Fast deep learning remote sensing image target detection method based on candidate region screening

Abstract

The invention relates to a fast deep learning remote sensing image target detection method based on candidate region screening, which belongs to the field of remote sensing image processing and includes the following steps: 1) using target training samples to train a deep convolutional network model; 2) inputting target geometry Feature conditions, including target length, width, and aspect ratio range; 3) Analyzing image parameters, mainly resolution information in two directions; 4) Converting target geometric features into pixel limiting conditions according to resolution information; 5) Using The remote sensing image target segmentation technology realizes the target candidate area extraction; 6) according to the target geometric information size limitation condition in step 4, the target candidate area in step 5 is screened; 7) the target candidate area after screening obtained in step 6 Perform feature recognition to determine whether it is a target. The invention proposes to use the target geometric feature information to screen the candidate areas, which improves the target detection efficiency and has a certain inhibitory effect on false alarms.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, and in particular relates to a rapid deep learning remote sensing image target detection method based on candidate region screening. Background technique [0002] In the 1960s, remote sensing was developed as an emerging comprehensive technology. Since then, a long-standing scientific problem in remote sensing is how to extract information from remote sensing data, because more and more high-spatial-resolution remote sensing data continue to The emergence of remote sensing technology has made people pay more attention to how to comprehensively utilize various useful information extraction technologies and how to better extract quantitative information from various remote sensing data. Among them, remote sensing image target detection and recognition is an important application field and difficult problem in the application of remote sensing images. It refers to the purpose...

AI Technical Summary

Problems solved by technology

[0004] An important problem of the deep learning method is that it has a large computational complexity. For remote sensing images, especially high-resolution remote sensing images, the target detection efficiency is low, which seriously limits the application of deep learning methods in practical systems.

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