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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
71

New design and realization methods for perfect reconstruction nonuniform filter banks

Xie, Xuemei, 謝雪梅 January 2004 (has links)
published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy
72

Segmentation and reconstruction of medical images

Su, Qi, 蘇琦 January 2008 (has links)
published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy
73

Visual tracking of multiple moving objects in images based on robust estimation of the fundamental matrix

Poon, Ho-shan., 潘浩山. January 2009 (has links)
published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy
74

A region merging methodology for color and texture image segmentation

Tan, Zhigang, 譚志剛 January 2009 (has links)
published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy
75

Correlation filters for time domain signal processing

Orcutt, Edward Kerry, 1964- January 1989 (has links)
This study proposes employing new filters in various configurations for use in digital communication systems. We believe that significant improvements in such performance areas as transmission rate and synchronization may be achieved by incorporating these filters into digital communications receivers. Recently reported in the literature, these filters may offer advantages over the matched filter which allow enhancements in data rates, ISI tolerance, and synchronization. To make full use of the benefits of these filters, we introduce the concept of parallel signal transmission over a single channel. We also examine the effects of signal set selection and noise on performance.
76

Design of the ultraspherical window function and its applications

Bergen, Stuart William Abe. 10 April 2008 (has links)
No description available.
77

High-performance signal processing architectures for digital aperture array telescopes

Armstrong, Richard Paul January 2011 (has links)
An instrument with the ability to image neutral atomic hydrogen (HI) to cosmic redshift will allow the fundamental properties of the Universe to be more precisely determined; in particular the distribution, composition, and evolutionary history of its matter and energy. The Square Kilometre Array (SKA) is a radio survey telescope conceived with this aim. It will have the observational potential for much further fundamental science, including strong field tests of gravity and general relativity, revealing the origin and history of cosmological re-ionisation and magnetism, direct measures of gravitational radiation, and surveys of the unmapped Universe. And it is the advance of instrumentation that will enable it. This thesis makes three central contributions to radio instrumentation. Digital aperture arrays are a collector technology proposed for the key low- and mid- frequency ranges targeted by the SKA that have the potential to provide both the collecting area and field of view required for deep, efficient all-sky surveys of HI. The 2-Polarisations, All Digital (2-PAD) aperture array is an instrumental pathfinder for the SKA, novel in being a densely-spaced, wide-band aperture array that performs discrete signal filtering entirely digitally. The digital design of the 2-PAD radio receiver and the deployment of the aperture array and signal processing system at Jodrell Bank Radio Observatory is detailed in this thesis. The problem of element anisotropy in small arrays, the atomic unit of the SKA station array, ultimately affects beam quality. Addressing this issue, a metaheuristic digital beam-shape optimisation technique is applied to a small beamformed array, and is shown to outperform traditional analytic solutions. Digital processing for aperture arrays is challenging. A qualitative framework shows that energy, computational and communication requirements demand optimised processing architectures. A quantitative model reveals the physical limitations on architecture choice. An energy-optimised architecture, the IBM BIT integer array processor, is investigated in detail; a cycle-accurate architectural simulator and programming language are developed and used to build signal processing algorithms on the array architecture.
78

A novel fault detection and diagnosis framework for rotating machinery using advanced signal processing techniques and ensemble extreme learning machines

Wang, Xian Bo January 2018 (has links)
University of Macau / Faculty of Science and Technology. / Department of Electromechanical Engineering
79

