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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Rathi, V. | - |
dc.contributor.author | Goyal, P. | - |
dc.date.accessioned | 2022-06-26T09:04:52Z | - |
dc.date.available | 2022-06-26T09:04:52Z | - |
dc.date.issued | 2022-06-26 | - |
dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/3587 | - |
dc.description.abstract | In 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.iso | en_US | en_US |
dc.subject | Binary trees | en_US |
dc.subject | Convolution | en_US |
dc.subject | Correlation | en_US |
dc.subject | Filtering algorithms | en_US |
dc.subject | Hyperspectral imaging | en_US |
dc.subject | Indexes | en_US |
dc.subject | Signal processing algorithms | en_US |
dc.title | Multispectral Image Demosaicking Based on Novel Spectrally Localized Average Images | en_US |
dc.type | Article | en_US |
Appears in Collections: | Year-2022 |
Files in This Item:
File | Description | Size | Format | |
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Full Text.pdf | 1.53 MB | Adobe PDF | View/Open Request a copy |
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