Method and system for realizing remote sensing image target detection based on deep neural network, and storage medium thereof

Abstract

The invention relates to a method and a system for realizing remote sensing image target detection based on a deep neural network, and a storage medium thereof, so as to realize detection of horizontal and rotary arrangement targets of a remote sensing image. According to the method, an anchor point box generation module is designed, an anchor point box is generated in a self-adaptive mode throughfeature information of different positions, and the influence of the difference of preset anchor point boxes on detection precision is reduced; aiming at the characteristic that more small targets exist in a remote sensing image, an improved feature pyramid structure is provided, and deep and shallow layer feature information is fused by adopting a transposed convolution method; aiming at difficulties such as complex background of a remote sensing image, a receptive field expanding module is adopted to extract more characteristic information, and the detection precision of a small target under a complex background is improved; a SmoothLn function is adopted as regression loss, so that the algorithm performance is further improved; for a rotation arrangement target, regression of an anglefactor is introduced to realize rotation frame detection. In addition, in order to facilitate the use of a user, the remote sensing image target detection system designed by the invention has the functions of horizontal frame and rotary frame detection and result statistics.

Description

technical field [0001] The invention belongs to the technical field of remote sensing image processing, relates to target detection and recognition in image processing, and specifically refers to a method, system and computer-readable storage medium for realizing remote sensing image target detection based on a deep neural network. Background technique [0002] Remote sensing images are widely used in environmental monitoring, resource surveys, agricultural output value calculations, urban construction planning, and military deployment. They are of great significance to national defense and social and economic development. As one of the applications of remote sensing image processing, target detection has very important uses in civilian and military fields by obtaining specific target category and location information. At the same time, using the determined target type and location also has a certain auxiliary effect on further information processing decision-making. [000...

AI Technical Summary

Problems solved by technology

[0004] At the same time, the detection effect of most anchor point methods in the prior art is greatly affected by the hyperparameters of the preset anchor point frame, so if the setting is not appropriate, it is easy to have more missed detections, etc., while the non-anchor point method is When dealing with dense scenes in remote sensing images, matching errors are prone to occur, resulting in loss of accuracy

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