Demosaicing Method for Multispectral Images Using Derivative Operations

Abstract Multispectral images have been found useful for various applications such as remote sensing, medical imaging, military surveillance, vision inspection for food quality control, etc. but the high costs of multispectral cameras limit their usage. Low cost multispectral cameras can be developed using a single sensor multispectral filter array (MSFA) and a demosaicing method to reconstruct the complete image from under sampled multispectral image data acquired using a single sensor MSFA imaging system. In this paper, we present a new demosaicing method based on the derivative operations for the multi-spectral images. To design MSFA patterns, binary tree method is often used and the band sequence is chosen such that the middle band has a higher probability of appearance in MSFA pattern. In the proposed method, first the middle spectral band pixel values are estimated and then it is used to compute derivatives that help estimate other spectral band pixel values. Unlike many recently developed demosaicing methods that are applicable to only specific band size multispectral images, the proposed method is generic and can be applied to obtain multispectral images for any number of spectral bands. The TokyoTech dataset and CAVE dataset of multispectral images are used for the evaluation purpose, and the experimental results show that the proposed method outperforms currently best known generic multispectral demosaicing method, namely binary tree edge sensing (BTES) method on both datasets and for different band-size multispectral images.