Simultaneous HDR image reconstruction and denoising for dynamic scenes
Resumen:
High dynamic range (HDR) images are usually generated by combining multiple photographs acquired with different exposure times. This approach, while effective, suffers from various drawbacks. The irradiance estimation is performed by combining, for each pixel, different exposure values at the same spatial position. This estimation scheme does not take advantage of the redundancy present in most images. Moreover, images must be perfectly aligned and objects must be in the exact same position in all frames in order to combine the different exposures. In this work, we propose a new HDR image generation approach that simultaneously copes with these problems and exploits image redundancy to produce a denoised result. A reference image is chosen and a patch-based approach is used to find similar pixels that are then combined for the irradiance estimation. This patch-based approach permits to obtain a denoised result and is robust to image misalignments and object motions. Results show significant improvements in terms of noise reduction over previous HDR image generation techniques, while being robust to motion and changes between the exposures.
2013 | |
Cameras Maximum likelihood estimation Noise reduction Signal to noise ratio Robustness Procesamiento de Señales |
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Inglés | |
Universidad de la República | |
COLIBRI | |
https://hdl.handle.net/20.500.12008/41773 | |
Acceso abierto | |
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
_version_ | 1807522938783531008 |
---|---|
author | Aguerrebere, Cecilia |
author2 | Delon, Julie Gousseau, Yann Musé, Pablo |
author2_role | author author author |
author_facet | Aguerrebere, Cecilia Delon, Julie Gousseau, Yann Musé, Pablo |
author_role | author |
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collection | COLIBRI |
dc.creator.none.fl_str_mv | Aguerrebere, Cecilia Delon, Julie Gousseau, Yann Musé, Pablo |
dc.date.accessioned.none.fl_str_mv | 2023-12-11T19:57:42Z |
dc.date.available.none.fl_str_mv | 2023-12-11T19:57:42Z |
dc.date.issued.es.fl_str_mv | 2013 |
dc.date.submitted.es.fl_str_mv | 20231211 |
dc.description.abstract.none.fl_txt_mv | High dynamic range (HDR) images are usually generated by combining multiple photographs acquired with different exposure times. This approach, while effective, suffers from various drawbacks. The irradiance estimation is performed by combining, for each pixel, different exposure values at the same spatial position. This estimation scheme does not take advantage of the redundancy present in most images. Moreover, images must be perfectly aligned and objects must be in the exact same position in all frames in order to combine the different exposures. In this work, we propose a new HDR image generation approach that simultaneously copes with these problems and exploits image redundancy to produce a denoised result. A reference image is chosen and a patch-based approach is used to find similar pixels that are then combined for the irradiance estimation. This patch-based approach permits to obtain a denoised result and is robust to image misalignments and object motions. Results show significant improvements in terms of noise reduction over previous HDR image generation techniques, while being robust to motion and changes between the exposures. |
dc.description.es.fl_txt_mv | Trabajo presentado a IEEE International Conference on Computational Photography (ICCP), Cambridge, MA, USA, 2013 |
dc.identifier.citation.es.fl_str_mv | Aguerrebere, C, Delon, J, Gousseau, Y, Musé, P."Simultaneous HDR image reconstruction and denoising for dynamic scenes," Publicado en Proceedings of the IEEE International Conference on Computational Photography (ICCP), Cambridge, MA, USA, 2013, pp. 1-11, doi: 10.1109/ICCPhot.2013.6528309. |
dc.identifier.uri.none.fl_str_mv | https://hdl.handle.net/20.500.12008/41773 |
dc.language.iso.none.fl_str_mv | en eng |
dc.rights.license.none.fl_str_mv | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess |
dc.source.none.fl_str_mv | reponame:COLIBRI instname:Universidad de la República instacron:Universidad de la República |
dc.subject.es.fl_str_mv | Cameras Maximum likelihood estimation Noise reduction Signal to noise ratio Robustness |
dc.subject.other.es.fl_str_mv | Procesamiento de Señales |
dc.title.none.fl_str_mv | Simultaneous HDR image reconstruction and denoising for dynamic scenes |
dc.type.es.fl_str_mv | Ponencia |
dc.type.none.fl_str_mv | info:eu-repo/semantics/conferenceObject |
dc.type.version.none.fl_str_mv | info:eu-repo/semantics/publishedVersion |
