Please use this identifier to cite or link to this item: https://idr.nitk.ac.in/jspui/handle/123456789/16415
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dc.contributor.authorGogineni R.
dc.contributor.authorChaturvedi A.
dc.contributor.authorB S D.S.
dc.date.accessioned2021-05-05T10:30:25Z-
dc.date.available2021-05-05T10:30:25Z-
dc.date.issued2020
dc.identifier.citationInternational Journal of Image and Data Fusion , Vol. , , p. -en_US
dc.identifier.urihttps://doi.org/10.1080/19479832.2020.1838629
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/16415-
dc.description.abstractPan-sharpening is a remote sensing image fusion technique that generates a high-resolution multispectral (HRMS) image on combining a low resolution multispectral (MS) image and a panchromatic (PAN) image. In this paper, a new optimisation model is proposed for pan-sharpening. The proposed model consists of three terms: (i) a data synthesis fidelity term formulated on inferring the relationship between source MS image and fused image to preserve the spectral information, (ii) a total generalised variation-based prior term to inject the significant spatial details from PAN image to pan-sharpened image, and (iii) a spectral distortion reduction term that exploits the correlation between multispectral image bands. To solve the resultant convex optimisation problem, an efficient and convergence guaranteed operator splitting framework based on the alternating direction method of multipliers (ADMM) algorithm is formulated. Finally, the proposed model is experimentally validated using full-resolution and reduced-resolution data. The pan-sharpened outcomes exhibit the potential of the proposed method in enhancing the spatial and spectral quality. © 2020 Informa UK Limited, trading as Taylor & Francis Group.en_US
dc.titleA variational pan-sharpening algorithm to enhance the spectral and spatial detailsen_US
dc.typeArticleen_US
Appears in Collections:1. Journal Articles

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