Multispectral demosaicking using adaptive kernel upsampling

Multispectral demosaicking, which estimates full multispectral images from raw data observed using a single image sensor with a color filter array (CFA), is a challenging task because each spectral component is severely undersampled. In this paper, we propose a novel multispectral demosaicking algor...

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Bibliographic Details
Main Authors: Monno, Y., Tanaka, M., Okutomi, M.
Format: Conference Proceeding
Language:English
Subjects:
adaptive kernel
Arrays
Cameras
color filter array
Conferences
demosaicking
Estimation
Image color analysis
Kernel
Multispectral imaging
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Summary:Multispectral demosaicking, which estimates full multispectral images from raw data observed using a single image sensor with a color filter array (CFA), is a challenging task because each spectral component is severely undersampled. In this paper, we propose a novel multispectral demosaicking algorithm. We extend existing upsampling algorithms to adaptive kernel upsampling algorithms using an adaptive kernel as a spatial weight and apply them to multispectral demosaicking. We also propose a new CFA and a direct adaptive kernel estimation from the raw data of the proposed CFA. Experimental results with real multispectral images demonstrate the effectiveness of the proposed algorithm.
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2011.6116337