description | Trabajo presentado a IEEE International Conference on Computational Photography (ICCP), Cambridge, MA, USA, 2013 |
eu_rights_str_mv | openAccess |
format | conferenceObject |
id | COLIBRI_25b7f82e8326fed6a89e72030322e8f6 |
identifier_str_mv | Aguerrebere, C, Delon, J, Gousseau, Y, Musé, P."Simultaneous HDR image reconstruction and denoising for dynamic scenes," Publicado en Proceedings of the IEEE International Conference on Computational Photography (ICCP), Cambridge, MA, USA, 2013, pp. 1-11, doi: 10.1109/ICCPhot.2013.6528309. |
instacron_str | Universidad de la República |
institution | Universidad de la República |
instname_str | Universidad de la República |
language | eng |
language_invalid_str_mv | en |
network_acronym_str | COLIBRI |
network_name_str | COLIBRI |
oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/41773 |
publishDate | 2013 |
reponame_str | COLIBRI |
repository.mail.fl_str_mv | mabel.seroubian@seciu.edu.uy |
repository.name.fl_str_mv | COLIBRI - Universidad de la República |
repository_id_str | 4771 |
rights_invalid_str_mv | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
spelling | 2023-12-11T19:57:42Z2023-12-11T19:57:42Z201320231211Aguerrebere, C, Delon, J, Gousseau, Y, Musé, P."Simultaneous HDR image reconstruction and denoising for dynamic scenes," Publicado en Proceedings of the IEEE International Conference on Computational Photography (ICCP), Cambridge, MA, USA, 2013, pp. 1-11, doi: 10.1109/ICCPhot.2013.6528309.https://hdl.handle.net/20.500.12008/41773Trabajo presentado a IEEE International Conference on Computational Photography (ICCP), Cambridge, MA, USA, 2013High dynamic range (HDR) images are usually generated by combining multiple photographs acquired with different exposure times. This approach, while effective, suffers from various drawbacks. The irradiance estimation is performed by combining, for each pixel, different exposure values at the same spatial position. This estimation scheme does not take advantage of the redundancy present in most images. Moreover, images must be perfectly aligned and objects must be in the exact same position in all frames in order to combine the different exposures. In this work, we propose a new HDR image generation approach that simultaneously copes with these problems and exploits image redundancy to produce a denoised result. A reference image is chosen and a patch-based approach is used to find similar pixels that are then combined for the irradiance estimation. This patch-based approach permits to obtain a denoised result and is robust to image misalignments and object motions. Results show significant improvements in terms of noise reduction over previous HDR image generation techniques, while being robust to motion and changes between the exposures.Made available in DSpace on 2023-12-11T19:57:42Z (GMT). No. of bitstreams: 5 ADGM13a.pdf: 14540772 bytes, checksum: 883a3a444d0415bd7ec845f4cf8e4933 (MD5) license_text: 21936 bytes, checksum: 9833653f73f7853880c94a6fead477b1 (MD5) license_url: 49 bytes, checksum: 4afdbb8c545fd630ea7db775da747b2f (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) license.txt: 4244 bytes, checksum: 528b6a3c8c7d0c6e28129d576e989607 (MD5) Previous issue date: 2013enengLas obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad De La República. (Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)CamerasMaximum likelihood estimationNoise reductionSignal to noise ratioRobustnessProcesamiento de SeñalesSimultaneous HDR image reconstruction and denoising for dynamic scenesPonenciainfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaAguerrebere, CeciliaDelon, JulieGousseau, YannMusé, PabloProcesamiento de SeñalesTratamiento de 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- Universidad de la Repúblicafalse |
spellingShingle | Simultaneous HDR image reconstruction and denoising for dynamic scenes Aguerrebere, Cecilia Cameras Maximum likelihood estimation Noise reduction Signal to noise ratio Robustness Procesamiento de Señales |
status_str | publishedVersion |
title | Simultaneous HDR image reconstruction and denoising for dynamic scenes |
title_full | Simultaneous HDR image reconstruction and denoising for dynamic scenes |
title_fullStr | Simultaneous HDR image reconstruction and denoising for dynamic scenes |
title_full_unstemmed | Simultaneous HDR image reconstruction and denoising for dynamic scenes |
title_short | Simultaneous HDR image reconstruction and denoising for dynamic scenes |
title_sort | Simultaneous HDR image reconstruction and denoising for dynamic scenes |
topic | Cameras Maximum likelihood estimation Noise reduction Signal to noise ratio Robustness Procesamiento de Señales |
url | https://hdl.handle.net/20.500.12008/41773 |