2008
DOI: 10.1209/0295-5075/81/44001
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Quantum limits in image processing

Abstract: We determine the limit to the maximum achievable sensitivity in the estimation of a scalar parameter from the information contained in an optical image in the presence of quantum noise. This limit, based on the Cramer-Rao bound and valid for any image processing protocol, is calculated for a shot noise limited image, for a locally squeezed light, and for a single-mode squeezed light in a well-defined "noise mode". In addition, we exhibit an image processing protocol that allows us to reach the limits in the di… Show more

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Cited by 60 publications
(67 citation statements)
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References 24 publications
(29 reference statements)
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“…Given the image data ρ(x; q), we construct, as in Refs. [28,29], a linear filter g(x) to provide an estimate for q:…”
Section: Poissonian Counting Statisticsmentioning
confidence: 99%
See 1 more Smart Citation
“…Given the image data ρ(x; q), we construct, as in Refs. [28,29], a linear filter g(x) to provide an estimate for q:…”
Section: Poissonian Counting Statisticsmentioning
confidence: 99%
“…This optimization problem has the following solution, as pointed out in Ref. [29] for a coherent state of light populating a single spatial mode:…”
Section: Poissonian Counting Statisticsmentioning
confidence: 99%
“…This has been first experimentally demonstrated for measurements in which the information about the parameter θ is carried by the total intensity [3] or by the phase [4] of a light beam. Later situations were considered where the parameter θ does not change the total intensity of the light but modifies the details of the repartition of light in the transverse plane [5] (for example to estimate a very small lateral displacement of a beam [6]). As the energy of the squeezed state increases with the squeezing factor, the ultimate limit with squeezed state for a fixed total energy scales as 1/N 3/4 .…”
mentioning
confidence: 99%
“…The second example assumes that the mean intensity is large enough so as to invoke the Central Limit Theorem [19], but it considers the improvement that can be achieved when using nonclassical, squeezed light (see, e.g., [30][31][32]). Under these circumstances, squeezed light produces Gaussian noise statistics with variance s 2 n 0 , where s 2 < 1 is the squeezing factor [33,34]. The number of absorbed photons on a single detector is thus parameterized by the PDFs:…”
Section: A Noise Models and Fisher Informationmentioning
confidence: 99%