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面向舰船目标识别的遥感图像超分辨率重建

张天霖 逄征 陈红珍 陈实 卞春江

计算机工程与应用2024,Vol.60Issue(13):190-199,10.
计算机工程与应用2024,Vol.60Issue(13):190-199,10.DOI:10.3778/j.issn.1002-8331.2304-0200

面向舰船目标识别的遥感图像超分辨率重建

Remote Sensing Image Super-Resolution Reconstruction Method for Ship Target Recognition

张天霖 1逄征 1陈红珍 2陈实 2卞春江2

作者信息

  • 1. 中国科学院 国家空间科学中心 复杂航天系统综合电子与信息技术重点实验室,北京 100190||中国科学院大学 计算机科学与技术学院,北京 100049
  • 2. 中国科学院 国家空间科学中心 复杂航天系统综合电子与信息技术重点实验室,北京 100190
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摘要

Abstract

The degradation of space-based remote sensing image resolution poses great challenges for the recognition of ship targets.Image super-resolution reconstruction technology can provide rich information for recognition tasks.However,if image super-resolution reconstruction and ship target recognition tasks are performed independently,the internal coher-ence between the two tasks will be ignored.Aiming at these problems,in order to explore the effective combination of image super-resolution reconstruction and target recognition tasks,a remote sensing image super-resolution reconstruction method for ship target recognition is proposed.Specifically,a full channel concatenation network is firstly designed,which replaces the residual connection with an adaptively weighted full channel concatenation,improves the fluidity and expression performance of each layer feature,and realizes efficient super-resolution reconstruction of remote sensing images.In order to further explore the potential of super-resolution reconstruction to improve the performance of ship target recognition,a joint network of super-resolution reconstruction and target recognition is proposed by introducing multi-task learning technology.The stable training of the joint end-to-end network is realized by multi-stage training optimization strategy,so as to guide effective mutual supervised learning between tasks.The experimental results on the public data set FGSCR-42 show that when the resolution of remote sensing images is degraded by 8 times and 16 times,the proposed super-resolution reconstruction network helps the accuracy of ship target recognition to increase by 33.27 and 17.48 percentage points respectively;the proposed joint network further improves the recognition accuracy by 1.75 and 1.91 percentage points.

关键词

天基遥感图像/图像超分辨重建/舰船目标识别

Key words

space-based remote sensing images/image super-resolution reconstruction/ship target recognition

分类

信息技术与安全科学

引用本文复制引用

张天霖,逄征,陈红珍,陈实,卞春江..面向舰船目标识别的遥感图像超分辨率重建[J].计算机工程与应用,2024,60(13):190-199,10.

基金项目

中科院国家空间科学中心"攀登计划"(E1PD30031S). (E1PD30031S)

计算机工程与应用

OA北大核心CSTPCD

1002-8331

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