Remote sensing image change detection method based on deep learning

Through the deep learning optimization model, data quality evaluation and feature extraction of remote sensing image sets are solved, and the problem of inaccurate feature extraction in remote sensing image change detection is achieved, and more efficient abnormal change warning and analysis support is achieved.

CN119295456AActive Publication Date: 2025-01-10LONGYAN UNIV +3
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Patent Information

Application Number
CN202411822965.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-12
Publication Date
2025-01-10
Estimated Expiration
2044-12-12

AI Technical Summary

Technical Problem

The prior art directly extracts features in remote sensing image change detection, resulting in inaccuracy of analysis results and affecting the accuracy of image change analysis.

Method used

The target remote sensing image set is optimized through the optimization model in the deep learning method, the data quality is evaluated and feature extraction is performed, and the abnormal change factors are analyzed to achieve accurate early warning of remote sensing images.

Benefits of technology

It improves the accuracy and efficiency of change detection, enhances the accuracy and clarity of image information, reduces the impact of noise and interference on feature extraction, and provides a more reliable basis for data analysis.

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Abstract

The invention relates to the technical field of computers, and particularly discloses a remote sensing image change detection method based on deep learning, and the method comprises the steps: optimizing a target remote sensing image set through a first optimization model in a deep learning method, and obtaining the attribute parameters of the optimized target remote sensing image set; according to the method, data quality of a target remote sensing image set is evaluated, features in the target remote sensing image set are extracted based on the target remote sensing image set with high data quality, feature precision of a pixel-level feature set is analyzed, and early warning is performed on abnormal change of a target optimization remote sensing image set based on the high-precision features. Therefore, accurate early warning of the abnormal change in the target optimization remote sensing image set is realized, powerful technical support is provided for remote sensing monitoring and analysis, and the accuracy and efficiency of change detection are effectively improved.
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Citation Information

Patent Citations

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  • High-resolution remote sensing image change detection method based on self-supervised learning

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  • Remote sensing image intelligent segmentation method based on artificial intelligence

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