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Title: Spatial resolution, signal-to-noise and information capacity of linear imaging systems
Contributor(s): Gureyev, Timur  (author)orcid ; Nesterets, Yakov  (author); de Hoog, Frank (author)
Publication Date: 2016
Open Access: Yes
DOI: 10.1364/oe.24.017168Open Access Link
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Abstract: A simple model for image formation in linear shift-invariant systems is considered, in which both the detected signal and the noise variance are varying slowly compared to the point-spread function of the system. It is shown that within the constraints of this model, the square of the signal-to-noise ratio is always proportional to the "volume" of the spatial resolution unit. In the case of Poisson statistics, the ratio of these two quantities divided by the incident density of the imaging particles (e.g. photons) represents a dimensionless invariant of the imaging system, which was previously termed the intrinsic imaging quality. The relationship of this invariant to the notion of information capacity of communication and imaging systems, which was previously considered by Shannon, Gabor and others, is investigated. The results are then applied to a simple generic model of quantitative imaging of weakly scattering objects, leading to an estimate of the upper limit for the amount of information about the sample that can be obtained in such experiments. It is shown that this limit depends only on the total number of imaging particles incident on the sample, the average scattering coefficient, the size of the sample and the number of spatial resolution units.
Publication Type: Journal Article
Source of Publication: Optics Express, 24(15), p. 17168-17182
Publisher: Optical Society of America
Place of Publication: United States of America
ISSN: 1094-4087
Field of Research (FOR): 020504 Photonics, Optoelectronics and Optical Communications
Socio-Economic Outcome Codes: 970102 Expanding Knowledge in the Physical Sciences
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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