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

published_or_final_version / Mathematics / Master / Master of Philosophy

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