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22 February 2013 Fuzzy logic components for iterative deconvolution systems
Brian M. Northan
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Proceedings Volume 8589, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XX; 858903 (2013) https://doi.org/10.1117/12.2002974
Event: SPIE BiOS, 2013, San Francisco, California, United States
Abstract
Deconvolution systems rely heavily on expert knowledge and would benefit from approaches that capture this expert knowledge. Fuzzy logic is an approach that is used to capture expert knowledge rules and produce outputs that range in degree. This paper describes a fuzzy-deconvolution-system that integrates traditional Richardson-Lucy deconvolution with fuzzy components. The system is intended for restoration of 3D widefield images taken under conditions of refractive index mismatch. The system uses a fuzzy rule set for calculating sample refractive index, a fuzzy median filter for inter-iteration noise reduction, and a fuzzy rule set for stopping criteria.
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Brian M. Northan "Fuzzy logic components for iterative deconvolution systems", Proc. SPIE 8589, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XX, 858903 (22 February 2013); https://doi.org/10.1117/12.2002974
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KEYWORDS
Fuzzy logic
Point spread functions
Deconvolution
Digital filtering
Statistical analysis
Image filtering
Refractive index
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