Thesis (M.S.)--University of Missouri-Columbia, 2004. / Typescript. Includes bibliographical references (leaves 90-92). Also available on the Internet.

Thesis (M.S.)--University of Missouri-Columbia, 2004. / Typescript. Includes bibliographical references (leaves 90-92). Also available on the Internet.

Thesis (M.S.)--University of North Texas, May, 2007. / Title from title page display. Includes bibliographical references.

No description available.

As video applications become more diverse, video must be adapted in different ways to meet the requirements of different applications when there are insufficient resources. In this dissertation, we address two sorts of requirements that cannot be addressed by existing video adaptation technologies: (i) accommodating large variations in resolution and (ii) collecting video effectively in a multi-hop sensor network. In addition, we also address requirements for implementing video adaptation in a sensor network. Accommodating large variation in resolution is required by the existence of display devices with widely disparate screen sizes. Existing resolution adaptation technologies usually aim at adapting video between two resolutions. We examine the limitations of these technologies that prevent them from supporting a large number of resolutions efficiently. We propose several hybrid schemes and study their performance. Among these hybrid schemes, Bonneville, a framework that combines multiple encodings with limited scalability, can make good trade-offs when organizing compressed video to support a wide range of resolutions. Video collection in a sensor network requires adapting video in a multi-hop storeand- forward network and with multiple video sources. This task cannot be supported effectively by existing adaptation technologies, which are designed for real-time streaming applications from a single source over IP-style end-to-end connections. We propose to adapt video in the network instead of at the network edge. We also propose a framework, Steens, to compose adaptation mechanisms on multiple nodes. We design two signaling protocols in Steens to coordinate multiple nodes. Our simulations show that in-network adaptation can use buffer space on intermediate nodes for adaptation and achieve better video quality than conventional network-edge adaptation. Our simulations also show that explicit collaboration among multiple nodes through signaling can improve video quality, waste less bandwidth, and maintain bandwidth-sharing fairness. The implementation of video adaptation in a sensor network requires system support for programmability, retaskability, and high performance. We propose Cascades, a component-based framework, to provide the required support. A prototype implementation of Steens in this framework shows that the performance overhead is less than 5% compared to a hard-coded C implementation.

No description available.

No description available.

In the immediate future, multimedia product distribution through the Internet will become main stream. However, it can also have the side effect of unauthorized duplication and distribution of multimedia products. That effect could be a critical challenge to the legal ownership of copyright and intellectual property. Many schemes have been proposed to address these issues; one is digital watermarking which is appropriate for image and video copyright protection. Videos distributed via the Internet must be processed by compression for low bit rate, due to bandwidth limitations. The most widely adapted video compression standard is MPEG-4. Discrete cosine transform (DCT) domain watermarking is a secure algorithm which could survive video compression procedures and, most importantly, attacks attempting to remove the watermark, with a visibly degraded video quality result after the watermark attacks. For a commercial broadcasting video system, real-time response is always required. For this reason, an FPGA hardware implementation is studied in this work. This thesis deals with video compression, watermarking algorithms and their hardware implementation with FPGAs. A prototyping VLSI architecture will implement video compression and watermarking algorithms with the FPGA. The prototype is evaluated with video and watermarking quality metrics. Finally, it is seen that the video qualities of the watermarking at the uncompressed vs. the compressed domain are only 1dB of PSNR lower. However, the cost of compressed domain watermarking is the complexity of drift compensation for canceling the drifting effect.

Streaming multimedia quality is impacted by two main factors: capacity constraint and packet loss. To match the capacity constraint while preserving real-time playout, media scaling can be used to discard the encoded multimedia content that has the least impact on perceived video quality. To limit the impact of lost packets, repair techniques, e.g. forward error correction (FEC), can be used to repair frames damaged by packet loss. However, adding data to facilitate repair requires further reduction of the original multimedia data, making the decision of how much repair data to use of critical importance. Assuming a limited network capacity and the availability of an estimate of the current packet loss rate along a flow path, selecting the best distribution of FEC packets for video frames with inherent interframe encoding dependencies can be cast as a constraint optimization problem that attempts to optimize the quality of the video stream. This thesis presents an Adjusting Repair and Media scaling with Operations Research (ARMOR) system. An analytical model is derived for streaming video with FEC and media scaling. Given parameters to represent network loss as well as video frame types and sizes, if the number of FEC packets per video frame type and media scaling pattern is specified, the model can estimate the video quality at the receiver side. The model is then used in an operations research algorithm to adjust the FEC strength and media scaling level to yield the best quality under the capacity constraint. Four different combinations of FEC type and media scaling method are studied: Media Independent FEC with Temporal Scaling (MITS), Media Independent FEC with Quality Scaling (MIQS), Media Independent FEC with Temporal and Quality Scaling (MITQS), and Media Dependent FEC with Quality Scaling (MDQS). The analytical experiments show: 1) adjusting FEC always achieves a higher video quality than streaming video without FEC or with a fixed amount of FEC; 2) Quality Scaling usually works better than Temporal Scaling; and 3) Media Dependent FEC (MDFEC) is typically less effective than Media Independent FEC (MIFEC). A user study is presented with results from 74 participants analysis shows that the ARMOR model can accurately estimate users¡¯perceptual quality. Well-designed simulations and a realistic system implementation suggests the ARMOR system can practically improve the quality of streaming video.

Abstract not available