Noise suppression of point spread functions and its influence on deconvolution of three-dimensional fluorescence microscopy image sets
Noise suppression of point spread functions and its influence on deconvolution of three-dimensional fluorescence microscopy image sets
The point spread function (PSF) is of central importance in the image restoration of three-dimensional image sets acquired by an epifluorescent microscope. Even though it is well known that an experimental PSF is typically more accurate than a theoretical one, the noise content of the experimental PSF is often an obstacle to its use in deconvolution algorithms. In this paper we apply a recently introduced noise suppression method to achieve an effective noise reduction in experimental PSFs. We show with both simulated and experimental three-dimensional image sets that a PSF that is smoothed with this method leads to a significant improvement in the performance of deconvolution algorithms, such as the regularized least-squares algorithm and the accelerated Richardson-Lucy algorithm.
Deconvolution, Fluorescent microscopy, Image restoration, Noise suppression, Point spread function
93-108
Lai, X.
d031430a-966e-4d9b-a69c-603a2debfe90
Lin, Zhiping
9b046adc-5fd0-4f26-a722-4e72598ecd9f
Ward, E. S.
b31c0877-8abe-485f-b800-244a9d3cd6cc
Ober, Raimund J.
31f4d47f-fb49-44f5-8ff6-87fc4aff3d36
January 2005
Lai, X.
d031430a-966e-4d9b-a69c-603a2debfe90
Lin, Zhiping
9b046adc-5fd0-4f26-a722-4e72598ecd9f
Ward, E. S.
b31c0877-8abe-485f-b800-244a9d3cd6cc
Ober, Raimund J.
31f4d47f-fb49-44f5-8ff6-87fc4aff3d36
Lai, X., Lin, Zhiping, Ward, E. S. and Ober, Raimund J.
(2005)
Noise suppression of point spread functions and its influence on deconvolution of three-dimensional fluorescence microscopy image sets.
Journal of Microscopy, 217 (1), .
(doi:10.1111/j.0022-2720.2005.01440.x).
Abstract
The point spread function (PSF) is of central importance in the image restoration of three-dimensional image sets acquired by an epifluorescent microscope. Even though it is well known that an experimental PSF is typically more accurate than a theoretical one, the noise content of the experimental PSF is often an obstacle to its use in deconvolution algorithms. In this paper we apply a recently introduced noise suppression method to achieve an effective noise reduction in experimental PSFs. We show with both simulated and experimental three-dimensional image sets that a PSF that is smoothed with this method leads to a significant improvement in the performance of deconvolution algorithms, such as the regularized least-squares algorithm and the accelerated Richardson-Lucy algorithm.
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More information
Accepted/In Press date: 28 October 2004
e-pub ahead of print date: 12 January 2005
Published date: January 2005
Keywords:
Deconvolution, Fluorescent microscopy, Image restoration, Noise suppression, Point spread function
Identifiers
Local EPrints ID: 424095
URI: http://eprints.soton.ac.uk/id/eprint/424095
ISSN: 0022-2720
PURE UUID: 94804638-a733-4988-9239-82d24e1e9b12
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Date deposited: 04 Oct 2018 16:30
Last modified: 16 Mar 2024 04:37
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Contributors
Author:
X. Lai
Author:
Zhiping Lin
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