Dual-polarized SAR small ship detection method based on enhanced feature pyramid

A feature pyramid and ship detection technology, which is applied in neural learning methods, character and pattern recognition, biological neural network models, etc., can solve problems such as small scale and weak scattering intensity, and achieve the effect of reducing feature redundancy

Pending Publication Date: 2021-09-17
BEIJING UNIV OF CHEM TECH
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Problems solved by technology

[0005] The main purpose of the present invention is to provide a SAR based on dual-polarization adaptive channel fusion and attention-enhanced low-level feature pyramid to solve the problem of missed detection of small ship targets in SAR images due to their small scale and weak scattering intensity. Target Detection Method for Small Ships

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  • Dual-polarized SAR small ship detection method based on enhanced feature pyramid
  • Dual-polarized SAR small ship detection method based on enhanced feature pyramid
  • Dual-polarized SAR small ship detection method based on enhanced feature pyramid

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[0057] The implementation process and experimental results of the present invention will be further described below in conjunction with the accompanying drawings.

[0058] The sample data used in the implementation of the present invention is the LS-SSDD-v1.0 data set released by the University of Electronic Science and Technology of China (Chengdu) in 2020, which is obtained by annotating 15 large-scale sentinel-1 images, and provides VV and VH. The size of each large image is 24000×16000 pixels, the resolution is 5×20m, and there are a total of 2358 ship targets, which are labeled with Labelimg software based on AIS data and Google Earth. The number of pixels marked in the data set is less than 2342, and they are all small targets in the large scene image. A total of 9000 ship slices are obtained by sequentially cropping with a sliding window of 800×800 size, including a large number of pure ships without ship targets. Background slice, the main features of this data set are...

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Abstract

The invention discloses a dual-polarization SAR small ship detection method based on an enhanced feature pyramid, and aims to solve the problem that small and medium-sized ships in a synthetic aperture radar (SAR) image are generally weak in scattering intensity and only occupy a small number of pixels in the image to cause leak detection. Two channel fusion coefficients in dual-polarization SAR data are automatically learned through feedback of a detection result, and a fusion channel input feature extraction network is obtained through coefficient weighting. In the improved attention enhancement type low-level feature pyramid, the sampling frequency under the deep network is reduced to obtain the low-level feature pyramid, prediction is carried out on a large-scale feature map, the problem that features disappear due to the fact that small ships occupy few pixels in an SAR image can be relieved, and meanwhile a space and channel attention mechanism is introduced.

Description

technical field [0001] The invention relates to a SAR small ship target detection method based on dual polarization self-adaptive channel fusion and attention-enhanced low-level feature pyramid, and belongs to the technical field of SAR automatic target detection. Background technique [0002] Synthetic Aperture Radar (SAR) is a high-resolution imaging radar based on active microwave sensing. Widely used in environmental terrain survey, military reconnaissance, marine monitoring and other fields, SAR image ship target detection is an important technical means of marine monitoring. [0003] Traditional ship target detection mostly uses methods such as threshold method and manual feature extraction to distinguish the ship from the sea background in large-scene SAR images. However, manual extraction of features is complex and requires certain prior knowledge, which requires high technical requirements. With the continuous development of computer vision, deep learning has been...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/08G06N3/04
CPCG06N3/08G06N3/045G06F18/25
Inventor 周勇胜张飞翔张帆马飞尹嫱项德良
Owner BEIJING UNIV OF CHEM TECH
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