SAR image change detection method based on significance and deep convolutional network

Abstract

The present invention discloses an SAR image change detection method based on significance and a deep convolutional network. The problem is mainly solved that the detection precision is low and the capacity of resisting disturbance is poor in the prior art. The implementation scheme of the method comprises the steps of: performing preprocessing of two SAR images of the same area at different moment to perform logarithm ratio operation and normalization to obtain a normalized logarithm ratio difference graph; performing significance feature extraction of the difference graph to obtain a saliency map; performing thresholding of the saliency map, multiplying the saliency map by a thresholding result to obtain a saliency feature map; performing clustering of the difference graph to obtain pre-classification results; selecting training samples from the pre-classification results; constructing a deep convolutional network, and performing training of the network by employing the training samples; and performing change detection of the SAR image by employing the trained network. The SAR image change detection method can effectively inhibit the disturbance of background area information, can improve the change detection accuracy, and can be used for natural disaster assessment, environmental resource detection and urban modeling planning.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a SAR image change detection method, which can be used for natural disaster assessment, environmental resource detection and urban construction planning. Background technique [0002] Compared with visible light and infrared remote sensing, synthetic aperture radar (SAR) has the characteristics of all-day, all-weather, and strong penetrating ability, so it has been widely used in both military and civilian fields. With the rapid development of SAR technology, SAR image change detection technology becomes increasingly important. SAR image change detection refers to the comparison and analysis of two or more SAR images obtained at different times in the same area, and the change information of the studied area over time is obtained according to the change differences between these SAR images. The key steps of SAR image change detection are to generate correspo...

AI Technical Summary

Problems solved by technology

Although this method improves the accuracy of multi-temporal SAR image change detection to a certain extent, the disadvantage is that it does not make good use of the spatial information between image neighborhoods, but directly pulls image blocks into vectors, Limits the improvement of SAR image change detection accuracy

The disadvantage of this method is that the training samples for training the network are manually calibrated, which will be a huge burden for high-resolution SAR image change detection. Artificial errors affect the accuracy of SAR image change detection

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