Denoising time-resolved microscopy image sequences with singular value thresholding

Time-resolved imaging in microscopy is important for the direct observation of a range of dynamic processes in both the physical and life sciences. However, the image sequences are often corrupted by noise, either as a result of high frame rates or a need to limit the radiation dose received by the...

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Hauptverfasser: Furnival, Thomas, Leary, Rowan, Midgley, Paul
Weitere Verfasser: Plants and Ecosystems (PLECO) - Ecology in a time of change
Sprache:Englisch
Veröffentlicht: Elsevier 2019
Online-Zugang:https://demo7.dspace.org/handle/123456789/472
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author Furnival, Thomas
Leary, Rowan
Midgley, Paul
author2 Plants and Ecosystems (PLECO) - Ecology in a time of change
author_browse Furnival, Thomas
Leary, Rowan
Midgley, Paul
Plants and Ecosystems (PLECO) - Ecology in a time of change
author_facet Plants and Ecosystems (PLECO) - Ecology in a time of change
Furnival, Thomas
Leary, Rowan
Midgley, Paul
author_sort Furnival, Thomas
collection DSpace
description Time-resolved imaging in microscopy is important for the direct observation of a range of dynamic processes in both the physical and life sciences. However, the image sequences are often corrupted by noise, either as a result of high frame rates or a need to limit the radiation dose received by the sample. Here we exploit both spatial and temporal correlations using low-rank matrix recovery methods to denoise microscopy image sequences. We also make use of an unbiased risk estimator to address the issue of how much thresholding to apply in a robust and automated manner. The performance of the technique is demonstrated using simulated image sequences, as well as experimental scanning transmission electron microscopy data, where surface adatom motion and nanoparticle structural dynamics are recovered at rates of up to 32 frames per second.
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publishDate 2019
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spelling oai:localhost:123456789-4722021-04-07T16:30:12Z Denoising time-resolved microscopy image sequences with singular value thresholding Furnival, Thomas Leary, Rowan Midgley, Paul Plants and Ecosystems (PLECO) - Ecology in a time of change Time-resolved imaging in microscopy is important for the direct observation of a range of dynamic processes in both the physical and life sciences. However, the image sequences are often corrupted by noise, either as a result of high frame rates or a need to limit the radiation dose received by the sample. Here we exploit both spatial and temporal correlations using low-rank matrix recovery methods to denoise microscopy image sequences. We also make use of an unbiased risk estimator to address the issue of how much thresholding to apply in a robust and automated manner. The performance of the technique is demonstrated using simulated image sequences, as well as experimental scanning transmission electron microscopy data, where surface adatom motion and nanoparticle structural dynamics are recovered at rates of up to 32 frames per second. 2019-04-26T08:57:25Z 2019-04-26T08:57:25Z 10/05/16 https://demo7.dspace.org/handle/123456789/472 en Elsevier
spellingShingle Furnival, Thomas
Leary, Rowan
Midgley, Paul
Denoising time-resolved microscopy image sequences with singular value thresholding
title Denoising time-resolved microscopy image sequences with singular value thresholding
title_full Denoising time-resolved microscopy image sequences with singular value thresholding
title_fullStr Denoising time-resolved microscopy image sequences with singular value thresholding
title_full_unstemmed Denoising time-resolved microscopy image sequences with singular value thresholding
title_short Denoising time-resolved microscopy image sequences with singular value thresholding
title_sort denoising time resolved microscopy image sequences with singular value thresholding
url https://demo7.dspace.org/handle/123456789/472
work_keys_str_mv AT furnivalthomas denoisingtimeresolvedmicroscopyimagesequenceswithsingularvaluethresholding
AT learyrowan denoisingtimeresolvedmicroscopyimagesequenceswithsingularvaluethresholding
AT midgleypaul denoisingtimeresolvedmicroscopyimagesequenceswithsingularvaluethresholding