摘要
针对线阵CCD立靶测试系统采集到的弹丸图像背景复杂、目标信号弱及信噪比低等问题,文中基于动态背景特性及弹丸图像特征,利用双模板复杂度分析方法,建立了图像加权信息熵处理模型,对图像背景进行抑制并增强弹丸信号;提出基于复杂度的自适应门限分割算法,利用最小二乘法构建灰度分布模型,分割并处理信息熵差值图像.对实弹测试图像进行了检测,检测结果表明,文中算法准确有效的提取出线阵CCD图像中的高速弱小目标,为复杂背景下高速弱小目标的提取提供了一种有效的方法.
The linear CCD testing system has some disadvantages of complicated image background,weak target signal and low signal to noise ratio.In order to suppress the image background and enhance the projectile signals,an image weighted information entropy model was established on the basis of the dynamic background characteristics and projectile image features and by the double template complexity method.A complexity based adaptive threshold segmentation algorithm was put forward and a gray distribution model was built by using the least squares to segment and process the information entropy difference image.Through a live fire experiment and image processing,the results show that the algorithm proposed in this paper can effectively extract high speed and small targets in linear CCD images.The research provides an effective method for extracting high speed and small targets in complex background.
作者
孙磊
李静
王泽民
SUN Lei;LI Jing;WANG Zemin(School of Electronic Information Engineering,Xi’an Technological University,Xi’an 710021,China)
出处
《西安工业大学学报》
CAS
2017年第11期807-812,共6页
Journal of Xi’an Technological University
