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Image cosegmentation and denoise. / 图像共同分割和降噪 / CUHK electronic theses & dissertations collection / Tu xiang gong tong fen ge he xiang zao

我们提出了两个新的方法来解决低级别计算机视觉任务,即图像共同分割和降噪。 / 在共同分割模型上,我们发现对象对应可以为前景统计估计提供有用的信息。我们的方法可以处理极具挑战性的场景,如变形,角度的变化和显着不同的视角和尺度。此外,我们研究了一种新的能量最小化模型,可以同时处理多个图像。真实和基准数据的定性和定量实验证明该方法的有效性。 / 另一方面,噪音始终和高频图像结构是紧耦合的,从而使得减少噪音非常很难。在我们的降噪模型中,我们建议稍微使图像光学离焦,以减少图像和噪声的耦合。这使得我们能更有效地降低噪音,随后恢复失焦。我们的分析显示,这是可能的,并且用许多例子证明我们的技术,其中包括低光图像。 / We present two novel methods to tackle low level computer vision tasks,i.e., image cosegmentation and denoise . / In our cosegmentationmodel, we discover object correspondence canprovide useful information for foreground statistical estimation. Ourmethod can handle extremely challenging scenarios such as deformation, perspective changes and dramatically different viewpoints/scales. In addition, we develop a novel energy minimization model that can handlemultiple images. Experiments on real and benchmark data qualitatively and quantitatively demonstrate the effectiveness of the approach. / One the other hand, noise is always tightly coupled with high-frequencyimage structure, making noise reduction generally very difficult. In ourdenoise model, we propose slightly optically defocusing the image in orderto loosen this noise-image structure coupling. This allows us to more effectively reduce noise and subsequently restore the small defocus. Weanalytically show how this is possible, and demonstrate our technique on a number of examples that include low-light images. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Qin, Zenglu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 64-71). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese. / Abstract --- p.i / Acknowledgement --- p.ii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation and Objectives --- p.1 / Chapter 1.1.1 --- Cosegmentation --- p.1 / Chapter 1.1.2 --- Image Denoise --- p.4 / Chapter 1.2 --- Thesis Outline --- p.7 / Chapter 2 --- Background --- p.8 / Chapter 2.1 --- Cosegmentation --- p.8 / Chapter 2.2 --- Image Denoise --- p.10 / Chapter 3 --- Cosegmentation of Multiple Deformable Objects --- p.12 / Chapter 3.1 --- Related Work --- p.12 / Chapter 3.2 --- Object Corresponding Cosegmentation --- p.13 / Chapter 3.3 --- Importance Map with Object Correspondence --- p.15 / Chapter 3.3.1 --- Feature Importance Map --- p.16 / Chapter 3.3.2 --- Importance Energy E[subscript i](xp) --- p.20 / Chapter 3.4 --- Experimental Result --- p.20 / Chapter 3.4.1 --- Two-Image Cosegmentation --- p.21 / Chapter 3.4.2 --- ETHZ Toys Dataset --- p.22 / Chapter 3.4.3 --- More Results --- p.24 / Chapter 3.5 --- Summary --- p.27 / Chapter 4 --- Using Optical Defocus to Denoise --- p.28 / Chapter 4.1 --- Related Work --- p.29 / Chapter 4.2 --- Noise Analysis --- p.30 / Chapter 4.3 --- Noise Estimation with Focal Blur --- p.33 / Chapter 4.3.1 --- Noise Estimation with a Convolution Model --- p.33 / Chapter 4.3.2 --- Determining λ --- p.41 / Chapter 4.4 --- Final Deconvolution and Error Analysis --- p.43 / Chapter 4.5 --- Implementation --- p.45 / Chapter 4.6 --- Quantitative Evaluation --- p.47 / Chapter 4.7 --- More Experimental Results --- p.53 / Chapter 4.8 --- Summary --- p.56 / Chapter 5 --- Conclusion --- p.62 / Bibliography --- p.64

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_328159
Date January 2012
ContributorsQin, Zenglu., Chinese University of Hong Kong Graduate School. Division of Computer Science and Engineering.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatelectronic resource, electronic resource, remote, 1 online resource ([1], viii, 71 leaves) : ill. (chiefly col.)
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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