SAR and optical remote sensing image registration method based on pseudo twin convolutional neural network

A convolutional neural network and optical remote sensing image technology, applied in the field of SAR and optical remote sensing image registration based on pseudo-twin convolutional neural network, can solve the problems of low accuracy, poor SAR and optical image registration effect, etc. The effect of improved performance

Active Publication Date: 2020-04-17
NO 54 INST OF CHINA ELECTRONICS SCI & TECH GRP +1
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[0008] The purpose of the present invention is to provide a SAR and optical remote sensing image registration method based on a pseudo-twin convolutional neural

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  • SAR and optical remote sensing image registration method based on pseudo twin convolutional neural network
  • SAR and optical remote sensing image registration method based on pseudo twin convolutional neural network
  • SAR and optical remote sensing image registration method based on pseudo twin convolutional neural network

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[0050] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0051] See Figure 1-5 , The present invention provides a technical solution: SAR and optical remote sensing image registration method based on pseudo twin convolutional neural network,

[0052] (1) Construct a pseudo-twin convolutional network model, such as figure 1 Shown.

[0053] In order to deal with the very different geometry and radiation appearance of SAR and optical remote sensing images, a pseudo-twin network architecture with tw...

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Abstract

The invention discloses an SAR and optical remote sensing image registration method based on a pseudo twin convolutional neural network in the technical field of remote sensing image registration. Firstly, feature image blocks are collected and matched; abnormal point removal and final registration are carried out, a strategy of maximizing a feature distance between a positive sample and a hard negative sample is adopted, a new loss function is defined to train the network, and two branches of the pseudo twin network are connected through convolution operation to obtain a similarity score between two input image blocks. According to the invention, a pseudo twin convolutional neural network system structure is provided, so that the left branch and the right branch of the pseudo twin networkcan respectively input optical and SAR remote sensing images with different sizes, and the task of identifying corresponding image blocks in the optical and SAR remote sensing images under extremelyhigh resolution can be solved.

Description

technical field [0001] The invention relates to the technical field of remote sensing image registration, in particular to a SAR and optical remote sensing image registration method based on a pseudo-twin convolutional neural network. Background technique [0002] In recent decades, earth monitoring through Remote Sensing (RS) has been widely used in both military and civilian life. Multimodal remote sensing images contain a lot of complementary information, which is beneficial to many remote sensing applications. To this end, image registration is a common requirement to exploit multimodal images. However, due to the different imaging mechanisms, multimodal image registration is more challenging than ordinary image registration, especially for optical and Synthetic Aperture Radar (SAR) images. Finding common features in optical and SAR images is very difficult due to the different imaging mechanisms. And as the spatial resolution increases, the existing gap in geometrica...

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Application Information

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IPC IPC(8): G06T7/33
CPCG06T7/33G06T2207/10044G06T2207/10032G06T2207/20081G06T2207/20084G06T2207/20021G06T2207/20164
Inventor 帅通董喆孙建国田左关键林尤添田野袁野刘加贝肖飞扬尹晗琦
Owner NO 54 INST OF CHINA ELECTRONICS SCI & TECH GRP
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