一种水上航行场景可见光偏振图像融合方法
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1.武汉理工大学航运学院,武汉 430063;2.内河航运技术湖北省重点实验室,武汉 430063;3.山东交通学院威海校区威海海洋信息科学与技术研究院,威海 264200

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基金项目:

国家自然科学基金(51579204, 52001241)。


A Polarization Image Fusion Method of Visible Light in Water Navigation Scene
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Affiliation:

1.School of Navigation, Wuhan University of Technology, Wuhan 430063, China;2.Hubei Key Laboratory of Inland Shipping Technology, Wuhan 430063, China;3.Weihai Institute of Marine Information Science and Technology, Shandong Jiaotong University Weihai Campus, Weihai 264200, China

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    摘要:

    为了提升无人船(Unmanned surface vehicle, USV)在恶劣航行场景下的视觉感知能力,提出一种基于HSV(Hue, Saturation, Value)颜色空间的水上航行场景可见光偏振图像融合方法。根据水上航行场景的偏振特性,制定了不同区域的融合规则,再基于HSV颜色空间,融合原场景的颜色信息,实现了对恶劣航行场景图像的语义分割,并将测试结果进行对比分析。在耀斑场景下,综合像素精度(Pixel accuracy, PA)值为0.768 2。实验结果表明:该方法能增强图像对比度,凸显边缘轮廓信息,能够在恶劣航行场景下,稳定获得对比度较强、目标特性较好的特征信息,一定程度上提升了无人船在恶劣航行场景下的环境感知能力。

    Abstract:

    In order to improve the visual perception ability of unmanned surface vehicle(USV) in harsh navigation scene, a polarization image fusion method of visible light for water navigation scene is proposed based on hue, saturation, value(HSV) color space. The fusion rules for different regions are formulated in accordance with the polarization characteristics of the water navigation scene. And based on the HSV color space, the color information of the original scene is fused, which is tested that realizes the semantic segmentation of the harsh navigation scene image. The most striking result is that the pixel accuracy(PA) value in the flare scene is 0.768 2. And the experimental results indicate that the proposed method can enhance image contrast, highlight edge contour information, and stably obtain feature information with strong contrast as well as better target characteristics in harsh navigation scene, which improves the USV’s performance in harsh navigation scene to a certain extent.

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姜阳,肖长诗,文元桥,詹文强,陈芊芊.一种水上航行场景可见光偏振图像融合方法[J].数据采集与处理,2022,37(6):1376-1390

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  • 收稿日期:2021-06-29
  • 最后修改日期:2022-02-24
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  • 在线发布日期: 2022-11-25