Accurate detection and localization of two dimensional (2D) image features (or 'key-points') is important for vision tasks such as structure from motion, stereo matching, and line labeling. 2D image features are ideal for these vision tasks because 2D image features are high in information and yet they occur sparsely in typical images. Several methods for the detection of 2D image features have already been developed. However, it is difficult to assess the performance of these methods because no one has produced an adequate definition of corners that encompasses all types of 2D luminance variations that make up 2D image features. The fact that there does not exist a consensus on the definition of 2D image features is not surprising given the confusion surrounding the definition of 1D image features. The general perception of 1D image features has been that they correspond to 'edges' in an image and so are points where the intensity gradient in some direction is a local maximum. The Sobel [68], Canny [7] and Marr-Hildreth [37] operators all use this model of 1D features, either implicitly or explicitly. However, other profiles in an image also make up valid 1D features, such as spike and roof profiles, as well as combinations of all these feature types. Spike and roof profiles can also be found by looking for points where the rate of change of the intensity gradient is locally maximal, as Canny did in defining a 'roof-detector' in much the same way he developed his 'edge-detector'. While this allows the detection of a wider variety of 1D features profiles, it comes no closer to the goal of unifying these different feature types to an encompassing definition of 1D features. The introduction of the local energy model of image features by Marrone and Owens [45] in 1987 provided a unified definition of 1D image features for the first time. They postulated that image features correspond to points in an image where there is maximal phase congruency in the frequency domain representation of the image. That is, image features correspond to points of maximal order in the phase domain of the image signal. These points of maximal phase congruency correspond to step-edge, roof, and ramp intensity profiles, and combinations thereof. They also correspond to the Mach bands perceived by humans in trapezoidal feature profiles. This thesis extends the notion of phase congruency to 2D image features. As 1D image features correspond to points of maximal 1D order in the phase domain of the image signal, this thesis contends that 2D image features correspond to maximal 2D order in this domain. These points of maximal 2D phase congruency include all the different types of 2D image features, including grey-level corners, line terminations, blobs, and a variety of junctions. Early attempts at 2D feature detection were simple 'corner detectors' based on a model of a grey-level corner in much the same way that early 1D feature detectors were based on a model of step-edges. Some recent attempts have included more complex models of 2D features, although this is basically a more complex a priori judgement of the types of luminance profiles that are to be labeled as 2D features. This thesis develops the 2D local energy feature detector based on a new, unified definition of 2D image features that marks points of locally maximum 2D order in the phase domain representation of the image as 2D image features. The performance of an implementation of 2D local energy is assessed, and compared to several existing methods of 2D feature detection. This thesis also shows that in contrast to most other methods of 2D feature detection, 2D local energy is an idempotent operator. The extension of phase congruency to 2D image features also unifies the detection of image features. 1D and 2D image features correspond to 1D and 2D order in the phase domain respresentation of the image respectively. This definition imposes a hierarchy of image features, with 2D image features being a subset of 1D image features. This ordering of image features has been implied ever since 1D features were used as candidate points for 2D feature detection by Kitchen [28] and others. Local energy enables the extraction of both 1D and 2D image features in a consistent manner; 2D image features are extracted from the 1D image features using the same operations that are used to extract 1D image features from the input image. The consistent approach to the detection of image features presented in this thesis allows the hierarchy of primitive image features to be naturally extended to higher order image features. These higher order image features can then also be extracted from higher order image data using the same hierarchical approach. This thesis shows how local energy can be naturally extended to the detection of 1D (surface) and higher order image features in 3D data sets. Results are presented for the detection of 1D image features in 3D confocal microscope images, showing superior performance to the 3D extension of the Sobel operator [74].

