Large-breadth SAR image ship target detection and identification method based on fine segmentation

Abstract

The invention belongs to the technical field of SAR ship target detection and identification, and discloses a large-breadth SAR image ship target detection and identification method based on fine segmentation. The method comprises the following steps: carrying out stretching and cutting of a large-breadth SAR original image, and obtaining a plurality of slice images; detecting the slice images to obtain a detection result, mapping the detection result back to the original image, fusing redundant detection frames by utilizing a voting strategy, and calculating a new target position; sending each target area into a segmentation network FCN to obtain a fine pixel-level segmentation result of a target; and taking out a minimum bounding box of a segmented target, sending the minimum bounding box into a classification network AlexNet, and suppressing a false alarm target to obtain a final detection and identification result. According to the method, the positioning precision and the detection speed of the target are effectively improved in the detection stage, after segmentation and classification network processing, the accuracy of a prediction frame is further improved, the false alarm rate is reduced, and detection and identification of SAR ship fine positioning are achieved.

Description

technical field [0001] The invention belongs to the technical field of SAR ship target detection and recognition, in particular to a large-format SAR image ship target detection and recognition method based on fine segmentation. Background technique [0002] Synthetic Aperture Radar (SAR) has the characteristics of strong penetrating power, high resolution, and can work around the clock. It is one of the most important means for people to observe the earth at present, and has been highly valued by various countries. In 2016, my country's Gaofen-3 satellite was successfully launched, marking my country's first self-developed high-resolution microwave remote sensing satellite. The successful launch of the satellite has effectively improved my country's high-resolution SAR dependence on imports. More and more SARs are carried on aircraft and missiles for battlefield reconnaissance, ocean surveillance and guidance. SAR data also shows an increase year by year. trend. [0003] S...

AI Technical Summary

Problems solved by technology

[0006] (1) For a large amount of large-format SAR data captured in near real-time by remote sensing satellites or UAVs equipped with SAR, the existing SAR detection network is difficult to take into account the detection speed and detection accuracy, and cannot achieve efficient and high-precision detection of massive large-format data

[0007] (2) SAR data labeling is difficult, and the labeling form of the rectangular box is the main form. The detection network trained based on this rectangular box can locate the ship target relatively rough, and cannot achieve a finer positioning like the rotating box

[0008] (3) Due to the large size of the SAR image and the small ship target, the detection network often misidentifies objects such as islands, reefs and bright spots as ship targets, resulting in a high false alarm rate

[0011] (2) Although the rotating frame detection network can achieve precise positioning of the ship target to a certain extent and outline the general outline of the ship target, the number of existing rotating frame data sets is not enough to support the network for effective training

Therefore, we need to find a new method to solve the problem of rough ship target positioning and realize the fine positioning of ships.

[0012] (3) The imaging mechanism of SAR leads to the lack of significant texture features of ship targets, and most of them are bright cross spots. For islands and ports with buildings of the same material, it is more difficult to distinguish them through the detection network.

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