In recent years, in Space-Ground-Sea Wireless Networks, the rapid development of image recognition also promotes the development of images fusion. For example, the content of a single-mode medical image is very single, and the fused image contains more image information, which provides a more reliable basis for diagnosis. However, in wireless communication and medical image processing, the image fusion effect is poor and the efficiency is low. To solve this problem, an image fusion algorithm based on fast finite shear wave transform and convolutional neural network is proposed for wireless communication in this paper. This algorithm adopts the methods such as fast finite shear wave transform (FFST), reducing the dimension of the convolution layer, and the inverse process of fast finite shear wave transform. The experimental results show that the algorithm has a very good effect in both objective indicators and subjective vision, and it is also very feasible in wireless communication.

近年来，在天地海无线网络中，图像识别的快速发展也推动了图像融合的发展。例如，单模医学图像的内容非常单一，融合后的图像包含更多的图像信息，为诊断提供了更可靠的依据。但是，在无线通信和医学图像处理中，图像融合效果差，效率低。针对这一问题，本文提出了一种基于快速有限剪切波变换和卷积神经网络的无线通信图像融合算法。该算法采用了快速有限剪切波变换（FFST）、降低卷积层维数、快速有限剪切波变换的逆过程等方法。