KEYWORDS: RGB color model, Near infrared, Optical filters, Color difference, Image filtering, Lutetium, Image quality, Cameras, Algorithm development, Linear filtering
Extra band information in addition to the RGB, such as the near-infrared (NIR) and the ultra-violet, is valuable for many applications. In this paper, we propose a novel color filter array (CFA), which we call “hybrid CFA," and a demosaicking algorithm for the simultaneous capturing of the RGB and the additional band images. Our proposed hybrid CFA and demosaicking algorithm do not rely on any specific correlation between the RGB and the additional band. Therefore, the additional band can be arbitrarily decided by users. Experimental results demonstrate that our proposed demosaicking algorithm with the proposed hybrid CFA can provide the additional band image while keeping the RGB image almost the same quality as the image acquired by using the standard Bayer CFA.
KEYWORDS: Color difference, Image processing, Algorithm development, Image acquisition, Visualization, Image interpolation, Color imaging, Digital cameras, Cameras, RGB color model
A color difference interpolation technique is widely used for color image demosaicking. In this paper, we propose
a minimized-laplacian residual interpolation (MLRI) as an alternative to the color difference interpolation, where
the residuals are differences between observed and tentatively estimated pixel values. In the MLRI, we estimate
the tentative pixel values by minimizing the Laplacian energies of the residuals. This residual image transfor-
mation allows us to interpolate more easily than the standard color difference transformation. We incorporate
the proposed MLRI into the gradient based threshold free (GBTF) algorithm, which is one of current state-of-
the-art demosaicking algorithms. Experimental results demonstrate that our proposed demosaicking algorithm
can outperform the state-of-the-art algorithms for the 30 images of the IMAX and the Kodak datasets.
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