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Multispectral remote sensing image detection method and system for three-party generative adversarial network

A technology of remote sensing images and detection methods, applied in the field of image processing, can solve problems such as mode collapse, and achieve the effects of high change detection accuracy and reliable final change detection results

Active Publication Date: 2020-02-25
HOHAI UNIV
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Problems solved by technology

The disadvantage of this method is that the network is only composed of two-sided confrontation networks, and the training of the network is prone to mode collapse.

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  • Multispectral remote sensing image detection method and system for three-party generative adversarial network
  • Multispectral remote sensing image detection method and system for three-party generative adversarial network
  • Multispectral remote sensing image detection method and system for three-party generative adversarial network

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Embodiment Construction

[0047] A multi-spectral remote sensing image detection method and system based on a tripartite generative adversarial network, including performing image registration on the remote sensing image and using a multivariate change detection method to perform radiation correction, and then calculating the change vector magnitude of the remote sensing image; according to the change vector magnitude And use the maximum expectation algorithm to obtain the pseudo-training sample set, including the labeled sample set (including the changed sample set, the non-changed sample set) and the non-labeled sample set; build a three-party generation confrontation network based on the discriminant network, the generation network and the classification network, The discriminative network D judges the authenticity of the input image, that is, judges whether the input image is a real image or an image generated by the generation network G or a non-marked image input by the classification network; the ...

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Abstract

The invention discloses a multispectral remote sensing image detection method and system of a three-party generative adversarial network, and belongs to the technical field of image processing. The multispectral remote sensing image detection method comprises a generative network, a discrimination network and a classification network. The generative network generates false data. The correspondingclassification network calculates the cross entropy of the generative data and labeled data and predicts the category of unlabeled data. The discrimination network discriminates marked data as true, generated data and non-marked data as false, and each network parameter is continuously updated through a three-party network game, so that the final change detection result of the dual-temporal multispectral remote sensing image is more reliable and stable; in addition, an unmarked sample set is added in the training of the network to participate in the training, so that the change detection precision is higher.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a multispectral remote sensing image detection method and system using a tripartite generative confrontation network. Background technique [0002] With the continuous accumulation of multi-temporal remote sensing data and the successive establishment of spatial databases, how to extract and detect change information from these remote sensing data has become an important research topic in remote sensing science and geographic information science. According to remote sensing images of different time phases in the same area, dynamic information such as cities and environments can be extracted to provide scientific decision-making basis for resource management and planning, environmental protection and other departments. The change detection of remote sensing images is the technique of extracting change information from remote sensing data of different periods c...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/13G06N3/048G06N3/045G06F18/241
Inventor 石爱业石冉
Owner HOHAI UNIV
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