  We propose a novel demosaicking method for multispectral filter arrays based
on a deep convolutional neural network. The proposed method first interpolates
mosaicked multispectral images utilizing a bilinear approach, then applies a
residual network to initial demosaicked images. The residual network consists
of various three-dimensional convolutional layers and a rectified linear unit
for describing the features of a multispectral data cube. Experimental results
reveal that the proposed method outperforms conventional demosaicking methods.
