2014
DOI: 10.1109/tip.2014.2321493
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Filtering Chromatic Aberration for Wide Acceptance Angle Electrostatic Lenses

Abstract: Chromatic aberration is a major issue for imaging mainly with large acceptance angle electrostatic lenses. Its correction is necessary to take advantage of the outstanding spatial and angular resolution that these lenses provide. We propose a method to eliminate the effect of chromatic aberration on the measured images by determining the impact resulting from higher and lower kinetic energies. Based on a spectral image sequence and a matrix, which describes the transmission function of the lens, a system of li… Show more

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Cited by 3 publications
(18 citation statements)
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“…1) where a matrix (A), whose elements describes the transmission function of the lens system, acts on the vector of the ordered intensity values of the pixels of the aberrations and distortions free spectral image sequence (b) resulting the vector of the ordered intensity values of the pixels of measured and aberration distorted spectral image sequence (c) (see ref. [18]). …”
Section: Filtering the Effect Of Chromatic Aberration (Feca) For mentioning
confidence: 99%
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“…1) where a matrix (A), whose elements describes the transmission function of the lens system, acts on the vector of the ordered intensity values of the pixels of the aberrations and distortions free spectral image sequence (b) resulting the vector of the ordered intensity values of the pixels of measured and aberration distorted spectral image sequence (c) (see ref. [18]). …”
Section: Filtering the Effect Of Chromatic Aberration (Feca) For mentioning
confidence: 99%
“…This strongly nonlinear 3D deconvolution-like method can enhance not only the real-and k-space image quality, sharpness, contrast as well as the position-, angular-and spectral information contents, but it can be applied as a Software Based Imaging Energy Analyzer (SBIEA). Furthermore, it is also possible to utilize the method to correct other, different types of aberrations [18]. The present paper is the sequel of the previous article [18], which discusses the theoretical concepts and model calculations of the filtering method on a simulated image sequence.…”
Section: Introductionmentioning
confidence: 96%
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