Five algorithms in different applications are proposed in this thesis. All of them are formulated as smoothness based labeling problems, including single image segmentation, video object cutout, image/video completion, image denoising, and image matting. According to different definitions, different optimization approaches are used in these algorithms. In single image segmentation and video object cutout, the graph-cut algorithms are used; in image/video completion, belief propagation is used; and in image denoising and image matting, closed form optimization is implemented. / Many applications in computer vision can be formulated as labeling problems of assigning each pixel a label where the labels represent some local quantities. If all pixels are regarded as independent, i.e., the label of each pixel has nothing to do with the labels of other pixels, such labeling problems are seriously sensitive to noise. On the other hand, for applications in videos, if the inter-frame information is neglected, the performance of the algorithms will be degraded. / Successful performance of the five proposed algorithms, with comparisons to related methods, demonstrates that the proposed models of the labeling problems using the smoothness-based priors work very well in these computer vision applications. / Such labeling problems with smoothness-based priors can be solved by minimizing a Markov energy. According to different definitions of the energy functions, different optimization tools can be used to obtain the results. In this thesis, three optimization approaches are used due to their good performance: graph cuts, belief propagation, and optimization with a closed form solution. / To improve results of these labeling problems, smoothness-based priors can be enforced in the formulations. For a single image, the smoothness is the spatial coherence, which means that spatially close pixels trend to have similar labels. For a video, an additional temporal coherence is enforced, which means that the corresponding pixels in different frames should have similar labels. The spatial coherence constraint makes algorithms robust to noise and the temporal coherence constraint utilizes the inter-frame information for better video-based applications. / Chen, Shifeng. / Adviser: Liu Jian Zhuang. / Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3594. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 130-145). / 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. / Abstracts in English and Chinese. / School code: 1307.

隨著數碼相機與移動照相設備的日益普及，現時的拍攝照片數量遠遠超過以前。數碼照相機的內在缺陷使得數字圖像還原領域得到廣泛的興趣。在本論文中，我們將研究圖像去模糊。圖像去模糊旨在從一張模糊的圖像恢復出清晰的圖像。它是一個在計算機視覺和圖形學有理論和實踐影響力的根本問題。單圖反卷積問題是一個十分挑戰的問題因為我們觀察到的信息比要恢復的信息要少。我們討論模糊核估計並分析為什麼現存的算法可以獲得成功。基於這些分析和理解，我們提出了一個創新的統一框架。該框架具有優異的圖像對模糊性能，並且只需使用很少的運算時間。這個框架還被擴展到了非均一的圖像去模糊上，並且取得與最先進算法相當的效果。 / 在現實模糊圖像中，模糊常常是非均一的，這種模糊具有更大的挑戰性。均一模糊的技術發展使得這個問題相對於以前較容易著手。在本論文中，我們對現存的相機抖動模型進行了詳細的研究並討論其中存在的一些問題。我們對相機模型進行歸納總結並且提出了基於每個平面的非均一圖像去模糊框架。基於這個框架，我們解決了一種特殊形式的模糊。這種模糊是產生於外平面運動，常見於用車載，體育和監控相機拍攝的照片。我們在具有挑戰性的網絡圖片和自己拍攝的圖片上進行測試，驗證了我們的方法的正確性。 / With the popularity of digital cameras and mobile phone cameras, much more photos are being taken nowadays than ever before. The imperfection of digital cameras arouses broad interest in digital image restoration. In this thesis, we study an important topic, i.e., image deblurring, which aims to recover a sharp image from only a blurry observation. It is one of the fundamental problems in computer vision and graphics with both theoretical and practical impact. Single image blind deconvolution is challenging since there are more unknowns than observations. We discuss problems involving blur kernel estimation and why state-ofthe-art methods work. These insights lead to a novel unified framework to achieve decent deblurring performance on publicly available datasets in faster speed. The extension of the framework to non-uniform image deblurring also achieves comparable performance to state-of-the-art methods. / Further, in real blurred images, it is quite often that blur is spatiallyvariant, which is very difficult to deal with. Advance in uniform deblurring makes this problem tractable. We make a detailed study of current camera shake models and discuss problems in these models. We also generalize the framework and propose a plane-wise non-uniform image deblurring framework. Based on it, we tackle a specific type of blur involving out-of-plane motion, which typically appears on photos captured using car, sport and surveillance camera. We validate our method on challenging photos obtained from internet and taken by ourselves. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Zheng, Shicheng. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 71-79). / Abstracts also in Chinese. / Abstract --- p.i / Acknowledgement --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation and Objectives --- p.1 / Chapter 1.2 --- Contributions --- p.5 / Chapter 1.3 --- Thesis Outline --- p.6 / Chapter 2 --- Background --- p.8 / Chapter 2.1 --- Non-blind Image Deconvolution --- p.8 / Chapter 2.2 --- Blind Deconvolution --- p.13 / Chapter 2.3 --- Non-uniform Image Deblurring --- p.14 / Chapter 3 --- Unnatural Representation For Natural Image Deblurring --- p.19 / Chapter 3.0.1 --- Analysis --- p.21 / Chapter 3.0.2 --- Our Contribution --- p.23 / Chapter 3.1 --- Framework --- p.24 / Chapter 3.2 --- Optimization --- p.28 / Chapter 3.2.1 --- Solve for k --- p.28 / Chapter 3.2.2 --- Solve for k{U+1D57}⁺¹ with l{U+1D57}+1 --- p.32 / Chapter 3.2.3 --- Final Image Restoration --- p.34 / Chapter 3.3 --- Discussion --- p.34 / Chapter 3.4 --- Experimental Results --- p.38 / Chapter 3.5 --- Concluding Remarks --- p.41 / Chapter 4 --- Forward Motion Deblurring --- p.43 / Chapter 4.1 --- Background --- p.45 / Chapter 4.2 --- OurModel --- p.51 / Chapter 4.3 --- Forward Motion Deblurring. --- p.55 / Chapter 4.3.1 --- Kernel and Image Restoration --- p.55 / Chapter 4.4 --- Implementation and Discussion --- p.58 / Chapter 4.5 --- Experimental Results --- p.59 / Chapter 4.6 --- Conclusion and Limitation --- p.64 / Chapter 5 --- Conclusion --- p.65 / Chapter A --- New Sparsity Function --- p.67 / Bibliography --- p.71

