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Remote-sensing image rotating target detection method

A remote sensing image and target detection technology, applied in the field of aerial image target detection, can solve the problems of insufficient robustness, insufficient use of scene and target semantic information, inability to predict the coordinates of rotated quadrilaterals, etc., to reduce interference and improve accuracy.

Active Publication Date: 2020-10-16
中国人民解放军93114部队 +1
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AI Technical Summary

Problems solved by technology

[0014] The purpose of the present invention is to provide a method for detecting rotating targets in remote sensing images, to solve the problem that the detection of optical remote sensing targets is not robust enough when the background is complex, the coordinates of the rotating quadrilateral surrounding the target cannot be predicted, and the scene and target are not fully utilized. The problem of semantic information between

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Embodiment

[0032] Example: A remote sensing image rotating target detection method, which proposes a new target detection network (GLS-Net), based on the Fast R-CNN network, combining the saliency algorithm RC with the feature pyramid network and adopts The saliency pyramid is constructed based on the saliency algorithm and neural network, and on the basis of the saliency pyramid, the global attention network branch is proposed, and the global semantic constraint network based on the channel attention mechanism is used to extract the depth features of the scene, and then on this basis, A fast feature fusion strategy based on the local target information of the saliency pyramid and the global semantic information optimized by the channel attention mechanism is proposed. Finally, an angle-sensitive IoU algorithm is proposed and used to optimize the non-maximum suppression algorithm during training. Effect to obtain a more accurate five-parameter rotating frame representation;

[0033] Specifi...

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Abstract

The invention discloses a remote sensing image rotating target detection method based on a global-local attention mechanism. The method comprises the following steps: S1, extracting depth features; s2, extracting a saliency feature map; s3, constructing a significance pyramid; s4, extracting features and coordinates of candidate regions which contain foreground potential targets and are ranked atthe top; s5, generating a global scene semantic constraint feature, and splicing the global scene semantic constraint feature with the feature from S4; s6, carrying out a RoIAlign pooling operation; s7, generating a final feature map; s8, category prediction and prediction of bounding box coordinates represented by five parameters are carried out; and S9, analog loss and coordinate loss are calculated, a calculation result of a non-maximum suppression algorithm is optimized by adopting an IoU, and a target detection result is displayed. The method can effectively reduce the interference of background noise, improves the precision of a detection result, can effectively eliminate an obvious false detection result, and finally obtains a high-precision and reasonable type and rotating boundingbox result.

Description

Technical field [0001] The invention relates to a remote sensing image rotating target detection method, belonging to the technical field of aerial image target detection. Background technique [0002] Simultaneous positioning and category recognition are the foundation and difficulty of aerial image target detection. As the number of aircraft and satellites increases, more and more aerial images are available. Target detection in aerial images has become one of the research hotspots in the field of computer vision, and has a wide range of applications in the fields of traffic control, airport monitoring, oil depot monitoring, near shore ship detection, and military target discovery. [0003] When the target scale changes drastically, the background is complex, the target direction is arbitrary, and the meteorological environment is complicated, it is an important and urgent problem to use the semantic information of the scene and the target and the difference between the target a...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/04G06N3/08G06T3/40
CPCG06T3/4038G06N3/084G06V20/13G06V10/507G06V10/56G06V2201/07G06N3/045G06F18/253
Inventor 洪海龙李成源毛文举安雨陈东罗斌刘军王晨捷
Owner 中国人民解放军93114部队
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