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Sensors 2017, 17(12), 2787; https://doi.org/10.3390/s17122787

Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking

1
Department of Systems and Control Engineering, School of Engineering, Tokyo Institute of Technology, Meguro-ku, Tokyo 152-8550, Japan
2
Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology, Koto-ku, Tokyo 135-0064, Japan
This paper is an extended version of our paper published in Monno, Y.; Kiku, D.; Tanaka, M.; Okutomi, M. Adaptive residual interpolation for color image demosaicking. In Proceedings of the 2015 IEEE International Conference on Image Processing (ICIP), Quebec City, QC, Canada, 27–30 September 2015; pp. 3861–3865.
Current affiliation is Olympus Corporation, Hachioji, Tokyo 192-8512, Japan. This work was performed in part when the author was a graduate student at Tokyo Institute of Technology.
*
Author to whom correspondence should be addressed.
Received: 31 October 2017 / Revised: 24 November 2017 / Accepted: 29 November 2017 / Published: 1 December 2017
(This article belongs to the Special Issue Snapshot Multi-Band Spectral and Polarization Imaging Systems)
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Abstract

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. View Full-Text
Keywords: image sensor; Bayer color filter array; multispectral filter array; demosaicking; residual interpolation image sensor; Bayer color filter array; multispectral filter array; demosaicking; residual interpolation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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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.

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