The effects of support constraints on the Fourier spectra of measured data when deconvolution is employed is evaluated using a Cramér-Rao lower bound approach. It is shown that support constraints preferentially lower the variances of the higher spatial frequencies in data corrupted by Poisson and read noises.

© 2004 Optical Society of America

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