High-resolution remote sensing image weak and small target detection method based on deep learning

Abstract

The embodiment of the invention discloses a high-resolution remote sensing image weak and small target detection method and device based on deep learning. The method comprises the steps of obtaining ato-be-processed remote sensing image; inputting the remote sensing image to be processed into a pre-trained convolutional neural network, carrying out 4-time downsampling, 8-time downsampling and 16-time downsampling respectively on the remote sensing image to be processed through the convolutional neural network; obtaining the priori boxes of different sizes corresponding to the to-be-processedremote sensing image, identifying the target priori boxes of which the target category confidence is greater than a preset threshold, and determining the coordinate information of a target included inthe to-be-processed remote sensing image through a preset clustering algorithm according to the coordinate information of each target priori box, wherein the first layer of the convolutional neural network comprises a residual component, the second layer, the third layer and the fourth layer of the convolutional neural network each comprise four residual components, and each residual component comprises two convolutional layers and a fast link. By applying the scheme provided by the embodiment of the invention, the weak and small target detection precision can be improved.

Description

technical field [0001] The invention relates to the technical field of remote sensing image processing, in particular to a method for detecting weak and small targets in high-resolution remote sensing images based on deep learning. Background technique [0002] With the development of remote sensing technology, remote sensing images have been more and more widely used. For example, the target coordinate information, target attribute information, etc. can be obtained by detecting the target in the remote sensing image. [0003] The known target detection methods mainly detect targets based on prior information combined with single or multiple features designed manually. However, for weak and small targets in remote sensing images (such as resolutions smaller than 32*32, 64*64, 16*16, etc.), because they have less information and lower contrast, and occupy fewer pixels As a result, there are few available features, and the high-resolution remote sensing images are relatively...

AI Technical Summary

Problems solved by technology

However, for weak and small targets in remote sensing images (such as resolutions smaller than 32*32, 64*64, 16*16, etc.), because they have less information and lower contrast, and occupy fewer pixels As a result, there are few available features, and the high-resolution remote sensing images are relatively large, which makes detection based on traditional methods low in accuracy, and it is difficult to accurately detect weak and small targets.

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