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231224s2017 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2017.2651366
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|a eng
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|a Li, Zhengguo
|e verfasserin
|4 aut
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|a Detail-Enhanced Multi-Scale Exposure Fusion
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|c 2017
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|a Text
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|a ƒaComputermedien
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|a Date Completed 30.07.2018
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|a Date Revised 30.07.2018
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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| 520 |
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|a Multi-scale exposure fusion is an effective image enhancement technique for a high dynamic range (HDR) scene. In this paper, a new multi-scale exposure fusion algorithm is proposed to merge differently exposed low dynamic range (LDR) images by using the weighted guided image filter to smooth the Gaussian pyramids of weight maps for all the LDR images. Details in the brightest and darkest regions of the HDR scene are preserved better by the proposed algorithm without relative brightness change in the fused image. In addition, a new weighted structure tensor is introduced to the differently exposed images and it is adopted to design a detail extraction component for the proposed fusion algorithm, such that users are allowed to manipulate fine details in the enhanced image according to their preference. The proposed multi-scale exposure fusion algorithm is also applied to design a simple single image brightening algorithm for both low-light imaging and back-light imaging
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|a Journal Article
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|a Wei, Zhe
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|a Wen, Changyun
|e verfasserin
|4 aut
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| 700 |
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|a Zheng, Jinghong
|e verfasserin
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 26(2017), 3 vom: 07. März, Seite 1243-1252
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|g month:03
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