Impact craters are formed due to the high-speed collisions between small to medium-sized celestial bodies.Impact is the most significant driving force in the evolution of celestial bodies,and the impact craters provid...Impact craters are formed due to the high-speed collisions between small to medium-sized celestial bodies.Impact is the most significant driving force in the evolution of celestial bodies,and the impact craters provide crucial insights into the formation,evolution,and impact history of celestial bodies.In this paper,we present a detailed review of the characteristics of impact craters,impact crater remote sensing data,recognition algorithms,and applications related to impact craters.We first provide a detailed description of the geometric texture,illumination,and morphology characteristics observed in remote sensing data of craters.Then we summarize the remote sensing data and cataloging databases for the four terrestrial planets(i.e.,the Moon,Mars,Mercury,and Venus),as well as the impact craters on Ceres.Subsequently,we study the advancement achieved in the traditional methods,machine learning methods,and deep learning methods applied to the classification,segmentation,and recognition of impact craters.Furthermore,based on the analysis results,we discuss the existing challenges in impact crater recognition and suggest some solutions.Finally,we explore the implementation of impact crater detection algorithms and provide a forward-looking perspective.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.41925006,12003075,42371383,and 42271450)。
文摘Impact craters are formed due to the high-speed collisions between small to medium-sized celestial bodies.Impact is the most significant driving force in the evolution of celestial bodies,and the impact craters provide crucial insights into the formation,evolution,and impact history of celestial bodies.In this paper,we present a detailed review of the characteristics of impact craters,impact crater remote sensing data,recognition algorithms,and applications related to impact craters.We first provide a detailed description of the geometric texture,illumination,and morphology characteristics observed in remote sensing data of craters.Then we summarize the remote sensing data and cataloging databases for the four terrestrial planets(i.e.,the Moon,Mars,Mercury,and Venus),as well as the impact craters on Ceres.Subsequently,we study the advancement achieved in the traditional methods,machine learning methods,and deep learning methods applied to the classification,segmentation,and recognition of impact craters.Furthermore,based on the analysis results,we discuss the existing challenges in impact crater recognition and suggest some solutions.Finally,we explore the implementation of impact crater detection algorithms and provide a forward-looking perspective.
