Figure 4.

Illustration of the proposed deep learning architectures for RGB color restoration from multi-spectral images: (a) Convolutional and Deconvolutional Neural Network (CDNet) and (b) Encoder-Decoder Neural Network (ENDENet). CONV refers to convolution, DECONV to deconvolution and RELU (Rectified Linear Unit) is the non-linear function used for the layers in the respective illustration. For the term “k3f32s2”, k = kernel size (3 × 3), f = feature size (32) and s = size of stride (2, 2); the same notation is used through the illustration.