Matching Method of Lunar Remote Sensing Image Based on Laplacian

Abstract

Abstract In recent years, there is an emerging interest in the exploration of the lunar surface. We can use many images of the lunar with different resolutions sent by more and more satellites that launched to the Moon. However, research on the lunar image matching still faces various difficulties. Significantly differing from the complex physical structure of the Earth’s surface, the lunar surface is mainly craters, ridges and mountains, and its simple physical structure directly leads to the difficulty of extracting the same name points; satellite sensors are easily influenced by multiple factors while imaging, such as the shooting angle of the forward-looking and backward-looking linear array, the sun’s angle of incidence, which is likely to cause some differences in the brightness of the images, and it makes the image matching choose the appropriate image enhancement method. In this paper, taking Chang’e II CCD lunar image as an example, firstly we propose a method of extracting the same-name point of lunar images based on Laplacian and image grayscale matching, and compare it with the commonly used SIFT + RANSAC algorithm, the accuracy rate and processing speed rate increases by 4.55% and 58.3% respectively, which verifies the scientificity and rationality of this method. Our work provides a new idea for the study of lunar image matching technology and lays foundation for the image-based lunar surface research and development.