Multi-exposure electric power monitoring image fusion method without ghosting based on exposure fusion framework and color dissimilarity feature
To solve the ghosting artifacts problem in dynamic scene multi-scale exposure fusion, an improved multi-exposure fusion method has been proposed without ghosting based on the exposure fusion framework and the color dissimilarity feature of this study. This fusion method can be further applied to pow...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-01-01
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| Series: | Frontiers in Neurorobotics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fnbot.2022.1105385/full |
| _version_ | 1797956361038856192 |
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| author | Sichao Chen Zhenfei Li Dilong Shen Yunzhu An Jian Yang Bin Lv Guohua Zhou |
| author_facet | Sichao Chen Zhenfei Li Dilong Shen Yunzhu An Jian Yang Bin Lv Guohua Zhou |
| author_sort | Sichao Chen |
| collection | DOAJ |
| description | To solve the ghosting artifacts problem in dynamic scene multi-scale exposure fusion, an improved multi-exposure fusion method has been proposed without ghosting based on the exposure fusion framework and the color dissimilarity feature of this study. This fusion method can be further applied to power system monitoring and unmanned aerial vehicle monitoring. In this study, first, an improved exposure fusion framework based on the camera response model was applied to preprocess the input image sequence. Second, the initial weight map was estimated by multiplying four weight items. In removing the ghosting weight term, an improved color dissimilarity feature was used to detect the object motion features in dynamic scenes. Finally, the improved pyramid model as adopted to retain detailed information about the poor exposure areas. Experimental results indicated that the proposed method improves the performance of images in terms of sharpness, detail processing, and ghosting artifacts removal and is superior to the five existing multi-exposure image fusion (MEF) methods in quality evaluation. |
| first_indexed | 2024-04-10T23:47:47Z |
| format | Article |
| id | doaj.art-23641ef0f385425ca61896ebd0a38601 |
| institution | Directory Open Access Journal |
| issn | 1662-5218 |
| language | English |
| last_indexed | 2024-04-10T23:47:47Z |
| publishDate | 2023-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neurorobotics |
| spelling | doaj.art-23641ef0f385425ca61896ebd0a386012023-01-10T22:24:59ZengFrontiers Media S.A.Frontiers in Neurorobotics1662-52182023-01-011610.3389/fnbot.2022.11053851105385Multi-exposure electric power monitoring image fusion method without ghosting based on exposure fusion framework and color dissimilarity featureSichao Chen0Zhenfei Li1Dilong Shen2Yunzhu An3Jian Yang4Bin Lv5Guohua Zhou6Hangzhou Xinmei Complete Electric Appliance Manufacturing Co., Ltd., Hangzhou, ChinaSchool of Electrical and Electronic Engineering, Shandong University of Technology, Zibo, ChinaHangzhou Xinmei Complete Electric Appliance Manufacturing Co., Ltd., Hangzhou, ChinaSchool of Electrical and Electronic Engineering, Shandong University of Technology, Zibo, ChinaHangzhou Xinmei Complete Electric Appliance Manufacturing Co., Ltd., Hangzhou, ChinaHangzhou Xinmei Complete Electric Appliance Manufacturing Co., Ltd., Hangzhou, ChinaHangzhou Xinmei Complete Electric Appliance Manufacturing Co., Ltd., Hangzhou, ChinaTo solve the ghosting artifacts problem in dynamic scene multi-scale exposure fusion, an improved multi-exposure fusion method has been proposed without ghosting based on the exposure fusion framework and the color dissimilarity feature of this study. This fusion method can be further applied to power system monitoring and unmanned aerial vehicle monitoring. In this study, first, an improved exposure fusion framework based on the camera response model was applied to preprocess the input image sequence. Second, the initial weight map was estimated by multiplying four weight items. In removing the ghosting weight term, an improved color dissimilarity feature was used to detect the object motion features in dynamic scenes. Finally, the improved pyramid model as adopted to retain detailed information about the poor exposure areas. Experimental results indicated that the proposed method improves the performance of images in terms of sharpness, detail processing, and ghosting artifacts removal and is superior to the five existing multi-exposure image fusion (MEF) methods in quality evaluation.https://www.frontiersin.org/articles/10.3389/fnbot.2022.1105385/fullghosting artifactselectric power monitoringcamera response modelcolor dissimilarity featurepyramidmulti-exposure image fusion |
| spellingShingle | Sichao Chen Zhenfei Li Dilong Shen Yunzhu An Jian Yang Bin Lv Guohua Zhou Multi-exposure electric power monitoring image fusion method without ghosting based on exposure fusion framework and color dissimilarity feature Frontiers in Neurorobotics ghosting artifacts electric power monitoring camera response model color dissimilarity feature pyramid multi-exposure image fusion |
| title | Multi-exposure electric power monitoring image fusion method without ghosting based on exposure fusion framework and color dissimilarity feature |
| title_full | Multi-exposure electric power monitoring image fusion method without ghosting based on exposure fusion framework and color dissimilarity feature |
| title_fullStr | Multi-exposure electric power monitoring image fusion method without ghosting based on exposure fusion framework and color dissimilarity feature |
| title_full_unstemmed | Multi-exposure electric power monitoring image fusion method without ghosting based on exposure fusion framework and color dissimilarity feature |
| title_short | Multi-exposure electric power monitoring image fusion method without ghosting based on exposure fusion framework and color dissimilarity feature |
| title_sort | multi exposure electric power monitoring image fusion method without ghosting based on exposure fusion framework and color dissimilarity feature |
| topic | ghosting artifacts electric power monitoring camera response model color dissimilarity feature pyramid multi-exposure image fusion |
| url | https://www.frontiersin.org/articles/10.3389/fnbot.2022.1105385/full |
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