Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking

• Published in: Sensors (Basel, Switzerland) Vol. 17; no. 12; p. 2787
• Main Authors: Monno, Yusuke, Kiku, Daisuke, Tanaka, Masayuki, Okutomi, Masatoshi
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.12.2017; MDPI
• Subjects: Adaptive algorithms; Algorithms; Bayer color filter array; Color imagery; demosaicking; Image acquisition; Image processing; Image quality; image sensor; Interpolation; multispectral filter array; Noise levels; residual interpolation; Spectral bands; State of the art; image sensor; demosaicking; multispectral filter array; residual interpolation; Bayer color filter array
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s17122787

Color 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.