Thesis (M.S.)--University of Missouri-Columbia, 2003. / Typescript. Includes bibliographical references (leaf 81). Also available on the Internet.

Rapport de stage (DPSSIB) : Ecole nationale supérieure des sciences de l'information et des bibliothèques : Villeurbanne (France) : 2001. / DPSSIB = Diplôme professionnel supérieur en sciences de l'information et des bibliothèques.

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An assessment is made of the impact of a thermally bloomed atmosphere on target image quality. The steady-state phase perturbations due to blooming and the effects of the distortion on return wave-fronts are determined using a physical optics propagation code. The wavelength of the return radiation used to sense the distortions is shown to be an important consideration in the stability of the return image. The return targets images for several realistic scenarios are reconstructed based on the incoherent point spread function for each isoplanatic region of the object (target) plane. Special requirements of the back propagation algorithm are discussed with respect to "point source" geometry, tilt, tilt sensitivity, and isoplanatism criterion. The wave optics approach is shown to agree with the experimental results in regards to image blur and distortion. The stability of the reconstructed images is discussed using merit functions defining the amount of blur, distortion, and degradation in peak irradiance. The merit functions are shown to correlate well with the scenario distortion number used to define the degree of blooming induced in the forward propagation.

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With advances in imaging and communication systems, there is increased use of multi-dimensional images. Examples include multi-view image/video, hyperspectral image/video and dynamic volume imaging in CT/MRI/Ultrasound. These datasets consume even larger amounts of resources for transmission or storage compared to 2-D images. Hence, it is vital to have efficient compression methods for multi-dimensional images. In this dissertation, first, a JPEG2000 Part-2 compliant scheme is proposed for compressing multi-dimensional datasets for any dimension N>=3. Secondly, a novel view-compensated compression method is investigated for remote visualization of volumetric data. Experimental results indicate superior compression performance compared to state-of-the-art compression standards. Thirdly, a new scalable low complexity coder is designed that sacrifices some compression efficiency to get substantial gain in throughput. Potential use of the scalable low complexity coder is illustrated for two applications: Airborne video transmission and remote volume visualization.

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