Method for automatically detecting remote sensing ground object target based on stochastic geometry model

Abstract

The invention provides a method for automatically detecting a remote sensing ground object target based on a stochastic geometry model. The method solves the automatic detection problem of a target with a relatively complex structure but relatively singular geometric component features in a remote sensing image. The method comprises the following steps: establishing a plurality of classes of image representative sets comprising the remote sensing ground object target; constructing the stochastic geometry model aiming at a target to be processed by taking geometric components for forming the target as processing units; after constructing the stochastic geometry model of the target components, converting the automatic detection problem of the target into an optimal configuration problem of a stochastic target seeking process; estimating the maximum value of the non-parameter probability density by using a Markov chain Monte Carlo method; and finally, detecting the target by using the stochastic geometry model, judging whether the target exists in the tested image or not, ending and outputting a result that no target exists if no target exists, and processing the image by using the stochastic geometry model to obtain the detection result corresponding to optimal configuration and outputting the final detection position of the target if the target exists.

Description

technical field [0001] The invention relates to a method for target detection in the technical field of image information processing, in particular to a method for automatically detecting ground objects and targets in remote sensing scene images based on a random geometric model. Background technique [0002] According to the characteristics of remote sensing surface objects in terms of shape and appearance, it can be divided into a large category of targets with complex structures. The structure of this type of targets is relatively complex but the characteristics of geometric components are relatively simple, such as aircraft and ship targets. Due to the rich information contained in the remote sensing image and the complex scene, not only the detailed features of the target are enlarged, but also the interference is enhanced, which brings great difficulty to the detection and positioning of this type of target. [0003] Stochastic geometry theory is a modern random set th...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a method for automatic detection of remote sensing ground object targets based on random geometric models to solve the problem of automatic detection of targets with relatively complex structures but relatively single geometric component characteristics in remote sensing images, such as aircrafts, ships, etc.

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