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dc.contributor.authorChen, Wen_NZ
dc.contributor.authorJia, Zen_NZ
dc.contributor.authorYang, Jen_NZ
dc.contributor.authorKasabov, NKen_NZ
dc.date.accessioned2022-02-08T02:31:32Z
dc.date.available2022-02-08T02:31:32Z
dc.date.copyright2022-01-01en_NZ
dc.identifier.citationRemote Sensing. 2022, 14, 233. https://doi.org/ 10.3390/rs14010233
dc.identifier.issn2072-4292en_NZ
dc.identifier.urihttp://hdl.handle.net/10292/14888
dc.description.abstractCompared with single-band remote sensing images, multispectral images can obtain information on the same target in different bands. By combining the characteristics of each band, we can obtain clearer enhanced images; therefore, we propose a multispectral image enhancement method based on the improved dark channel prior (IDCP) and bilateral fractional differential (BFD) model to make full use of the multiband information. First, the original multispectral image is inverted to meet the prior conditions of dark channel theory. Second, according to the characteristics of multiple bands, the dark channel algorithm is improved. The RGB channels are extended to multiple channels, and the spatial domain fractional differential mask is used to optimize the transmittance estimation to make it more consistent with the dark channel hypothesis. Then, we propose a bilateral fractional differentiation algorithm that enhances the edge details of an image through the fractional differential in the spatial domain and intensity domain. Finally, we implement the inversion operation to obtain the final enhanced image. We apply the proposed IDCP_BFD method to a multispectral dataset and conduct sufficient experiments. The experimental results show the superiority of the proposed method over relative comparison methods.en_NZ
dc.publisherMDPI
dc.relation.urihttps://www.mdpi.com/2072-4292/14/1/233
dc.rights© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
dc.subjectMultispectral image enhancement; Remote sensing; Dark channel prior; Fractional differential
dc.titleMultispectral Image Enhancement Based on the Dark Channel Prior and Bilateral Fractional Differential Modelen_NZ
dc.typeJournal Article
dc.rights.accessrightsOpenAccessen_NZ
dc.identifier.doi10.3390/rs14010233en_NZ
aut.relation.issue1en_NZ
aut.relation.volume14en_NZ
pubs.elements-id447823
aut.relation.journalRemote Sensingen_NZ


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