2018_TGRS_HSI-DeNet: Hyperspectral Image Restoration via Convolutional Neural Network ( Chinese science- Chang Yi)
Good evening everyone, today we share a paper on hyperspectral image restoration using Convolutional Neural Network (CNN).In this paper, based on CNN, we introduce both residual learning, dilation convolution and multi-channel filtering to obtain HSI-DeNet network, which achieves the removal of mixed noise in HSI: random, structural stripes, dead lines, etc. In addition, in order to obtain high image quality and quantization metrics at the same time, the proposed network is introduced into the generative adversarial network to obtain the HSI-DeGAN network in this paper.
First, the network structure of HSI-DeNet is shown below.
Each of these Blocks consists of three parts: convolution layer, block normalization (BN) and activation function (ReLU), as follows.