Extension of luminance component based demosaicking algorithm to 4- and 5-band multispectral images

• Published in: Array (New York) Vol. 12; p. 100088
• Main Authors: Hounsou, Norbert, Sanda Mahama, Amadou T., Gouton, Pierre
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.12.2021; Elsevier
• Subjects: Convolution; Demosaicking algorithm; Luminance component; Multispectral filter array; Weighted bilinear interpolation; Multispectral filter array; Demosaicking algorithm; Convolution; Luminance component; Weighted bilinear interpolation
• ISSN: 2590-0056; 2590-0056
• DOI: 10.1016/j.array.2021.100088

Multispectral imaging systems are currently expanding with a variety of multispectral demosaicking algorithms. But these algorithms have limitations due to the remarkable presence of artifacts in the reconstructed image. In this paper, we propose a powerful multispectral image demosaicking method that focuses on the G band and luminance component. We've first identified a relevant 4-and 5-band multispectral filter array (MSFA) with the dominant G band and then proposed an algorithm that consistently estimates the missing G values and other missing components using a convolution operator and a weighted bilinear interpolation algorithm based on the luminance component. Using the considered MSFA patterns, we've also demonstrated that our algorithm outperforms existing approaches both visually and quantitatively in terms of the PSNR and SSIM.