1 October 1994 Error reduction in images using high-quality prior knowledge
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Optical Engineering, 33(10), (1994). doi:10.1117/12.181246
Abstract
The use of information about an image in addition to measured data has been demonstrated to provide the possibility of decreasing the noise in the measured data. A new constraint, recently proposed, is that of perfect knowledge of part of an image. These results are generalized, and the usefulness of this new constraint in decreasing noise outside the region of prior knowledge is shown to be a function of the measured data noise-correlation properties. In particular, it is shown that prior high-quality knowledge is a generalization of support constraints.
Charles L. Matson, "Error reduction in images using high-quality prior knowledge," Optical Engineering 33(10), (1 October 1994). http://dx.doi.org/10.1117/12.181246
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KEYWORDS
Denoising

Computer simulations

Signal to noise ratio

Algorithms

Binary data

Fourier transforms

Optical engineering

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