evaluations --- p.115 / Chapter 6.4 --- Conclusions --- p.119 / Chapter 7 --- Conclusions and future work --- p.120 / Chapter 7.1 --- Contributions --- p.120 / Chapter 7.1.1 --- 3D object positioning --- p.120 / Chapter 7.1.2 --- Automatic human body detection --- p.120 / Chapter 7.1.3 --- Human face recognition --- p.121 / Chapter 7.1.4 --- Automatic human body segmentation --- p.121 / Chapter 7.1.5 --- Arbitrarily shaped object coding --- p.121 / Chapter 7.2 --- Future work --- p.122 / Bibliography --- p.123

Typescript (photocopy). / Digitized by Kansas Correctional Industries

With increasing availability and diversity of visual data generated in research labs and everyday life, it is becoming critical to develop disciplined and practical computation tools for such data. This thesis focuses on the low complexity representations and algorithms for visual data, in light of recent theoretical and algorithmic developments in high-dimensional data analysis. We first consider the problem of modeling a given dataset as superpositions of basic motifs. This model arises from several important applications, including microscopy image analysis, neural spike sorting and image deblurring. This motif-finding problem can be phrased as "short-and-sparse" blind deconvolution, in which the goal is to recover a short convolution kernel from its convolution with a sparse and random spike train. We normalize the convolution kernel to have unit Frobenius norm and then cast the blind deconvolution problem as a nonconvex optimization problem over the kernel sphere. We demonstrate that (i) in a certain region of the sphere, every local optimum is close to some shift truncation of the ground truth, when the activation spike is sufficiently sparse and long, and (ii) there exist efficient algorithms that recover some shift truncation of the ground truth under the same conditions. In addition, the geometric characterization of the local solution as well as the proposed algorithm naturally extend to more complicated sparse blind deconvolution problems, including image deblurring, convolutional dictionary learning. We next consider the problem of modeling physical nuisances across a collection of images, in the context of illumination-invariant object detection and recognition. Illumination variation remains a central challenge in object detection and recognition. Existing analyses of illumination variation typically pertain to convex, Lambertian objects, and guarantee quality of approximation in an average case sense. We show that it is possible to build vertex-description convex cone models with worst-case performance guarantees, for nonconvex Lambertian objects. Namely, a natural detection test based on the angle to the constructed cone guarantees to accept any image which is sufficiently well approximated with an image of the object under some admissible lighting condition, and guarantees to reject any image that does not have a sufficiently approximation. The cone models are generated by sampling point illuminations with sufficient density, which follows from a new perturbation bound for point images in the Lambertian model. As the number of point images required for guaranteed detection may be large, we introduce a new formulation for cone preserving dimensionality reduction, which leverages tools from sparse and low-rank decomposition to reduce the complexity, while controlling the approximation error with respect to the original cone. Preliminary numerical experiments suggest that this approach can significantly reduce the complexity of the resulting model.

All-optical signal processing. In current and future optical communication systems and networks, the data rate per wavelength has been approaching the speed limitation of electronics. Thus, all-optical signal processing techniques are highly desirable to support the necessary optical switching functionalities in future ultrahigh-speed optical packet-switching networks. To cope with the wide use of optical phase-modulated signals, in the thesis, an all-optical logic for DPSK or PSK input signals is developed, for the first time. Based on four-wave mixing in semiconductor optical amplifier, the structure of the logic gate is simple, compact, and capable of supporting ultrafast operation. In addition to the general logic processing, a simple label recognition scheme, as a specific signal processing function, is proposed for phase-modulated label signals. The proposed scheme can recognize any incoming label pattern according to the local pattern, and is potentially capable of handling variable-length label patterns. / In recent years, optical phase modulation has attracted much research attention in the field of fiber optic communications. Compared with the traditional optical intensity-modulated signal, one of the main merits of the optical phase-modulated signal is the better transmission performance. For optical phase modulation, in spite of the comprehensive study of its transmission performance, only a little research has been carried out in terms of its functions, applications and signal processing for future optical networks. / Optical access network with multicast overlay and centralized light sources. In the arena of optical access networks, wavelength division multiplexing passive optical network (WDM-PON) is a promising technology to deliver high-speed data traffic. However, most of proposed WDM-PONs only support conventional point-to-point service, and cannot meet the requirement of increasing demand on broadcast and multicast service. In this thesis, a simple network upgrade is proposed based on the traditional PON architecture to support both point-to-point and multicast service. In addition, the two service signals are modulated on the same lightwave carrier. The upstream signal is also remodulated on the same carrier at the optical network unit, which can significantly relax the requirement on wavelength management at the network unit. / Optical time-division multiplexing and demultiplexing. With the ever-increasing demand on communication bandwidth, optical time division multiplexing (OTDM) is an effective approach to upgrade the capacity of each wavelength channel in current optical systems. OTDM multiplexing can be simply realized, however, the demultiplexing requires relatively complicated signal processing and stringent timing control, and thus hinders its practicability. To tackle this problem, in this thesis a new OTDM scheme with hybrid DPSK and OOK signals is proposed. Experimental investigation shows this scheme can greatly enhance the demultiplexing timing misalignment and improve the demultiplexing performance, and thus make OTDM more practical and cost effective. / These issues are systematically investigated in this thesis. The research findings suggest that optical phase modulation and its signal processing can greatly facilitate flexible network functions and high bandwidth which can be enjoyed by end users. In the thesis, the most important physical-layer technology, signal processing and multiplexing, are investigated with optical phase-modulated signals. Novel and advantageous signal processing and multiplexing approaches are proposed and studied. Experimental investigations are also reported and discussed in the thesis. / Deng, Ning. / "August 2007." / Adviser: Calvin Chun-Kit Chan. / Source: Dissertation Abstracts International, Volume: 69-02, Section: B, page: 1196. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 119-127). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract in English and Chinese. / School code: 1307.

