Multi-exposure microscopic image fusion-based detail enhancement algorithm
[EN] Traditional microscope imaging techniques are unable to retrieve the complete dynamic range of a diatom species with complex silica-based cell walls and multi-scale patterns. In order to extract details from the diatom, multi-exposure images are captured at variable exposure settings using micr...
| Autores: | , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad Rey Juan Carlos |
| Repositorio: | BULERIA. Repositorio Institucional de la Universidad de León |
| OAI Identifier: | oai:buleria.unileon.es:10612/19366 |
| Acceso en línea: | https://www.sciencedirect.com/science/article/pii/S0304399122000353 https://hdl.handle.net/10612/19366 |
| Access Level: | acceso abierto |
| Palabra clave: | Ecología. Medio ambiente Histogram equalization Image fusion Image decomposition Entropy 2417.07 Algología (Ficología) 2203.04 Microscopia Electrónica 2417.20 Taxonomía Vegetal 3308.11 Control de la Contaminación del Agua |
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Multi-exposure microscopic image fusion-based detail enhancement algorithmSingh, HarbinderCristóbal Pérez, GabrielBueno García, María GloriaBlanco Lanza, SaúlSingh, SimrandeepHrisheekesha, Periapattana NagarajMittal, NitinEcología. Medio ambienteHistogram equalizationImage fusionImage decompositionEntropy2417.07 Algología (Ficología)2203.04 Microscopia Electrónica2417.20 Taxonomía Vegetal3308.11 Control de la Contaminación del Agua[EN] Traditional microscope imaging techniques are unable to retrieve the complete dynamic range of a diatom species with complex silica-based cell walls and multi-scale patterns. In order to extract details from the diatom, multi-exposure images are captured at variable exposure settings using microscopy techniques. A recent innovation shows that image fusion overcomes the limitations of standard digital cameras to capture details from high dynamic range scene or specimen photographed using microscopy imaging techniques. In this paper, we present a cell-region sensitive exposure fusion (CS-EF) approach to produce well-exposed fused images that can be presented directly on conventional display devices. The ambition is to preserve details in poorly and brightly illuminated regions of 3-D transparent diatom shells. The aforesaid objective is achieved by taking into account local information measures, which select well-exposed regions across input exposures. In addition, a modified histogram equalization is introduced to improve uniformity of input multi-exposure image prior to fusion. Quantitative and qualitative assessment of proposed fusion results reveal better performance than several state-of-the-art algorithms that substantiate the method’s validitySIThis work was supported in part by the Spanish Government, Spain under the AQUALITAS-retos project (Ref.CTM2014-51907-C2-2-R-MINECO) and by Junta de Comunidades de Castilla-La Mancha, Spain under project HIPERDEEP (Ref. SBPLY/19/180501/000273). The funding agencies had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscriptElsevierEcologiaFacultad de Ciencias Biologicas y Ambientales2022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://www.sciencedirect.com/science/article/pii/S0304399122000353https://hdl.handle.net/10612/19366reponame:BULERIA. Repositorio Institucional de la Universidad de Leóninstname:Universidad Rey Juan CarlosInglésinfo:eu-repo/grantAgreement/MINECO/Programa Estatal de I+D+I Orientada a los Retos de la Sociedad/CTM2014-51907-C2-Rnfo:eu-repo/grantAgreement/Junta de comunidades de Castilla-La Mancha//SBPLY/19/180501/000273/ES/Definiendo la huella hiperespectral del cáncer de mama mediante técnicas de aprendizaje profundo aplicadas a imágenes microscópicas/HYPERDEEPhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:buleria.unileon.es:10612/193662026-06-24T12:43:27Z |
| dc.title.none.fl_str_mv |
Multi-exposure microscopic image fusion-based detail enhancement algorithm |
| title |
Multi-exposure microscopic image fusion-based detail enhancement algorithm |
| spellingShingle |
Multi-exposure microscopic image fusion-based detail enhancement algorithm Singh, Harbinder Ecología. Medio ambiente Histogram equalization Image fusion Image decomposition Entropy 2417.07 Algología (Ficología) 2203.04 Microscopia Electrónica 2417.20 Taxonomía Vegetal 3308.11 Control de la Contaminación del Agua |
| title_short |
