A Change Detection Method for SAR Image Based on Stacked Semi-Supervised Adaptive Denoising Autoencoder

An image change detection and self-encoder technology, applied in the field of image processing, can solve problems such as error, edge detail detection is not good enough, and learning samples have a large impact
CN107392940BActive Publication Date: 2020-10-30XIDIAN UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
XIDIAN UNIV
Publication Date
2020-10-30

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Abstract

The invention discloses a SAR image change detection method based on a stacked semi-supervised self-adaptive denoising self-encoder, which solves the problem of low detection accuracy of coherent speckle noise points and many edge change regions in the existing method. The implementation steps are: first generate a multi-scale difference guidance map; use the phase 1 image as input to train SDAE; use the multi-scale difference guidance map, phase 1 and phase 2 images as input to train SSADAE, and SSADAE adaptive error function The weights obtained by SDAE training are used in the method; then SSADAE is used to calculate the feature vectors of phase 1 and phase 2 images; the two are subtracted to obtain the difference vector, and then FCM classification is performed on it to obtain the change detection result map. The present invention firstly proposes a multi-scale difference guidance map, which can highlight the change area in the difference map; the SSADAE proposed later can use a small number of marked samples in the image to further improve the accuracy of change detection.
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Description

technical field

[0001] The invention belongs to the technical field of image processing and relates to change detection of SAR images, in particular to a SAR image change detection method based on a stack semi-supervised self-adaptive denoising self-encoder. This method can be used in change detection of SAR images. Background technique

[0002] Change detection is one of the key technologies in the field of remote sensing. It detects the changes in the gray value or local texture of images in different periods in the same imaging scene, and obtains the shape, position, quantity and other properties of the surface or objects of interest. change information. It has a wide range of applications in the fields of society, environment and military.

[0003] In the multi-temporal SAR image change detection method, there are two main routes, one is post-classification comparison (Post Classification Comparison, PCC), and the other is post-comparison classification. The former me...

Claims

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