PYI: Statistical Techniques in Inverse Problems

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Bresler This research falls into four broad areas: image reconstruction, reconstruction of time-varying distributions, sensor array processing, and visualization of multiparameter data. In the area of image processing, the principal objective is to develop the theory and associated computational algorithms for superresolution image reconstruction from partial and noisy data, using statistical models. For the second area, the goal is to develop optimum signal acquisition schemes subject to physical or economic constraints, and the associated efficient reconstruction algorithms, for imaging spatial data that is time varying during the acquisition process. In the area of sensor area processing, several issues are being addressed including the design of computationally efficient algorithms for the (sub)optimal solutions of model fitting problems, wideband source location, and imaging with sensor arrays. Finally, in the last area, the goal is to address the effective fusion, display, and visualization of multi-parameter spatially-related data, such as is acquired in multispectral, or multi-modality remote sensing and diagnostic imaging.