The most abundant clone found in ribosomal RNA clone libraries obtained from the world's oceans belongs to the SAR11 phylogenetic group of environmental marine bacteria. Imaging and counting SAR11 bacterial cells in situ has been an important research objective for the past decade. This objective has been especially challenging due to the extremely small size, and hypothetically, the low abundance of ribosomes contained by the cells. To facilitate the imaging of small dim oligotrophic bacterial cells, digital imaging technology featuring very small pixel size, high quantum yield scientific grade CCD chips was integrated with the use of multiple oligonucleotide probes on cells mounted on a non-fluorescing solid substrate. Research into the composition of bacterioplankton populations in natural marine systems follows a two-fold path. Increasing the culturability of microbes found in the natural environment is one research path. Identifying and enumerating the relative fractions of microorganisms in situ by culture-independent methods is another. The accumulation and systematic comparison of ribosomal RNA clones from the marine environment has resulted in a philosophical shift in marine microbiology away from dependence upon cultured strains and toward investigations of in situ molecular signals. The design and use of oligonucleotide DNA probes targeting rRNA targets has matured along with the growth in size and complexity of the public sequence databases. Hybridizing a fluorescently labeled oligonucleotide probe to an rRNA target inside an intact cell provides both phylogenetic and morphological information (a technique called Fluorescence in situ Hybridization (FISH)). To facilitate the imaging of small, dim oligotrophic bacterial cells, digital imaging technology featuring very small pixel size, high quantum yield, scientific grade CCD chips is integrated with the use of multiple oligonucleotide probes on cells mounted on a non-fluorescing solid substrate. This research develops the protocols necessary to acquire and analyze digital images of marine bacterial cells. Experiments were conducted with Bermuda Atlantic Time Series (BATS) environmental samples obtained during cruise BV21 (1998) and B138 (2000). The behavior of the SAR11⁴*Cy3 probe set when hybridized to bacterial cells from these samples was investigated to determine the optimal hybridization reaction conditions. The challenges of bacterial cell counting after cell transfer from PCTE membrane to treated microslides were addressed. Experiments with aged Oregon Coast seawater were performed to investigate the protocol used to transfer cells from membrane to microslides, and examined the distribution of cells and the statistics of counting cells using traditional epifluorescence microscopy and image analysis techniques. / Graduation date: 2002

An extremely important area that has enabled or will enable many of the digital video services and applications such as VideoCD, DVD, DVC, HDTV, video conferencing, and DSS is digital video compression. The great success of digital video compression is mainly because of two factors. The state of the art in very large scale integrated circuit (VLSI) and a considerable body of knowledge accumulated over the last several decades in applying video compression algorithms such as discrete cosine transform (DCT), motion estimation (ME), motion compensation (MC) and entropy coding techniques. The MPEG (Moving Pictures Expert Group) standard reflects the second factor. In this thesis, MPEG standards are discussed thoroughly and interpreted, and a VLSI chip implementation (CMOS 0.35�� technology and 3 layer metal) of a variable length decoder (VLD) for MPEG applications is developed. The VLD developed here achieves high performance by using a parallel and pipeline architecture. Furthermore, MPEG bitstream patterns are carefully analyzed in order to drastically improve VLD memory efficiency. Finally, a special clock scheme is applied to reduce the chip's power consumption. / Graduation date: 1998

Machine Vision has been extensively applied in industry. This thesis project, which originated with a local food processor, applies a vision system to inspection of packages for cosmetric errors. The basic elements and theory of the machine vision system are introduced, and some image processing techniques, such as histogram analysis, thresholding, and SRI algorithm, are utilized in this thesis. Computer programs written in C and Pascal are described. Hardware setup and computer interface, such as RS-232 serial interface, parallel digital I/O interface, conveyor control, and incremental shaft encoder, are described. Test results are presented and discussed. / Graduation date: 1991

