Segmentation algorithm of high resolution remote sensing images based on LBP and statistical region merging

Remote sensing image segmentation is the basis of object-oriented classification of remote sensing images. It is important for the application of remote sensing images. High-resolution remote sensing images contain rich spatial texture information. SRM is an efficient image segmentation algorithm. This paper presents a segmentation algorithm to take full advantage of the high-resolution remote sensing image texture information based on LBP and SRM, in the process of merging, according to the characteristics of regions, select the appropriate method to merge. It works well in the segmentation of high-resolution remote sensing images.