To address the problems of low accuracy and complex computation of AKAZE (accelerated-KAZE) algorithm in image matching, an image matching algorithm based on the fusion of Gaussian filtering and AKAZE-LATCH algorithm was proposed. Firstly, the input image is preprocessed by Gaussian filtering to remove continuous noise such as Gaussian noise and retain the edge information of the image. Then efficient binary descriptors were constructed for AKAZE using LATCH (Learned Arrangements of Three Patch Codes) algorithm, and corresponding matching pairs were obtained using KNN (K Nearest Neighbors) algorithm. Finally, the method was screened again with USAC(UniversalRANSAC) to remove false matches, and the final matching result was obtained. Experimental comparison shows that compared with AKAZE algorithm, the proposed algorithm has higher matching accuracy, good robustness and reliability, and can be used for image matching in most complex scenes.