基于改进RLCM的红外舰船检测算法研究
Research on Infrared Ship Detection Algorithm Based on Improved RLCM
郭宏林 1王磊1
作者信息
- 1. 沈阳理工大学 机械工程学院,辽宁 沈阳 110159
- 折叠
摘要
针对红外小目标检测在不同复杂背景下虚警率高、检测精度低的特点,提出了一种改进相对局部对比度 RLCM的红外小目标检测算法.在预处理阶段采用自适应双边滤波对无关噪声进行滤除,同时通过多尺度处理增强小目标边缘轮廓,防止小目标淹没在背景中,以提高检测精度.检测阶段引入权重信息,将目标信息和背景信息作为权重参数进一步增强小目标.通过将处理后的目标显著图与原图作差,以增强目标位置精度,减弱块效应的影响.经实验表明,相比于传统的检测算法,所提算法的处理效果有明显提升.
Abstract
Aiming at the characteristics of high false alarm rate and low detection accuracy in different complex backgrounds,an infrared small target detection algorithm with improved relative local contrast measure(RLCM)is proposed.In the pre-processing stage,the adaptive bilateral filtering is used to filter the irrelevant noise,and the edge contour of the small target is enhanced by multi-scale processing to prevent the small target from drowning in the background and improve the detection accuracy.In the detection stage,weight information is introduced,and target information and background information are used as weight parameters to further enhance small targets.By making a difference between the processed salient image and the original image,the position accuracy of the target is enhanced and the influence of the block effect is weakened.The experimental results show that the proposed algorithm is more effective than the traditional detection algorithm.
关键词
红外小目标/自适应/目标检测/双边滤波Key words
infrared small target/self-adaption/target detection/bilateral filtering引用本文复制引用
出版年
2024
NETL
NSTL
万方数据