Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking†
AbstractColor image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking. View Full-Text
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Monno, Y.; Kiku, D.; Tanaka, M.; Okutomi, M. Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking. Sensors 2017, 17, 2787.
Monno Y, Kiku D, Tanaka M, Okutomi M. Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking. Sensors. 2017; 17(12):2787.Chicago/Turabian Style
Monno, Yusuke; Kiku, Daisuke; Tanaka, Masayuki; Okutomi, Masatoshi. 2017. "Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking." Sensors 17, no. 12: 2787.
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