Aiming at the problems of poor real-time performance and low accuracy of the existing UV imagers in UV and visible image registration, a method of UV and visible image registration fusion based on convolutional neural network (CNN) and wavelet fusion (WF) is proposed and applied to high sensitive UV imager. Firstly, the parameter model of the collected image data is pre-trained by combining the rigid body transformation and convolution neural network, and the optimal spatial transformation parameters are found by self-mining image features to achieve accurate registration of UV image and visible image. Secondly, two-dimensional wavelet decomposition and reconstruction algorithm is used to realize the fusion of UV and visible images. Experimental results show that the proposed method has fast registration speed, high overlay accuracy and good stability.