Remote sensing image target detection model building method based on context enhancement and application

Abstract

The invention discloses a remote sensing image target detection model establishment method based on context enhancement and an application, and belongs to the technical field of image processing, andthe method comprises the steps: building a to-be-trained target detection model based on a neural network, and carrying out the target detection and training on a remote sensing image, obtaining a remote sensing image target detection model based on context enhancement; in the target detection model, using each module for extracting a multi-scale feature map F of the remote sensing image; extracting global context information of the F to obtain M; respectively enhancing boundary information and category information in the F to obtain M<E> and M<E><cl> and respectively capturing informationassociation between channels in M<E> and M<E><cl> to obtain channel weights W<d> and W<c>; and fusing the M and M<E> according to the W<d> to obtain a boundary information enhanced feature map F<E>, fusing the M and M<E><cl> according to the W<c> to obtain a category information enhanced feature map F<E><cl>, and fusingF, F<E>, and F<E><cl> to obtain a feature map F<E><ct>, and carrying outtarget detection on the feature map F<E><ct>. The method can improve the target detection precision of a remote sensing image.

Description

technical field [0001] The invention belongs to the technical field of image processing, and more specifically relates to a method and application for establishing a remote sensing image target detection model based on context enhancement. Background technique [0002] Target detection is a basic problem in the field of computer vision. The target position of interest is found in the image through a detection algorithm and its category is judged. Specific to remote sensing images, due to the complex image background, large changes in the target scale, there are many problems of missed detection and false detection, and the detection and recognition are more difficult. [0003] The existing target detection methods are mainly divided into: traditional target detection algorithms based on artificial features and target detection algorithms based on deep learning. Among them, the traditional target detection algorithm based on artificial features has poor generalization perfor...

AI Technical Summary

Problems solved by technology

[0006] Aiming at the defects and improvement needs of the prior art, the present invention provides a method and application for establishing a remote sensing image target detection model based on context enhancement. There are technical problems of feature conflicts in the process of classification and detection, in order to improve the detection ability of remote sensing image target detection methods

Images