Remote sensing image target detection method and device

A target detection and remote sensing image technology, applied in the field of image processing, can solve the problems of low detection accuracy, achieve high robustness, improve generalization ability, and improve the effect of accuracy

Inactive Publication Date: 2018-09-11
LUOYANG INST OF ELECTRO OPTICAL EQUIP OF AVIC
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Problems solved by technology

[0008] The purpose of the present invention is to provide a remote sensing image target detection method and device to solve the problem of low detection accuracy in the prior art when only accurately marked remote sensing image databases are used for remote sensing image target detection

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  • Remote sensing image target detection method and device
  • Remote sensing image target detection method and device

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Embodiment Construction

[0041] In order to achieve fast, high-precision, high-robust automatic target detection in complex backgrounds, the present invention provides a remote sensing image target detection device, which includes a processor, and the processor is used to execute instructions to realize the remote sensing of the present invention Image object detection method. The best implementation of the remote sensing image target detection method of the present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0042] First, build a deep fully convolutional neural network. The deep fully convolutional neural network includes two parts, the main network for feature extraction and the sub-network for object detection.

[0043] The main network is a deep convolutional neural network, including an input layer, a hidden layer and a fully connected layer. The input layer is used to input the remote sensing image to be tested into the convoluti...

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Abstract

The invention relates to a remote sensing image target detection method and device. The method comprises the following steps: firstly, establishing a depth full-convolution neural network; the depth full-convolution neural network comprises a main network used for feature extraction and a sub-network used for target detection; training the main network through an image classification database; after the main network is trained, adding the sub-network; fine-adjusting the network parameters by means of the remote sensing target detection database to obtain a trained depth full-convolution neuralnetwork; and finally inputting the remote sensing image to be detected into the depth full-convolution neural network to obtain a final target detection result. Compared with a conventional way of directly using a remote sensing target detection database to train the established depth all-convolution neural network, the generalization ability and accuracy can be improved, and the rapid, high-precision and high-robustness automatic target detection can be realized in a complex background.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a remote sensing image target detection method and device. Background technique [0002] The automatic detection of remote sensing image targets refers to the technology that the computer detects and locates typical targets in the monitoring area in a fully automatic manner. Remote sensing image target detection is the main research content in the current remote sensing image application field, which has important theoretical significance and extensive application value. [0003] Automatic detection technology has important application value in both military and civilian aspects. In the military, automatic target detection is used to detect and detect military targets, and realize automatic surveillance, detection and warning of the area. In terms of civilian use, automatic target detection technology can be used to assist staff in vehicle monitoring, land ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/13G06V2201/07G06F18/214
Inventor 陈水忠侯康
Owner LUOYANG INST OF ELECTRO OPTICAL EQUIP OF AVIC
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