A method for aircraft target detection in sar images based on information interaction and transfer learning

Abstract

The invention discloses a SAR image aircraft target detection method based on information interaction and transfer learning, based on bright and dark threshold segmentation and k-nearest neighbor selection and extraction of candidate regions of interest in pixel space; each candidate region of interest in pixel space is Corresponding to the semantic sketch map of the SAR image, the position and size of the corresponding target candidate region of interest in the semantic space are obtained; the sketch line segment of the suspected wing shadow in the target candidate region of interest in the semantic space is extracted; using the wing The aircraft shadow complement method based on the local structure relationship between shadows and bright spots obtains the target shadow area map; uses the generation confrontation transfer learning method based on sketch annotation information to realize the classification and recognition of the target shadow area map, and obtains the final aircraft target detection result. The invention improves the accuracy rate of aircraft target detection, eliminates a large number of false alarms, and is suitable for the detection of aircraft targets in ultra-high resolution SAR images in complex scenes.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a method for detecting aircraft targets in SAR images based on information interaction and transfer learning, which is suitable for detecting aircraft targets in ultra-high resolution SAR images in complex scenes. Background technique [0002] Synthetic Aperture Radar (SAR) image interpretation has always been widely concerned by researchers. In recent years, with the development of radar technology, SAR images have reached ultra-high resolution, which brings opportunities and challenges to the interpretation work. . As an important military target, the aircraft target has a complex structure and variety, and the background environment is extremely complex, especially in the ultra-high resolution SAR image (MiniSAR), it usually exists in the form of strong scattering points. Due to the incomplete surface information, direct Performing aircraft target detecti...

AI Technical Summary

Problems solved by technology

If effective training data cannot be obtained, the detection performance of deep learning-based methods will not achieve the expected results

[0008] The above-mentioned aircraft target detection methods are highly pertinent, have great limitations, and are not suitable for complex scenes of ultra-high resolution SAR images. Therefore, with the increasing data of ultra-high resolution SAR images, it is imminent to study novel interpretation methods

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