Leung, Man Kin. / Thesis submitted in: October 2008. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 121-126). / Abstracts in English and Chinese. / Abstract --- p.ii / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Motivation --- p.4 / Chapter 1.3 --- Contributions --- p.5 / Chapter 1.4 --- Organization of the thesis --- p.6 / Chapter 2 --- Literature review --- p.8 / Chapter 2.1 --- Introduction --- p.8 / Chapter 2.2 --- Background knowledge --- p.9 / Chapter 2.2.1 --- Pinhole camera model --- p.10 / Chapter 2.2.2 --- Kalman filter --- p.11 / Chapter 2.2.3 --- Extended Kalman filter --- p.14 / Chapter 2.2.4 --- Unscented Kalman filter --- p.15 / Chapter 2.3 --- Batch method --- p.19 / Chapter 2.3.1 --- Multiple view geometry --- p.19 / Chapter 2.3.2 --- Factorization --- p.21 / Chapter 2.3.3 --- Bundle adjustment --- p.22 / Chapter 2.4 --- Sequential method --- p.23 / Chapter 2.5 --- SLAM using cameras --- p.24 / Chapter 2.6 --- Summary --- p.26 / Chapter 3 --- Pose tracking of a stereo camera system --- p.27 / Chapter 3.1 --- Overview --- p.27 / Chapter 3.1.1 --- Related work --- p.27 / Chapter 3.1.2 --- Contribution --- p.29 / Chapter 3.2 --- Problem definition --- p.29 / Chapter 3.3 --- Algorithm --- p.31 / Chapter 3.3.1 --- Initialization --- p.33 / Chapter 3.3.2 --- Feature tracking and stereo correspondence matching --- p.33 / Chapter 3.3.3 --- Pose tracking based on two trifocal tensors --- p.35 / Chapter 3.3.4 --- Pose tracking using extended Kalman filter (Our EKF-2 approach) --- p.37 / Chapter 3.3.5 --- Pose tracking using unscented Kalman filter (Our UKF-2 approach) --- p.41 / Chapter 3.3.6 --- Pose tracking using differential evolution (Our DE-2 approach) --- p.44 / Chapter 3.4 --- Experiment --- p.49 / Chapter 3.4.1 --- Synthetic experiments --- p.49 / Chapter 3.4.2 --- Real experiments --- p.55 / Chapter 3.5 --- Summary --- p.67 / Chapter 4 --- Advance to two pairs of stereo cameras --- p.68 / Chapter 4.1 --- Overview --- p.68 / Chapter 4.1.1 --- Related work --- p.68 / Chapter 4.1.2 --- Contribution --- p.69 / Chapter 4.2 --- Problem definition --- p.70 / Chapter 4.3 --- Algorithm --- p.72 / Chapter 4.3.1 --- Initialization --- p.72 / Chapter 4.3.2 --- Feature tracking and stereo correspondence matching --- p.74 / Chapter 4.3.3 --- Pose tracking based on four trifocal tensors --- p.76 / Chapter 4.3.4 --- Pose tracking using extended Kalman filter (Our EKF-4 approach) --- p.79 / Chapter 4.3.5 --- Pose tracking using unscented Kalman filter (Our UKF-4 approach) --- p.84 / Chapter 4.4 --- Experiment --- p.87 / Chapter 4.4.1 --- Synthetic experiments --- p.87 / Chapter 4.4.2 --- Real experiments --- p.100 / Chapter 4.5 --- Summary --- p.113 / Chapter 5 --- Conclusion --- p.115 / Chapter 5.1 --- Conclusion --- p.115 / Chapter 5.2 --- Scope of Applications --- p.116 / Chapter 5.3 --- Limitations --- p.117 / Chapter 5.4 --- Difficulties --- p.118 / Chapter 5.5 --- Future work --- p.118 / Bibliography --- p.121

