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Th. doct.-ing.--Autom.--Grenoble--I.N.P., 1980. N°: DI 153.

Image registration is an important pre-processing operation to be performed before many image exploitation and processing functions such as data fusion, and super-resolution frame. Given two image frames, obtained from the same sensor or from different sensors, the registration problem involves determining the transformation that most nearly maps (or aligns) one image frame into the other. Typically, image registration requires intensive computational effort and the developed techniques are scene dependent. Furthermore, the problems of multimodal image registration (i.e. problem of registering images acquired from dissimilar sensors) and sub-pixel image registration (i.e. registering two images at sub-pixel accuracy) are highly challenging and no satisfactory solutions exist.This dissertation introduces novel techniques to solve the image registration problem both at the pixel-level and at the sub-pixel level. For pixel-level registration, a procedure is offered that enjoys the advantages that it is not scene dependent and provides the same level of accuracy for registering images acquired from different types of sensors. The new technique is based on obtaining the local frequency content of an image and using this local frequency representation to extract control points for establishing correspondence. To extract the local frequency representation of an image, a computationally efficient scheme based on minimizing the latency of a Gabor filter bank by exploiting certain biological considerations is presented. The dissertation also introduces an extension of using local frequency to solve the sub-pixel image registration problem. The new algorithm is based on using the scaled local frequency representation of the images to be registered, with computationally inexpensive scaling of the local frequency of the images prior to correlation matching. Finally, this dissertation provides a novel approach to solve the problem of multi-modal image registration. The principal idea behind this approach is to employ Computer Aided Design (CAD) models of man-made objects in the scene to permit extraction of regions-of-interest (ROI) whose local frequency representations are computed for extraction of stable matching points. Detailed performance evaluation results from an extensive set of experiments using diverse types of images are presented to highlight the strong points of the proposed registration algorithms.

Lau Tak Fu. / Thesis submitted in: October 2003. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 93-98). / Abstracts in English and Chinese. / Chapter 1 - --- Introduction --- p.9 / Chapter 1.1 --- Scope of the work --- p.9 / Chapter 1.2 --- Main contribution --- p.11 / Chapter 1.3 --- Outline of the thesis --- p.12 / Chapter 2 - --- Background --- p.14 / Chapter 2.1 --- Three dimensional models from images --- p.14 / Chapter 2.2 --- Un-calibrated 3D reconstruction --- p.14 / Chapter 2.3 --- Self calibrated 3D reconstruction --- p.16 / Chapter 2.4 --- Initial model formation using image based --- p.18 / Chapter 2.5 --- Volumes from Silhouettes --- p.19 / Chapter 3 - --- Initial model reconstruct the problem with mismatch noise --- p.22 / Chapter 3.1 --- Perspective Camera Model --- p.24 / Chapter 3.2 --- "Intrinsic parameters, Extrinsic parameters and camera motion" --- p.25 / Chapter 3.2.1 --- Intrinsic parameters --- p.25 / Chapter 3.2.2 --- Extrinsic parameter and camera motion --- p.27 / Chapter 3.3 --- Lowe's method --- p.29 / Chapter 3.4 --- Interleave bundle adjustment for structure and motion recovery from multiple images --- p.32 / Chapter 3.5 --- Feature points mismatch analysis --- p.38 / Chapter 4 - --- Feature selection by using look forward silhouette clipping --- p.43 / Chapter 4.1 --- Introduction to silhouette clipping --- p.43 / Chapter 4.2 --- Silhouette clipping for 3D model --- p.45 / Chapter 4.3 --- Implementation --- p.52 / Chapter 4.3.1 --- Silhouette extraction program --- p.52 / Chapter 4.3.2 --- Feature filter for alternative bundle adjustment algorithm --- p.59 / Chapter 5 - --- Experimental data --- p.61 / Chapter 5.1 --- Simulation --- p.61 / Chapter 5.1.1 --- Input of simulation --- p.61 / Chapter 5.1.2 --- Output of the simulation --- p.66 / Chapter 5.1.2.1 --- Radius distribution --- p.66 / Chapter 5.1.2.2 --- 3D model output --- p.74 / Chapter 5.1.2.3 --- VRML plotting --- p.80 / Chapter 5.2 --- Real Image testing --- p.82 / Chapter 5.2.1 --- Toy house on a turntable test --- p.82 / Chapter 5.2.2 --- Other tests on turntable --- p.86 / Chapter 6 - --- Conclusion and discussion --- p.89

