acquiring an image data set, and preprocessing the image data set to obtain an image set;

performing SLIC segmentation processing on the image set, introducing elevation information through weighting and setting a threshold in the SLIC segmentation processing process to obtain pre-segmentation results;

a method for the SLIC segmentation processing comprising: establishing spectral feature vectors and three-dimensional space feature vector among pixel points in a preset range; counting spectral Euclidean distances and three-dimensional space Euclidean distances between each pixel and a cluster center, and allocating the pixels to the segmentation regions with similar features; performing multiple iterations to optimize the cluster center; traversing the whole domain to remove regions with excessively small sizes;

performing region merging on the basis of the pre-segmentation results to complete image processing;

a method for obtaining the pre-segmentation results comprising: introducing elevation information into distance calculation and setting a comprehensive threshold of spectral weighting combined with the elevation information during the SLIC segmentation process; adding elevation information on the basis of a two-dimensional plane and spectral Euclidean distances to establish six-dimensional feature vectors; and

calculating the spectral Euclidean distances, the two-dimensional plane, and the elevation information for pixel i and pixel j within an initial superpixel range, expressed as respectively:

in the formulas, l, a and b represent spectral band values of pixels, x and y represent row and column numbers of pixels, and z represents an elevation value corresponding to the pixel.