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

Abstract

The invention relates to a quick deep learning remote sensing image target detection method based on candidate region screening and belongs to the field of remote sensing image processing. The methodcomprises the steps that (1) target training samples are utilized to train a deep convolution network model; (2) target geometric feature conditions are input, including target length, width and a length-to-width ratio range; (3) image parameters are analyzed, mainly including resolution information in two directions; (4) according to the resolution information, target geometric features are converted into pixel limiting conditions; (5) a remote sensing image target segmentation technology is utilized to realize target candidate region extraction; (6) according to the target geometric information size limiting conditions in the step 4, target candidate regions in the step 5 are screened; and (7) feature recognition is performed on the target candidate regions obtained after screening in the step 6 to determine a target. According to the method, target geometric feature information is utilized to screen the candidate regions, so that target detection efficiency is improved, and meanwhile false warning is suppressed to some extent.

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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