Photo enhancement / CUHK electronic theses & dissertations collection

January 2014 (has links)
Photo enhancement is an important and practical problem in computer vision. In real-word applications, there are massive needs for photo quality enhancement. Image cropping and image color enhancement are two common operations used to improve the visual quality of photographs. By learning from human examples, we propose automatic photo enhancement method which implements these two fundamental operations. / For image cropping, we present an automatic cropping technique that accounts for the two primary considerations of people when they crop: removal of distracting content, and enhancement of overall composition. Our approach utilizes a large training set consisting of photos before and after cropping by expert photographers to learn how to evaluate these two factors in a crop. In contrast to the many methods that exist for general assessment of image quality, ours specifically examines differences between the original and cropped photo in solving for the crop parameters. To this end, several novel image features are proposed to model the changes in image content and composition when a crop is applied. The effectiveness of each feature is empirically analyzed in determining a final feature set for crop computation. Our experiments demonstrate improvements of our method over recent cropping algorithms on a broad range of images. / We also present a machine-learned ranking approach for automatically enhancing the color of a photograph. Unlike previous techniques that train on pairs of images before and after adjustment by a human user, our method takes into account the intermediate steps taken in the enhancement process, which provide detailed information on the person's color preferences. To make use of this data, we formulate the color enhancement task as a learning-to-rank problem in which ordered pairs of images are used for training, and then various color enhancements of a novel input image can be evaluated from their corresponding rank values. From the parallels between the decision tree structures we use for ranking and the decisions made by a human during the editing process, we posit that breaking a full enhancement sequence into individual steps can facilitate training. Our experiments show that this approach compares well to existing methods for automatic color enhancement. / Yan, Jianzhou. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2014. / Includes bibliographical references (leaves 105-115). / Title from PDF title page (viewed on 30, November, 2016).
80

Image-based symmetry analysis and its applications. / 圖像對稱性分析及應用 / CUHK electronic theses & dissertations collection / Tu xiang dui cheng xing fen xi ji ying yong

January 2011 (has links)
In this thesis, we primarily focus on one common type of symmetry, the translational symmetry. We first review the current state-of-the-art methods for translational symmetry detection, and discuss their benefits and drawbacks. Towards an efficient, automatic and widely applicable translational symmetry detector, we develop a novel method for automatically detecting translational symmetry patterns, and extracting the corresponding lattices from images without pre-segmentation or reconstructing the underlying 3D geometry. In particular, we employ a region-based feature and fully utilize its regional properties (shape, orientation and well-defined boundary) to propose the repeated candidates. Compared with traditional treatments, which usually rely on point-based features and group them to propose repeated candidates, our treatment is more efficient and stable to perspective projection, distortion or noise. By clustering the candidate regions and indexing the major clusters using a GPU KD-tree, the parallel lattice formation processes turn out to be very efficient and achieve a real-time rate. By using a set of spatially varying vectors with a loose neighboring constraint to represent the underlying lattice, we successfully detect most of translational symmetry patterns over arbitrary surfaces, which can be planar or curve, without or with perspective projection, and even when suffered from global and local deformations. Moreover, the parallel searching and saving scheme enables us to simultaneously detect multiple disjoint symmetry patterns from an input images. / Symmetry has been an important concept in the nature, science and art. There is an abundant of biological, chemical, and artificial structures captured in many real-world images, exhibiting various forms of symmetry. The symmetry patterns and the repetitive elements reinforce the visual importance and usually make an image more attractive. Although our humans have an excellent innate ability in recognizing symmetry and perceiving its beauty, efficient and automatic symmetry detection from images remains a unsolved challenging problem in computer vision and graphics. Without understanding the high-level semantics of symmetry, editing such images while preserving the repetitions and their relations turns out to be difficult to perform, such as image resizing, image inpainting and image replacement. / The significant improvements of our method in both efficiency and accuracy make it a useful tool from which many applications can benefit. One of them is image resizing. We demonstrate that image resizing can be achieved more effectively if we have a better understanding of the image semantics. By analyzing the translational symmetry patterns, and detecting the underlying lattices in an image, we can summarize, instead of only distorting or cropping, the image content. This opens a new space for image resizing that allows us to manipulate, not only image pixels, but also the semantic cells in the lattice. As a general image contains both symmetry & non-symmetry regions and their natures are different, we propose to resize symmetry regions by summarization and non-symmetry region by optimized warping. In addition, by smoothing the intensity of cells across the lattice, we can further maintain the seamlessness of illumination during the summarization. As the difference in resizing strategy between symmetry regions and non-symmetry region leads to discontinuity at their shared boundary, we propose a framework to minimize the artifact. Experimental results show that, with the high-level knowledge of symmetry, our method outperforms the state-of-the-art resizing techniques. / Wu, Huisi. / Advisers: Tien-Tsin Wong; Pheng-Ann Heng. / Source: Dissertation Abstracts International, Volume: 73-06, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 92-100). / 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, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

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