Multi-exposure microscopic image fusion-based detail enhancement algorithm |
| title_full |
Multi-exposure microscopic image fusion-based detail enhancement algorithm |
| title_fullStr |
Multi-exposure microscopic image fusion-based detail enhancement algorithm |
| title_full_unstemmed |
Multi-exposure microscopic image fusion-based detail enhancement algorithm |
| title_sort |
Multi-exposure microscopic image fusion-based detail enhancement algorithm |
| dc.creator.none.fl_str_mv |
Singh, Harbinder Cristóbal Pérez, Gabriel Bueno García, María Gloria Blanco Lanza, Saúl Singh, Simrandeep Hrisheekesha, Periapattana Nagaraj Mittal, Nitin |
| author |
Singh, Harbinder |
| author_facet |
Singh, Harbinder Cristóbal Pérez, Gabriel Bueno García, María Gloria Blanco Lanza, Saúl Singh, Simrandeep Hrisheekesha, Periapattana Nagaraj Mittal, Nitin |
| author_role |
author |
| author2 |
Cristóbal Pérez, Gabriel Bueno García, María Gloria Blanco Lanza, Saúl Singh, Simrandeep Hrisheekesha, Periapattana Nagaraj Mittal, Nitin |
| author2_role |
author author author author author author |
| dc.contributor.none.fl_str_mv |
Ecologia Facultad de Ciencias Biologicas y Ambientales |
| dc.subject.none.fl_str_mv |
Ecología. Medio ambiente Histogram equalization Image fusion Image decomposition Entropy 2417.07 Algología (Ficología) 2203.04 Microscopia Electrónica 2417.20 Taxonomía Vegetal 3308.11 Control de la Contaminación del Agua |
| topic |
Ecología. Medio ambiente Histogram equalization Image fusion Image decomposition Entropy 2417.07 Algología (Ficología) 2203.04 Microscopia Electrónica 2417.20 Taxonomía Vegetal 3308.11 Control de la Contaminación del Agua |
| description |
[EN] Traditional microscope imaging techniques are unable to retrieve the complete dynamic range of a diatom species with complex silica-based cell walls and multi-scale patterns. In order to extract details from the diatom, multi-exposure images are captured at variable exposure settings using microscopy techniques. A recent innovation shows that image fusion overcomes the limitations of standard digital cameras to capture details from high dynamic range scene or specimen photographed using microscopy imaging techniques. In this paper, we present a cell-region sensitive exposure fusion (CS-EF) approach to produce well-exposed fused images that can be presented directly on conventional display devices. The ambition is to preserve details in poorly and brightly illuminated regions of 3-D transparent diatom shells. The aforesaid objective is achieved by taking into account local information measures, which select well-exposed regions across input exposures. In addition, a modified histogram equalization is introduced to improve uniformity of input multi-exposure image prior to fusion. Quantitative and qualitative assessment of proposed fusion results reveal better performance than several state-of-the-art algorithms that substantiate the method’s validity |
| publishDate |
2022 |
| dc.date.none.fl_str_mv |
2022 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
https://www.sciencedirect.com/science/article/pii/S0304399122000353 https://hdl.handle.net/10612/19366 |
| url |
https://www.sciencedirect.com/science/article/pii/S0304399122000353 https://hdl.handle.net/10612/19366 |
| dc.language.none.fl_str_mv |
Inglés |
| language_invalid_str_mv |
Inglés |
| dc.relation.none.fl_str_mv |
info:eu-repo/grantAgreement/MINECO/Programa Estatal de I+D+I Orientada a los Retos de la Sociedad/CTM2014-51907-C2-R nfo:eu-repo/grantAgreement/Junta de comunidades de Castilla-La Mancha//SBPLY/19/180501/000273/ES/Definiendo la huella hiperespectral del cáncer de mama mediante técnicas de aprendizaje profundo aplicadas a imágenes microscópicas/HYPERDEEP |
| dc.rights.none.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| eu_rights_str_mv |
openAccess |
| dc.publisher.none.fl_str_mv |
Elsevier |
| publisher.none.fl_str_mv |
Elsevier |
| dc.source.none.fl_str_mv |
reponame:BULERIA. Repositorio Institucional de la Universidad de León instname:Universidad Rey Juan Carlos |
| instname_str |
Universidad Rey Juan Carlos |
| reponame_str |
BULERIA. Repositorio Institucional de la Universidad de León |
| collection |
BULERIA. Repositorio Institucional de la Universidad de León |
| repository.name.fl_str_mv |
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| repository.mail.fl_str_mv |
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1869405757049405440 |
| score |
15,301629 |