Abstract: An image fusion method based on image and LiDAR point cloud is provided. The method comprises: acquiring a first image and sparse point cloud data, point cloud data in each channel of the sparse point cloud data corresponding to pixels in the first image respectively, and the sparse point cloud data and the first image having space and time synchronicity; obtaining a target gradient value corresponding to at least one target pixel in the first image according to the first image, the target pixel being a non-edge pixel of the first image; up-sampling the sparse point cloud data based on at least one target gradient value to obtain dense point cloud data, the target gradient value being determined according to a corresponding target pixel between adjacent channels of the sparse point cloud data; and obtaining a target fusion image based on the first image and the dense point cloud data.

Abstract: An image fusion method based on image and LiDAR point cloud, comprises: acquiring a first image and sparse point cloud data (S10), point cloud data comprised in each channel of the sparse point cloud data corresponding to pixels comprised in the first image respectively, and the sparse point cloud data and the first image having space and time synchronicity; obtaining a target gradient value corresponding to at least one target pixel comprised in the first image according to the first image (S12), the target pixel being a non-edge pixel of the first image; up-sampling the sparse point cloud data based on at least one target gradient value to obtain dense point cloud data (S14), the target gradient value being determined according to a corresponding target pixel between adjacent channels of the sparse point cloud data; and obtaining a target fusion image based on the first image and the dense point cloud data (S16).