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Not Available The proliferation of the World Wide Web, high resolution printers, and inexpensive imaging equipment have recently made graphics and image processing a routine part of many common activities. Commercial software abounds to manipulate digital images. This proposal deals with a particular image processing function that has been much pursued in the scientific literature over the last several decades - image restoration or superresolution. The desire to see, display, or print small details with high resolution is common. In scientific applications, improved resolution of measurements may mean the difference between solving a particular problem, or not. However, real physical equipment is limited by physical considerations that make high resolution expensive or seemingly impossible. SeeTec proposes an unconventional approach to superresolution processing. Current methods provide modest resolution improvement, even under favorable conditions. These iterative methods are sometimes slow to converge, and require significant processing resources. SeeTec will study and implement a new method based on direct extrapolation of the measured image in some suitable basis or coordinate system. We will compare Fourier, Prolate Spheroidal Wavefunctions, and Wavelet bases for developing these new algorithms. The method will attempt to reconstruct information not passed by an imaging system, based on information that is passed, and a priori information about the allowable class of solution images, or constraints such as non-negativity of passively-sensed images. If successful, this prototype software will be refined and marketed as a useful tool in the graphics and image processing arenas.