“…According to [32,33], the deep learning-based methods outperform the traditional methods, such as the Wiener filtering, polynomial regression, or the wavelet denoising, so the proposed method is compared with five state-of-the-art denoising methods, i.e. the NSST-BM3D model [18], the FFDNet model [30], the FFCNN model [31], the GAN model [35] and the NSTBNet model [36]. The parameters, such as the size of the convolutional layer, the network depth, are set to be the same as they are reported in the corresponding literature.…”