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• W3036222095 abstract "The most important part of the common algorithms for multi-exposure image fusion (MEF) is the selection of features and metrics that are appropriate for weight map extraction. This study presents a structure-based multi-exposure image fusion by employing the phase congruency (PC) of the input image. The main idea behind PC-based analysis is that the locations of image key attributes are at points where frequency components are maximally in phase. PC detects the details of an image invariant to its contrast and also emphasises on the texture- or structure-based features. In this work, alongside intensity-based maps, the extracted PC-based map is utilised for MEF in a pyramidal manner. Several experiments conducted on the benchmark dataset including a variety of natural multi-exposed image sequences to evaluate the proposed algorithm. Quantitative evaluations in terms of MEF structural similarity index and visual quality assessments show that the proposed method achieves better performance and produces comparable fused images in comparison to other approaches." @default.
• W3036222095 created "2020-06-25" @default.
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• W3036222095 date "2020-10-05" @default.
• W3036222095 modified "2023-10-14" @default.
• W3036222095 title "Multi‐exposure image fusion via a pyramidal integration of the phase congruency of input images with the intensity‐based maps" @default.
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• W3036222095 doi "https://doi.org/10.1049/iet-ipr.2019.1147" @default.
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