Ip Che Yin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 119-127). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Previous Work --- p.2 / Chapter 1.2.1 --- Reconstruction for Architecture Scene --- p.2 / Chapter 1.2.2 --- Super-resolution --- p.4 / Chapter 1.2.3 --- Coarse-to-Fine Approach --- p.4 / Chapter 1.3 --- Proposed solution --- p.6 / Chapter 1.4 --- Contribution --- p.6 / Chapter 1.5 --- Publications --- p.7 / Chapter 1.6 --- Layout of the thesis --- p.7 / Chapter 2 --- Background Techniques --- p.8 / Chapter 2.1 --- Interest Point Detectors --- p.8 / Chapter 2.1.1 --- Scale-space --- p.9 / Chapter 2.1.2 --- Harris Corner detectors --- p.10 / Chapter 2.1.3 --- Other Kinds of Interest Point Detectors --- p.17 / Chapter 2.1.4 --- Summary --- p.18 / Chapter 2.2 --- Steerable filters --- p.19 / Chapter 2.2.1 --- Orientation estimation --- p.20 / Chapter 2.3 --- Point Descriptors --- p.22 / Chapter 2.3.1 --- Image derivatives under illumination change --- p.23 / Chapter 2.3.2 --- Image derivatives under geometric scale change --- p.24 / Chapter 2.3.3 --- An example of a point descriptor --- p.25 / Chapter 2.3.4 --- Other examples --- p.25 / Chapter 2.4 --- Feature Tracking Techniques --- p.26 / Chapter 2.4.1 --- Kanade-Lucas-Tomasi (KLT) Tracker --- p.26 / Chapter 2.4.2 --- Guided Tracking Algorithm --- p.28 / Chapter 2.5 --- RANSAC --- p.29 / Chapter 2.6 --- Structure-from-motion (SFM) Algorithm --- p.31 / Chapter 2.6.1 --- Factorization methods --- p.33 / Chapter 2.6.2 --- Epipolar Geometry --- p.39 / Chapter 2.6.3 --- Bundle Adjustment --- p.47 / Chapter 2.6.4 --- Summary --- p.50 / Chapter 3 --- Hierarchical Registration of 3D Models --- p.52 / Chapter 3.1 --- Overview --- p.53 / Chapter 3.1.1 --- The Arrangement of Image Sequences --- p.53 / Chapter 3.1.2 --- The Framework --- p.54 / Chapter 3.2 3 --- D Model Reconstruction for Each Sequence --- p.57 / Chapter 3.3 --- Multi-scale Image Matching --- p.59 / Chapter 3.3.1 --- Scale-space interest point detection --- p.61 / Chapter 3.3.2 --- Point descriptor --- p.61 / Chapter 3.3.3 --- Point-to-point matching --- p.63 / Chapter 3.3.4 --- Image transformation estimation --- p.64 / Chapter 3.3.5 --- Multi-level image matching --- p.66 / Chapter 3.4 --- Linkage Establishment --- p.68 / Chapter 3.5 --- 3D Model Registration --- p.70 / Chapter 3.6 --- VRML Modelling --- p.73 / Chapter 4 --- Experiment --- p.74 / Chapter 4.1 --- Synthetic Experiments --- p.74 / Chapter 4.1.1 --- Study on Rematching Algorithm --- p.74 / Chapter 4.1.2 --- Comparison between Affine and Metric transforma- tions for 3D Registration --- p.80 / Chapter 4.2 --- Real Scene Experiments --- p.86 / Chapter 5 --- Conclusion --- p.112 / Chapter 5.1 --- Future Work --- p.114 / Chapter A --- Camera Parameters --- p.116 / Chapter A.1 --- Intrinsic Parameters --- p.116 / Chapter A.2 --- Extrinsic Parameters --- p.117 / Bibliography --- p.127

