摘要
边界层辐合线具有很强的气象风暴灾害的预示能力,它在多普勒雷达图像上表现为一条蜿蜒的、可能有岔路的、宽度不定的、取值变化的、若隐若现的带状区域.为此,提出一种"探测窗"协同加深"印象"算法,用于提取这种具有复杂背景的非规则带状区域.其中,探测窗探身于复杂对象的局地,用以击中疑似局部目标区,并将区域形态、取值等特点纳入探测准则之中,加深"印象"法有利于进一步地去伪存真.实验表明,该算法可以将落入值域的各种边界层辐合线提取出来.
PBL convergent lines have strong ability to predict weather storms, which are belt-shaped regions with winding, possibly branching, uncertain width and changing value in the Doppler radar images. In the paper, an algorithm including ＂detection window＂ and deepening ＂impression＂ was proposed for extracting the irregular beltshaped region from complex background. The detection window is set in local areas with complex object, hit them, and turn their features such as shapes and values into the detection criteria. The method of deepening ＂impression＂ helps eliminate false PBL convergent lines and keep true ones. The experimental result shows that various PBL convergent lines falling into the range can be extracted by the algorithm.
出处
《天津大学学报》
EI
CAS
CSCD
北大核心
2012年第2期135-139,共5页
Journal of Tianjin University(Science and Technology)
基金
公益性行业(气象)科研资助项目(GYHY200706004)
天津市自然科学基金资助项目(09JCYBJC07500)
中国气象局气象探测中心:新一代天气雷达业务建设软件开发资助项目
关键词
图像分割
形状识别
边界层辐合线
探测窗
image segmentation
shape recognition
PBL convergent line
detection window
