基于Roberts算子的激光夜视图像自动分割方法
Automatic segmentation method of laser night vision image based on Roberts operator
李星军 1邵志伟 1梁嘉怡1
作者信息
摘要
激光夜视图像分辨率较低,边缘信息难以检测,导致图像分割过程存在效率低、精度较差等问题,为此设计基于Roberts算子的激光夜视图像自动分割方法.使用相机采集夜间场景色彩信息,采用加权平均法重构图像数据,输出完整的激光夜视图像.拟合图像周边相邻像素,利用三次样条插值函数平滑处理图像,运用Roberts算子计算图像梯度,实现激光夜视图像边缘检测,得到图像插值后的平滑信息,提升夜视图像分辨率.通过模糊C均值聚类明确聚类范围,引入混沌粒子群算法实现图像分割.实验结果表明,所提方法分割差异率在3％以下,图像分割Dice相似性系数在0.97以上,图像分割平均耗时为9 s.
Abstract
The resolution of laser night vision images is low,and edge information is difficult to detect,resulting in low efficiency and poor accuracy in the image segmentation process.Therefore,a laser night vision image automatic segmentation method based on Roberts operator is designed.Use a camera to collect color information from nighttime scenes,reconstruct image data using the weighted average method,and output a complete laser night vision image.Fit adjacent pixels around the image,use cubic spline interpolation function to smooth the image,use Roberts operator to calculate image gradient,achieve edge detection of laser night vision images,obtain smooth information after image in-terpolation,and improve the resolution of night vision images.By using fuzzy C-means clustering to clarify the cluste-ring range,chaotic particle swarm optimization algorithm is introduced to achieve image segmentation.The experimen-tal results show that the segmentation difference rate of the proposed method is below 3％,the Dice similarity coeffi-cient of image segmentation is above 0.97,and the average image segmentation time is 9 seconds.
关键词
Roberts算子/三次样条插值函数/激光夜视图像/图像分割/模糊C均值聚类Key words
Roberts operator/cubic spline interpolation function/laser night vision image/image segmentation/fuzzy C-means clustering引用本文复制引用
基金项目
陕西省产业协同与城镇化发展耦合状态研究项目(2022JM-055)
出版年
2024
NETL
NSTL
万方数据