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Use of Additional Constraint Terms in Maximum A Posteriori Super Resolution

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Abstract

Super resolution algorithms derived by maximum a posteriori (MAP) estimation have been successfully applied to images of stars and other compact objects on dark backgrounds. One such algorithm, derived under the assumptions of positivity and Poisson statistics is [1] where the corresponding imaging equation is and ∗ denotes convolution, h(x) = imaging system point spread function (psf), f(x) = object, g(x) = image, and fn(x) = current estimate of object.

© 1992 Optical Society of America

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