Neural network-based pose estimation and registration method and device for heterogeneous images, and medium

Abstract

The present invention relates to the field of image processing. Disclosed are a neural network-based pose estimation and registration method for heterogeneous images. In the present invention, a phase correlation algorithm is optimized to be differentiable and embedded into an end-to-end learning network framework, and a neural network-based pose estimation method for heterogeneous images is constructed. According to the method, an optimal feature extractor can be found for a result of image matching, a solution can be obtained without exhaustive evaluation, and good interpretability and generalization capability are achieved. The test results show that the present invention allows for accurate pose estimation and registration for heterogeneous images and shortening of the required time, has high accuracy and real-time performance, can meet actual application requirements, and can be applied in fields such as robot self-positioning.