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SAR minimum entropy autofocusing based on Prewitt operator

Current autofocus algorithms utilizing image criteria impose a significant computational burden. Therefore, this paper proposes a computationally efficient autofocus algorithm combined with SAR image feature points, employing the Prewitt operator to obtain the SAR image features. The range cell with...

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Detalles Bibliográficos
Autores principales: Hou, Xiaoze, Ma, Yanheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9916621/
https://www.ncbi.nlm.nih.gov/pubmed/36763598
http://dx.doi.org/10.1371/journal.pone.0276051
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author Hou, Xiaoze
Ma, Yanheng
author_facet Hou, Xiaoze
Ma, Yanheng
author_sort Hou, Xiaoze
collection PubMed
description Current autofocus algorithms utilizing image criteria impose a significant computational burden. Therefore, this paper proposes a computationally efficient autofocus algorithm combined with SAR image feature points, employing the Prewitt operator to obtain the SAR image features. The range cell with the number of feature points in the front row as the input of the autofocus method to perform motion error estimation and compensation on SAR imagery. Our method’s key feature is to optimize the selection criteria of range cells by acquiring the feature points of SAR images,reduces the number of input range cell,reduce the computational complexity of the autofocus algorithm and ultimately enhance the focusing effect of SAR images. Trials involving simulation and measured data demonstrate the effectiveness of the developed method.
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spelling pubmed-99166212023-02-11 SAR minimum entropy autofocusing based on Prewitt operator Hou, Xiaoze Ma, Yanheng PLoS One Research Article Current autofocus algorithms utilizing image criteria impose a significant computational burden. Therefore, this paper proposes a computationally efficient autofocus algorithm combined with SAR image feature points, employing the Prewitt operator to obtain the SAR image features. The range cell with the number of feature points in the front row as the input of the autofocus method to perform motion error estimation and compensation on SAR imagery. Our method’s key feature is to optimize the selection criteria of range cells by acquiring the feature points of SAR images,reduces the number of input range cell,reduce the computational complexity of the autofocus algorithm and ultimately enhance the focusing effect of SAR images. Trials involving simulation and measured data demonstrate the effectiveness of the developed method. Public Library of Science 2023-02-10 /pmc/articles/PMC9916621/ /pubmed/36763598 http://dx.doi.org/10.1371/journal.pone.0276051 Text en © 2023 Hou, Ma https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hou, Xiaoze
Ma, Yanheng
SAR minimum entropy autofocusing based on Prewitt operator
title SAR minimum entropy autofocusing based on Prewitt operator
title_full SAR minimum entropy autofocusing based on Prewitt operator
title_fullStr SAR minimum entropy autofocusing based on Prewitt operator
title_full_unstemmed SAR minimum entropy autofocusing based on Prewitt operator
title_short SAR minimum entropy autofocusing based on Prewitt operator
title_sort sar minimum entropy autofocusing based on prewitt operator
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9916621/
https://www.ncbi.nlm.nih.gov/pubmed/36763598
http://dx.doi.org/10.1371/journal.pone.0276051
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