摘要
为了实现红外复杂背景下弱点目标的有效检测,提出了形态学Top-hat变换和改进的非线性扩散(以Perona-Malik(PM)的研究为基础)模型相结合的滤波算法,用于增强红外弱小目标信号、抑制复杂背景和噪声。该方法首先利用形态学滤波中的Top-hat算子对图像进行目标增强,然后对形态学滤波后的图像采用改进的PM滤波器进行进一步滤波达到抑制背景突出目标的目的,最终通过阈值分割实现弱小目标的检测。对比实验结果表明,该算法能够在低信噪比(signal-to-noise ratio,SNR)下实现红外弱小目标图像的背景及边缘有效抑制、使图像的信噪比提高20%,检测能力在原有算法上提高了40%。
In order to achieve effective detection of weak targets in infrared complex background,a filtering algorithm combining morphological Top-hat transform and improved non-linear diffusion（based on Perona-Malik＇s（PM）research）model was proposed to enhance infrared Weak target signal,suppress complex background and noise.The method firstly uses the Top-hat operator in morphological filtering to enhance the target of the image,and then uses the modified PM filter to further filter the morphologically filtered image to achieve the purpose of suppressing the background to highlight the target,and finally the dim target detection is realized by threshold segmentation.The comparison experiments show that the proposed algorithm can effectively suppress the background and edge of the infrared weak target image at low signal-to-noise ratio,increase the signal-to-noise ratio of the image by 20%,and increase the detection ability by 40%in the original algorithm.
作者
陆福星
李夜金
陈忻
陈桂林
饶鹏
LU Fuxing;LI Yejin;CHEN Xin;CHEN Guilin;RAO Peng(Shanghai Institute of Technical Physics,Chinese Academy of Sciences,Shanghai 200083,China;Key Laboratory of Infrared Detection and Imaging Technology,Chinese Academy of Sciences,Shanghai 200083,China;University of Chinese Academy of Sciences,Beijing 100049,China)
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2018年第7期1417-1422,共6页
Systems Engineering and Electronics
基金
装备预先研究基金项目资助课题
