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  • Topical Meeting on Signal Recovery and Synthesis with Incomplete Information and Partial Constraints
  • Technical Digest Series (Optica Publishing Group, 1983),
  • paper WA10
  • https://doi.org/10.1364/SRS.1983.WA10

Frequency Domain Optimal Inverse Convolution Filtering of Noisy Data

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Abstract

In many physical experiments, the observations r(m,n) can be represented as the convolution of a model p(m,n) with a source function s(m,n) subject to additive noise e(m,n). The ultimate goal of deconvolution schemes1,2 is to recover both the model and the source function using observations and all other available information. Let d(m,n) = p(m,n) * s(m,n). The signal-to-noise ratio α is defined as α = Σ Σ d2(m,n)/Σ Σ e2(m,n).

© 1983 Optical Society of America

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