Remote sensing image unsupervised change detection method based on Siamese network structure

A change detection and remote sensing image technology, applied in image enhancement, image analysis, image data processing, etc., can solve the problems of unsupervised changes in SAR images, and achieve the improvement of differential feature mining ability, signal-to-noise ratio, and strong feature expression ability. Effect

Active Publication Date: 2020-09-18
SHAANXI UNIV OF SCI & TECH
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[0009] The purpose of the present invention is to propose a method for unsupervised change detection of remote sensing images based on Siamese network structure, to solve the problem of unsupervised change detection of SAR images, and to highlight change areas and suppress A better balance between speckle noise and higher detection accuracy

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  • Remote sensing image unsupervised change detection method based on Siamese network structure
  • Remote sensing image unsupervised change detection method based on Siamese network structure
  • Remote sensing image unsupervised change detection method based on Siamese network structure

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[0043] The present invention will be described in further detail below in conjunction with specific examples, but not as a limitation of the present invention.

[0044] like figure 1 As shown, the present invention is based on the unsupervised change detection method of remote sensing images based on the Siamese network structure, and based on the idea of ​​knowledge-driven joint data-driven, prior knowledge is introduced into the deep convolutional neural network, which is described as follows:

[0045] (1) Initialization: The filtering template W in the ALEW algorithm is 3×3. DFF-Siamese takes the pixel-by-pixel neighborhood of the same position in the image before and after the change as input, and the two sets of inputs can be expressed as:

[0046]

[0047]

[0048] in and respectively represent the neighborhood of a certain pixel before and after the change, and the number of input pixel blocks is H×L.

[0049] The input size is set to 5×5. In order to avoid ...

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Abstract

The invention discloses a remote sensing image unsupervised change detection method based on a Siamese network structure. The remote sensing image unsupervised change detection method comprises the following steps: (1) initializing parameters; (2) obtaining a difference image; (3) performing pixel-level fusion on the two information complementary difference images in the step (2) by using an adaptive local energy weighting algorithm to obtain a new difference image; (4) adopting a clustering algorithm to realize pre-classification; (5) taking a pre-classification result as a label, and realizing the precise detection of an SAR image change region through a DFF-Siamese network; according to the method, unsupervised change detection of the SAR image is realized, priori knowledge is introduced into the deep convolutional neural network, feature mining is deeper by adding a layer-by-layer difference measurement module in the Siamese network, the learning ability of the network is effectively improved, and a more ideal change detection result can be obtained.

Description

technical field [0001] The invention belongs to the field of image processing and pattern recognition, relates to a remote sensing image change detection method, in particular to a remote sensing image unsupervised change detection method based on a Siamese network structure. Background technique [0002] Remote sensing image change detection is a technology that analyzes the difference of the ground surface through two or more images of the same scene captured at different times. With the rapid development of remote sensing technology, change detection based on remote sensing images has become a key technology for updating geographic big data. Among them, synthetic aperture radar remote sensing images are widely used in environmental monitoring, urban research, disaster assessment, forest resource monitoring, etc. field. Due to the influence of wave interference, there will be errors in the total echo received by the imaging equipment of the radar sensor, resulting in a l...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/50G06T5/00G06K9/62G06N3/04G06N3/08
CPCG06T5/50G06T5/002G06N3/08G06T2207/20024G06N3/045G06F18/23G06F18/24
Inventor 雷涛薛丁华张肖张栋
Owner SHAANXI UNIV OF SCI & TECH
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