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In this thesis, a low bit rate video coding system based on three-dimensional (3-D) wavelet coding is studied. In addition to the initial motivation to make use of the motion compensated wavelet based coding schemes, the other techniques that do not utilize the motion compensation in their coding procedures have also been considered on equal footing. The 3-D wavelet transform (WT) algorithm is based on the &ldquo / group of frames&rdquo / (GOF) concept. The group of eight frames are decomposed both temporally and spatially to their coarse and detail parts. The decomposition process utilizes both orthogonal and bi-orthogonal wavelet analysis filters. The transform coefficients are coded using an embedded image coding algorithm, called the &ldquo / Two-Dimensional Set Partitioning in Hierarchical Trees&rdquo / (2-D SPIHT). Due to its nature, the 2-D SPIHT is applied to the individual subband frames. In the reconstruction phase, the 2-D SPIHT decoding algorithm and the wavelet synthesis filters are employed, respectively. The Peak Signal to Noise Ratios (PSNRs) are used as a quality measure of the reconstructed frames. The investigations reveal that among several factors, the multi-level (de)composition is the dominant one effective both on the signal compression and the PSNR level. The encoded videos compressed to the ratio of 1:9 are reconstructed with the PSNR of about 30 dB in the best cases.

With technological advances digital video and imaging are becoming more and more relevant. Medical, remote-learning, surveillance, conferencing and home monitoring are just a few applications of these technologies. Along with compression, there is now a need for analysis and extraction of data. During the days of film and early digital cameras the processing and manipulation of data from such cameras was transparent to the end user. This transparency has been decreasing and the industry is moving towards `smart users' - people who will be enabled to program and manipulate their video and imaging systems. Smart cameras can currently zoom, refocus and adjust lighting by sourcing out current from the camera itself to the headlight. Such cameras are used in the industry for inspection, quality control and even counting objects in jewelry stores and museums, but could eventually allow user defined programmability. However, all this will not happen without interactive software as well as capabilities in the hardware to allow programmability. In this research, compression, expansion and detail extraction from videos in the surveillance arena are addressed. Here, a video codec is defined that can embed contextual details of a video stream depending on user defined requirements creating a video summary. This codec also carries out motion based segmentation that helps in object detection. Once an object is segmented it is matched against a database using its shape and color information. If the object is not a good match, the user can either add it to the database or consider it an anomaly. RGB vector angle information is used to generate object descriptors to match objects to a database. This descriptor implicitly incorporates the shape and color information while keeping the size of the database manageable. Color images of objects that are considered `safe' are taken from various angles and distances (with the same background as that covered by the camera is question) and their RGB vector angle based descriptors constitute the information contained in the database. This research is a first step towards building a compression and detection system for specific surveillance applications. While the user has to build and maintain a database, there are no restrictions on the size of the images, zoom and angle requirements, thus, reducing the burden on the end user in creating such a database. This also allows use of different types of cameras and doesn't need a lot of up-front planning on camera location, etc.

Thesis (Ph. D.)--University of Hawaii at Manoa, 1994. / Includes bibliographical references (leaves 199-209). / Microfiche. / xii, 209 leaves, bound ill. 29 cm

Thesis (M.S.)--University of Missouri-Columbia, 2007. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on January 3, 2008) Includes bibliographical references.

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

Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2002. / Includes bibliographical references (leaves 69-76). Also available in electronic version. Access restricted to campus users.

Thesis (M.S.)--Rochester Institute of Technology, 2007. / Typescript. Includes bibliographical references.

Thesis (M.S.)--Rochester Institute of Technology, 2008. / Typescript. Includes bibliographical references (leaves 59-60).