In intelligent document processing system and geographical information systems (GIS), the image processing and recognition play an important role. This thesis deals with various problems in processing images in documents and GIS: image smoothing, filling, linearization and extraction of contour features, extraction of structural points, separation and recognition of spurious segments in handwritten digits, reconstruction and recognition of broken digits, and separation and recognition of colour document and GIS images. These approaches are also called Optical Character Recognition (OCR). A new smoothing technique is developed to smooth follow contours of image. With the new smoothing algorithms, spurious pixels (points) of contours are removed based on smooth patterns, and smooth followed contours are found. Also, skeletons of image can be smoothed between neighboring �end� and �junction� points. Smooth following makes linearization of smoothed contours possible based on Freeman codes. A new filling algorithm of contours, project filling, is described based on two kinds of structural patterns. By this method, any complicated contours of images can be filled correctly. Different from other linearization methods, linearization and feature extraction of smoothed contours are based on difference chain codes. Curvature and bend angles of linearized are found. The convexity and concavity of linearized are described. In this way, a series of description features of contours is formed. Structural points are new and useful features to describe morphological structures between neighboring linearized lines. Extraction of structural points is based on structural patterns which are determined by element chain codes. Also, extension Freeman codes are used in this thesis. Structural points make description and recognition of contours possible. In order to recognize handwritten digits in document processing systems, separation of spurious segments, reconstruction of broken digits and recognition of handwritten digits are investigated. Experiments with large number of testing data set show satisfactory results for these algorithms. Separation and recognition of colour document and GIS images are discussed. Object images of document and GIS images are extracted based on the description of shape structures, prior knowledge and color information, which are associated with each other. Color images can be described by a limited number of colors in color document and GIS images. Therefore, separation of color image is done by color reduction method, and recognition of object images is based on structure patterns, prior knowledge and colour information. It can be seen that specific information should be considered in many practical problems to achieve better processing results.

One computer disk in pocket inside back cover. / System requirements for accompanying computer disk: Macintosh computer. / Bibliography: leaves 148-160. / xii, 161 leaves : ill. (some col.) ; 30 cm. + 1 computer disk (3.5 in. DD) / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / This thesis presents two new families of classification algorithms for pixel classification based on multi-spectral texture. The research demonstrates that algorithms making use of multispectral texture can be constructed that produce better classifications than standard algorithms at comparable computational cost. / Thesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1994?

Thesis (Ph.D.)--University of Delaware, 2006. / Principal faculty advisor: Fouad Kiamilev, Dept. of Electrical and Computer Engineering. Includes bibliographical references.

Thesis (Ph.D.)--University of Delaware, 2006. / Principal faculty advisor: Fouad Kiamilev, Dept. of Electrical and Computer Engineering. Includes bibliographical references.

In the conventional diffraction tomography a linear array is used to receive forward scattered field. Then a standard algorithm like back propagation or Fourier domain interpolation is used for reconstruction of the object. A circular array which captures both forward and backward scattered field has been proposed. A new theorem is proposed, which states that the scattered field measured with a large circular array surrounding the object is proportional to the Fourier transform of the object profile taken on the circumference of a circle of radius equa1 to the wave number and centered at (-k0 cosZO, -k0 sin Z0). The circular array outperforms in two counts. Firstly, a larger bandwidth of Fourier transform is used for reconstruction. Secondly, in circular array since the scattered field itself is related to the object Fourier transform, the reconstruction is free from the errors induced by finite array size. The effect of broad band illumination has been studied. A fewer number of illuminations appear to produce a reconstruction which is possible only with a large number of illuminations but narrow band illumination. Thus a trade off between the number of illumination angles and the bandwidth of the source exists.

Thesis (M.Sc. (Chemistry))--University of Pretoria, 2000. / Summaries in Afrikaans and English. Also available online.