Abstract

We investigate how prior knowledge of the object in the form of linear equality constraints influences the inverse problem of incoherently illuminated object reconstruction by using an elimination method in the context of least squares by regularized singular-value decomposition. Some representative numerical calculations that use noisy images were carried out to illustrate the analysis. When compared with the corresponding unconstrained inversion it appears that the linear constrained inverse does not seem to be any better when viewed in the global sense.

© 1999 Optical Society of America

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