Saliency and Deep Convolutional Networks Based Change Detection Method for SAR Images

Abstract

The invention discloses a SAR image change detection method based on saliency and deep convolution network, which mainly solves the problems of low detection accuracy and weak anti-interference ability in the prior art. The implementation plan is as follows: After preprocessing two SAR images in the same area at different times, perform logarithmic ratio operation and normalization to obtain a normalized logarithmic ratio difference map; perform significant feature extraction on the difference map, Obtain a saliency map; threshold the saliency map, and perform dot multiplication of the difference map and the thresholded result to obtain a saliency feature map; cluster the difference map to obtain pre-classification results; select training samples from the pre-classification results; Construct a deep convolutional network, use training samples to train the network; use the trained network to detect changes in SAR images. The invention can effectively suppress the interference of background area information, improve the accuracy of change detection, 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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