Graduation date: 1991

　　Image-based rendering (IBR) is an emerging technology for rendering photo-realistic views of scenes from a collection of densely sampled images or videos. It provides a framework for developing revolutionary virtual reality and immersive viewing systems. There has been considerable progress recently in the capturing, storage and transmission of image-based representations. This thesis proposes two image-based rendering (IBR) systems for improving the viewing freedom and environmental modeling capability of conventional static IBR systems. The first system consists of a circular array with 13 still cameras (Canon 550D) for capturing ancient Chinese artifacts at high resolution. The second one is constructed by mounting a linear array of 8 video cameras (Sony HDR-TGIE) on an electrically controllable wheel chair with its motion being controllable manually or remotely through wireless local area network (LAN) by means of additional hardware circuitry. 　　Both systems support object-based rendering and 3D reconstruction capability and consist of two main components. 1) A novel view synthesis algorithm using a new segmentation and mutual information (MI)-based algorithm for dense depth map estimation, which relies on segmentation, local polynomial regression (LPR)-based depth map smoothing and MI-based matching algorithm to iteratively estimate the depth map. The method is very flexible and both semi-automatic and automatic segmentation methods can be employed. They rank fourth and sixth, respectively, in the Middlebury comparison of existing depth estimation methods. This allows high quality renderings of outdoor and indoor scenes with improved mobility/freedom to be obtained. This algorithm can also be extended to object tracking. Experimental results also show that the proposed MI-based algorithms are applicable to robust registration in noisy dynamic ultrasound images. 2) A new 3D reconstruction algorithm which utilizes sequential-structure-from-motion (S-SFM) technique and the dense depth maps estimated previously. It relies on a new iterative point cloud refinement algorithm based on Kalman filter (KF) for outlier removal and the segmentation-MI-based algorithm to further refine the correspondences and the projection matrices. The mobility of our system allows us to recover more conveniently 3D model of static objects from the improved point cloud using a new robust radial basis function (RBF)-based modeling algorithm to further suppress possible outliers and generate smooth 3D meshes of objects. Moreover, a new rendering technique named view dependent texture mapping is used to enhance the final rendering effect. Experimental results show that the proposed 3D reconstruction algorithm significantly reduces the adverse effect of the outliers and produces high quality renderings using view dependent texture mapping and the model reconstructed. 　　Overall, this study provides a framework for designing IBR systems with improved viewing freedom and ability to cope with moving and static objects in indoor and outdoor environment. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

Computational imaging is an emerging field. Its rapid development has drawn tremendous attention from both research and commercial points of view. Unlike traditional imaging, which separately considers the optical imaging and computational processing, computational imaging combines the power of the optical elements and signal processing techniques to achieve augmented capabilities. Previous work on various aspects of computational imaging has shown the powerful abilities that computations can bring into the imaging systems. However, the research is still in an early stage. Some drawbacks need to be conquered. For example, in compressed sensing (CS) related systems, the reconstruction quality cannot be satisfactory due to the ill-posed nature of the problem. Likely, in computational photography, the systems share a major defect. That is, as four-dimensional radiance information is recorded by a regular two-dimensional sensor, an unavoidable sacrifice of the spatial resolution has to be made to resolve angular differences. This eventually causes the low spatial resolution output. To meet these challenges, more efforts have to be made in both imaging part and computational part. In this dissertation, we concentrate ourselves on a more specific form of computational imaging, i.e., mask-based coded imaging systems. In particular, the first part of the dissertation focuses on a mask-based terahertz (THz) CS imaging system. There we focus on the computational part and explore the reconstruction algorithms that can estimate the underlying scene as accurately as possible. After that, we discuss the lightfield photography and show that by combining the system modification and proper postprocessing algorithms, we can achieve a high-resolution lightfield. The corresponding simulation demonstrates the performance of our methods. / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

The present research study investigated the perceived credibility of television news in relationship to the acquisition of knowledge of digital video compositing techniques. An experiment was carried out to verify if acquiring knowledge of digital video post-production techniques affected the perceived credibility of television news. Instrumentation for the experiment included a video stimulus produced with a readily available digital video compositing software package as well as an online post-test questionnaire. A scale for perceived credibility of television news was constructed based on a frequently used operationalization of the concept of credibility. Findings showed that after subjects acquired knowledge of digital video post production techniques, their perception of television news credibility was less than subjects who did not acquire knowledge of digital video post production techniques. Also, the amount of education a subject possessed played a significant role in how he or she perceived the credibility of television news. Frequency of television news consumption, familiarity with digital imaging software tools, and academic background were also examined in relationship to perceived credibility of television news. Implications are explained for improving media literacy education, protecting television news credibility, and designing media effects experiments.

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published_or_final_version / abstract / Mathematics / Master / Master of Philosophy