Pun-Mo Ho. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 90-95). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- Existing Approaches --- p.2 / Chapter 1.3 --- Our Approach --- p.3 / Chapter 1.4 --- Structure of the Thesis --- p.4 / Chapter 2 --- Related Work --- p.5 / Chapter 2.1 --- Compression for Navigation --- p.5 / Chapter 2.1.1 --- Light Field/Lumigraph --- p.5 / Chapter 2.1.2 --- Surface Light Field --- p.6 / Chapter 2.1.3 --- Concentric Mosaics --- p.6 / Chapter 2.1.4 --- On the Compression --- p.7 / Chapter 2.2 --- Compression for Relighting --- p.7 / Chapter 2.2.1 --- Previous Approaches --- p.7 / Chapter 2.2.2 --- Our Approach --- p.8 / Chapter 3 --- Image-Based Relighting --- p.9 / Chapter 3.1 --- Plenoptic Illumination Function --- p.9 / Chapter 3.2 --- Sampling and Relighting --- p.11 / Chapter 3.3 --- Overview --- p.13 / Chapter 3.3.1 --- Codec Overview --- p.13 / Chapter 3.3.2 --- Image Acquisition --- p.15 / Chapter 3.3.3 --- Experiment Data Sets --- p.16 / Chapter 4 --- Data Preparation --- p.18 / Chapter 4.1 --- Block Division --- p.18 / Chapter 4.2 --- Color Model --- p.23 / Chapter 4.3 --- Mean Extraction --- p.24 / Chapter 5 --- Principal Component Analysis --- p.29 / Chapter 5.1 --- Overview --- p.29 / Chapter 5.2 --- Singular Value Decomposition --- p.30 / Chapter 5.3 --- Dimensionality Reduction --- p.34 / Chapter 5.4 --- Evaluation --- p.37 / Chapter 6 --- Eigenimage Coding --- p.39 / Chapter 6.1 --- Transform Coding --- p.39 / Chapter 6.1.1 --- Discrete Cosine Transform --- p.40 / Chapter 6.1.2 --- Discrete Wavelet Transform --- p.47 / Chapter 6.2 --- Evaluation --- p.49 / Chapter 6.2.1 --- Statistical Evaluation --- p.49 / Chapter 6.2.2 --- Visual Evaluation --- p.52 / Chapter 7 --- Relighting Coefficient Coding --- p.57 / Chapter 7.1 --- Quantization and Bit Allocation --- p.57 / Chapter 7.2 --- Evaluation --- p.62 / Chapter 7.2.1 --- Statistical Evaluation --- p.62 / Chapter 7.2.2 --- Visual Evaluation --- p.62 / Chapter 8 --- Relighting --- p.65 / Chapter 8.1 --- Overview --- p.66 / Chapter 8.2 --- First-Phase Decoding --- p.66 / Chapter 8.3 --- Second-Phase Decoding --- p.68 / Chapter 8.3.1 --- Software Relighting --- p.68 / Chapter 8.3.2 --- Hardware-Assisted Relighting --- p.71 / Chapter 9 --- Overall Evaluation --- p.81 / Chapter 9.1 --- Compression of IAIs --- p.81 / Chapter 9.1.1 --- Statistical Evaluation --- p.81 / Chapter 9.1.2 --- Visual Evaluation --- p.86 / Chapter 9.2 --- Hardware-Assisted Relighting --- p.86 / Chapter 10 --- Conclusion --- p.89 / Bibliography --- p.90

Inexpensive high quality fundus camera systems enable imaging of retina for vision related health management and diagnosis at large scale. A computer based analysis system can help establish the general baseline of normal conditions vs. anomalous ones, so that different classes of retinal conditions can be classified. Advanced applications, ranging from disease screening algorithms, aging vs. disease trend modeling and prediction, and content-based retrieval systems can be developed. In this dissertation, I propose an analytical framework for the modeling of retina blood vessels to capture their statistical properties, so that based on these properties one can develop blood vessel mapping algorithms with self-optimized parameters. Then, other image objects can be registered based on vascular topology modeling techniques. On the basis of these low level analytical models and algorithms, the third major element of this dissertation is a high level population statistics application, in which texture classification of macular patterns is correlated with vessel structures, which can also be used for retinal image retrieval. The analytical models have been implemented and tested based on various image sources. Some of the algorithms have been used for clinical tests. The major contributions of this dissertation are summarized as follows: (1) A concise, accurate feature representation of retinal blood vessel on retinal images by proposing two feature descriptors Sp and Ep derived from radial contrast transform. (2) A new statistical model of lognormal distribution, which captures the underlying physical property of the levels of generations of the vascular network on retinal images. (3) Fast and accurate detection algorithms for retinal objects, which include retinal blood vessel, macular-fovea area and optic disc, and (4) A novel population statistics based modeling technique for correlation analysis of blood vessels and other image objects that only exhibit subtle texture changes.

Thesis (Ph. D.)--School of Electrical and Computer Engineering, Georgia Institute of Technology, 2004. Directed by Monson H. Hayes. / Vita. Includes bibliographical references (leaves 133-138).

Includes bibliographical references (p. 60-63).

Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 56-60).