Video SAR Moving Target Detection Method Based on Machine Vision

When detecting moving targets in video SAR, it is impossible to accurately obtain the moving targets in dynamic images. In order to solve the problems of low detection integrity and poor effectiveness, a video SAR moving target detection method based on machine vision is proposed. Firstly, the moving target pixel points are matched by the mixed Gaussian model to obtain the target area of the video SAR moving image; secondly, the HSV model and reflectivity algorithm are used to remove the shadows caused by the moving target; finally, the processed target area is input into the YOLO algorithm to complete the final video SAR moving target detection. Experimental results show that the proposed algorithm has high detection integrity, high detection rate, low false detection rate, and better detection effectiveness.

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Publication Details

Journal
Scientific insights and discoveries review
Published
2024-10-11
DOI
https://doi.org/10.59782/sidr.v3i1.129
Primary Topic
Advanced SAR Imaging Techniques
Type
article
Field-Weighted Citation Impact
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article

Video SAR Moving Target Detection Method Based on Machine Vision

Di Wu, Ming He
Scientific insights and discoveries review
Advanced SAR Imaging Techniques
article

Video SAR Moving Target Detection Method Based on Machine Vision

Di Wu, Ming He
article en

Abstract

When detecting moving targets in video SAR, it is impossible to accurately obtain the moving targets in dynamic images. In order to solve the problems of low detection integrity and poor effectiveness, a video SAR moving target detection method based on machine vision is proposed. Firstly, the moving target pixel points are matched by the mixed Gaussian model to obtain the target area of the video SAR moving image; secondly, the HSV model and reflectivity algorithm are used to remove the shadows caused by the moving target; finally, the processed target area is input into the YOLO algorithm to complete the final video SAR moving target detection. Experimental results show that the proposed algorithm has high detection integrity, high detection rate, low false detection rate, and better detection effectiveness.

Scientific insights and discoveries reviewVol. 3
No poverty
Openalex Percentile: Top 73%
Advanced SAR Imaging Techniques
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