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dc.contributor.authorRathi, V.-
dc.contributor.authorGoyal, P.-
dc.date.accessioned2022-06-26T09:04:52Z-
dc.date.available2022-06-26T09:04:52Z-
dc.date.issued2022-06-26-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/3587-
dc.description.abstractIn thisletter, we propose a new generic multispectral image demosaicking algorithm using adaptive spectral correlation. Our proposed algorithm defines the spectrally localized average image (SLAI) corresponding to each spectral band, which has a strong spectral correlation with the pixel values of the corresponding spectral band in the raw image captured using a single sensor. The proposed algorithm uses the SLAI to estimate the missing pixel values of the spectral bands. Experimental results reveal that our algorithm outperforms other state-of-the-art generic multispectral image demosaicking algorithms in terms of objective and subjective evaluations.en_US
dc.language.isoen_USen_US
dc.subjectBinary treesen_US
dc.subjectConvolutionen_US
dc.subjectCorrelationen_US
dc.subjectFiltering algorithmsen_US
dc.subjectHyperspectral imagingen_US
dc.subjectIndexesen_US
dc.subjectSignal processing algorithmsen_US
dc.titleMultispectral Image Demosaicking Based on Novel Spectrally Localized Average Imagesen_US
dc.typeArticleen_US
Appears in Collections:Year-2022

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