Model for High Dynamic Range Imaging System Using Hybrid Feature Based Exposure Fusion

The luminous value is high for many natural scenes, which causes loss of information and occurs in dark images. The High Dynamic Range (HDR) technique captures the same objects or scene for multiple times in different exposure and produces the images with proper illumination. This technique is used...

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Autores principales:	Kiran Bagadi Ravi, Kumari Vatsavayi Valli, Raju KVSVN
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2020
Materias:	exposure exposure fusion high dynamic range luminance-chrominance-gradient hdr Science Q Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/52e304928b3c424291399cb5a0f8b1e7
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id	oai:doaj.org-article:52e304928b3c424291399cb5a0f8b1e7
record_format	dspace
spelling	oai:doaj.org-article:52e304928b3c424291399cb5a0f8b1e72021-12-05T14:10:50ZModel for High Dynamic Range Imaging System Using Hybrid Feature Based Exposure Fusion2191-026X10.1515/jisys-2018-0412https://doaj.org/article/52e304928b3c424291399cb5a0f8b1e72020-10-01T00:00:00Zhttps://doi.org/10.1515/jisys-2018-0412https://doaj.org/toc/2191-026XThe luminous value is high for many natural scenes, which causes loss of information and occurs in dark images. The High Dynamic Range (HDR) technique captures the same objects or scene for multiple times in different exposure and produces the images with proper illumination. This technique is used in the various applications such as medical imaging and observing the skylight, etc. HDR imaging techniques usually have the issue of lower efficiency due to capturing of multiple photos. In this paper, an efficient method is proposed for HDR imaging technique to achieve better performance and lower noise. The Luminance-Chrominance-Gradient High Dynamic Range (LCGHDR) method is proposed to obtain the proper luminous value of images. The same scenario is captured at different exposure are processed by the proposed method. Based on these feature values extracted from the different images and exposure fusion technique was developed that helps for the proper imaging. This experiment was evaluated and analyzed by comparing with the other methods, which showed the efficiency of the proposed method. This method needs only 124.594 seconds for the computation, while existing method need 139.869 seconds for the same number of images.Kiran Bagadi RaviKumari Vatsavayi ValliRaju KVSVNDe Gruyterarticleexposureexposure fusionhigh dynamic rangeluminance-chrominance-gradient hdrScienceQElectronic computers. Computer scienceQA75.5-76.95ENJournal of Intelligent Systems, Vol 30, Iss 1, Pp 346-360 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	exposure exposure fusion high dynamic range luminance-chrominance-gradient hdr Science Q Electronic computers. Computer science QA75.5-76.95
spellingShingle	exposure exposure fusion high dynamic range luminance-chrominance-gradient hdr Science Q Electronic computers. Computer science QA75.5-76.95 Kiran Bagadi Ravi Kumari Vatsavayi Valli Raju KVSVN Model for High Dynamic Range Imaging System Using Hybrid Feature Based Exposure Fusion
description	The luminous value is high for many natural scenes, which causes loss of information and occurs in dark images. The High Dynamic Range (HDR) technique captures the same objects or scene for multiple times in different exposure and produces the images with proper illumination. This technique is used in the various applications such as medical imaging and observing the skylight, etc. HDR imaging techniques usually have the issue of lower efficiency due to capturing of multiple photos. In this paper, an efficient method is proposed for HDR imaging technique to achieve better performance and lower noise. The Luminance-Chrominance-Gradient High Dynamic Range (LCGHDR) method is proposed to obtain the proper luminous value of images. The same scenario is captured at different exposure are processed by the proposed method. Based on these feature values extracted from the different images and exposure fusion technique was developed that helps for the proper imaging. This experiment was evaluated and analyzed by comparing with the other methods, which showed the efficiency of the proposed method. This method needs only 124.594 seconds for the computation, while existing method need 139.869 seconds for the same number of images.
format	article
author	Kiran Bagadi Ravi Kumari Vatsavayi Valli Raju KVSVN
author_facet	Kiran Bagadi Ravi Kumari Vatsavayi Valli Raju KVSVN
author_sort	Kiran Bagadi Ravi
title	Model for High Dynamic Range Imaging System Using Hybrid Feature Based Exposure Fusion
title_short	Model for High Dynamic Range Imaging System Using Hybrid Feature Based Exposure Fusion
title_full	Model for High Dynamic Range Imaging System Using Hybrid Feature Based Exposure Fusion
title_fullStr	Model for High Dynamic Range Imaging System Using Hybrid Feature Based Exposure Fusion
title_full_unstemmed	Model for High Dynamic Range Imaging System Using Hybrid Feature Based Exposure Fusion
title_sort	model for high dynamic range imaging system using hybrid feature based exposure fusion
publisher	De Gruyter
publishDate	2020
url	https://doaj.org/article/52e304928b3c424291399cb5a0f8b1e7
work_keys_str_mv	AT kiranbagadiravi modelforhighdynamicrangeimagingsystemusinghybridfeaturebasedexposurefusion AT kumarivatsavayivalli modelforhighdynamicrangeimagingsystemusinghybridfeaturebasedexposurefusion AT rajukvsvn modelforhighdynamicrangeimagingsystemusinghybridfeaturebasedexposurefusion
_version_	1718371666433671168

Model for High Dynamic Range Imaging System Using Hybrid Feature Based Exposure Fusion

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