Image segmentation method based on minimum spanning trees and statistical learning theory

Abstract

The invention discloses an image segmentation method based on minimum spanning trees and a statistical learning theory. On the basis of image map model construction, a bottom-up combination strategy is adopted, and the process of generating a plurality of minimum spanning trees is finished according to statistical learning theory-based synthesis criterions designed by the invention by using a minimum spanning tree algorithm. The segmentation method can effectively utilize regional statistical characteristics at the same time of meeting global optimum, is suitable for the high-resolution segmentation of various images, and achieves relatively higher noise immunity and relatively better segmentation effects on texture regions; and in the method, good regional boundaries can be obtained simultaneously.

Description

technical field [0001] The method belongs to the technical field of image processing and pattern recognition, and in particular relates to a new object-oriented image segmentation method based on minimum spanning tree optimization theory and statistical learning theory. Background technique [0002] High-spatial-resolution remote sensing images provide us with high-precision spatial geometric information, rich texture information, and multi-spectral information of the ground landscape, making traditional pixel-based remote sensing image classification methods inapplicable, thus making high-resolution remote sensing image processing more difficult. Challenged with the detail provided by imagery. For this reason, Baatz and Schape pointed out in [1] in 1999 that important semantic interpretation needs to be represented by meaningful objects and the relationship between objects in images rather than by pixels. The target recognition and classification method of high-resolution ...

AI Technical Summary

Problems solved by technology

[0028] In view of the above-mentioned difficulties and problems, the present invention adopts a kind of image segmentation based on minimum spanning tree theory and proposes a segmentation criterion based on statistical learning theory design, realizes object-oriented image segmentation, avoids the problem of seed point selection in region growth, and Effectively solve the problem of over-segmentation

Images