On-orbit SAR image change detection method based on sample self-calibration elm

Abstract

The invention proposes an on-orbit SAR image change detection method based on the sample self-calibration ELM, which improves the detection accuracy and expands the practical application range of the method. The steps include: calculating and obtaining the logarithmic difference map DI for two SAR image pairs of the registration phase; using PCA to obtain the principal component of DI; using the sample self-calibration strategy to obtain the strict change of the principal component of the logarithmic difference map after normalization region and strictly unchanged region; extract the neighborhood features of some samples from it, and use it as a training sample to train ELM; send the neighborhood of each sample in the logarithmic difference map to be detected to the trained ELM to obtain change detection Result graph. The present invention automatically extracts training samples from the differential image to be detected, eliminates the limitation of the training data on the detection ability of the method, expands the practical application range of the method, avoids manual participation, reduces the interference of noise, and improves the detection accuracy of the method rate, with stable and reliable detection capabilities.

Description

technical field [0001] The invention belongs to the technical field of image detection, and mainly relates to SAR image change detection, in particular to an on-orbit SAR image change detection method based on sample self-calibration ELM. It is used for real-time on-orbit change detection of SAR images captured by satellites. Background technique [0002] Synthetic Aperture Radar (SAR) is a high-resolution imaging radar that can obtain high-resolution radar images similar to optical photography in weather conditions with extremely low visibility. Due to its excellent characteristics, SAR has been widely used in industrial and agricultural production, urban monitoring, military and scientific research and other fields. SAR-based image change detection is to compare and analyze two images of the same area at different times, identify the differences between the images, and obtain the required target or terrain change information. Nowadays, with the rapid development of citie...

AI Technical Summary

Problems solved by technology

Although the detection method based on this idea eliminates the need for on-board network parameter training and improves the speed of the detection method to a certain extent, due to the scarcity and high cost of training data information and the network parameters of the on-board detection method fixed, so that when such methods are faced with data of target areas with different widths, different resolutions, and different imaging methods, their detection quality is subject to great fluctuations. Stability, which severely limits the practical application of the detection method

[0005] In summary, the detection accuracy and robustness of the unsupervised on-orbit SAR image change detection method are not ideal; the supervised on-orbit SAR image change detection method requires manual labeling of the training data, which cannot be flexibly applied to different imaging methods , the detection results are unstable due to different resolutions and imaging methods

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