Digital inpainting is the reconstruction of a missing or damaged region in a digital image. Intensity values in the missing region are approximated using information near the boundary of the region. Some applications include repair of chipped paintings, repair of rips in paper photographs, and removal of unwanted objects from photographs. In this thesis, we review 2D digital inpainting techniques, examine the application of 3D digital inpainting to cell path reconstruction, and propose a new inpainting technique inspired by the cell path reconstruction problem. Cell path reconstruction is the estimation of the shape and position of living cells in videos recorded using fluorescence microscopy. This procedure is necessary because in a particular phase of the life cycle of some cells, fluorescent light passes through the cells with an undetectable change in wavelength and they vanish from the frame. This leads to misleading results when, for example, the number of cells in a particular frame is counted. We transform the position/shape estimation problem into a 3D shape reconstruction problem by stacking the frames of the video to form a 3D volume. In this volume, cell paths form tubes with missing segments where cells have vanished. We apply elastica inpainting to the 3D tube reconstruction problem and introduce a new 3D inpainting model to overcome difficulties with a direct generalization to 3D of 2D elastica.

Digital inpainting is the reconstruction of a missing or damaged region in a digital image. Intensity values in the missing region are approximated using information near the boundary of the region. Some applications include repair of chipped paintings, repair of rips in paper photographs, and removal of unwanted objects from photographs. In this thesis, we review 2D digital inpainting techniques, examine the application of 3D digital inpainting to cell path reconstruction, and propose a new inpainting technique inspired by the cell path reconstruction problem. Cell path reconstruction is the estimation of the shape and position of living cells in videos recorded using fluorescence microscopy. This procedure is necessary because in a particular phase of the life cycle of some cells, fluorescent light passes through the cells with an undetectable change in wavelength and they vanish from the frame. This leads to misleading results when, for example, the number of cells in a particular frame is counted. We transform the position/shape estimation problem into a 3D shape reconstruction problem by stacking the frames of the video to form a 3D volume. In this volume, cell paths form tubes with missing segments where cells have vanished. We apply elastica inpainting to the 3D tube reconstruction problem and introduce a new 3D inpainting model to overcome difficulties with a direct generalization to 3D of 2D elastica.

Thesis (M.S. in oral sciences)--University of Illinois at Chicago, 1998. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (M.S.)--University of Illinois at Chicago, 1996. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (M.S. in oral sciences)--University of Illinois at Chicago, 1998. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (M.S.)--Rochester Institute of Technology, 1994. / Typescript. Bibliography: leaves 57-58.

Thesis (M.S.)--University of Illinois at Chicago, 1996. / Includes bibliographical references.