A detection method for small target in remote sensing image based on improved SSD

Ziqiang Hao; Chenglin Wang; Peng Chen; Daoxue Fan; Yixing Shang

doi:10.1117/12.2668089

20 April 2023 A detection method for small target in remote sensing image based on improved SSD

Ziqiang Hao, Chenglin Wang, Peng Chen, Daoxue Fan, Yixing Shang

Proceedings Volume 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022); 126021F (2023) https://doi.org/10.1117/12.2668089
Event: International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 2022, Changchun, China

Abstract

In recent years, with the rapid development of satellite technology, object detection technology in remote sensing images has become an important research direction in the field of image processing. In this paper, aiming at the problems of low resolution, slow detection speed and vulnerability to background interference in remote sensing satellite images of ground vehicles, a vehicle small object detection algorithm based on residual network is proposed. Based on the original SSD (Single Shot MultiBox Detector) algorithm, the backbone network adopts the residual network with stronger feature extraction ability and less parameters, which can effectively improve the detection accuracy of small targets; Meanwhile, the Dense Extra Feature Layers network is proposed to enhance Feature propagation. Experimental results show that the mAP value of the proposed method in vehicle remote sensing image detection reaches 0.573, and the detection speed is 30.1fps, which has a good improvement in the detection accuracy and speed.

Citation Download Citation

Ziqiang Hao, Chenglin Wang, Peng Chen, Daoxue Fan, and Yixing Shang "A detection method for small target in remote sensing image based on improved SSD", Proc. SPIE 12602, International Conference on Electronic Information Engineering and Computer Science (EIECS 2022), 126021F (20 April 2023); https://doi.org/10.1117/12.2668089

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