| 基于线支持区域的闪电通道识别算法 |
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| 引用本文： | 李峰,吕伟涛,李清勇,张舸,马颖,杨俊.基于线支持区域的闪电通道识别算法[J].应用气象学报,2016,27(6):725-733. |
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| 作者姓名： | 李峰 吕伟涛 李清勇 张舸 马颖 杨俊 |
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| 作者单位： | 1.北京交通大学轨道交通数据分析与挖掘北京市重点实验室，北京 100044 |
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| 基金项目： | 资助项目： 国家自然科学基金项目（41475003），国家重大科学仪器设备开发专项（2012YQ11020504）,中国气象科学研究院基本科研业务费项目（2014R015），中央高校基本科研业务费专项基金（2014JBZ003），北京市自然科学基金项目（4142043） |
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| 摘 要： | 提出了一种基于线支持区域的闪电通道识别算法 (LLSR)，该算法首先应用对比度拉伸和高斯匹配滤波方法对闪电通道图像进行预处理，以增强闪电通道的对比度；然后自动检测出包含闪电通道的线支持区域，并用最小外接矩形包含这些区域；最后在各个矩形区域内分别使用最大类间方差Otsu阈值法进行分割，得到闪电通道识别结果。试验结果表明:LLSR具有良好的局部特性和自适应性，它不仅能自动提取低对比度闪电图像的通道，还能自动提取具有复杂背景闪电图像的通道，自动提取结果在视觉上与人眼观测结果一致。且定量评估结果表明:LLSR相比传统算法具有更好的分割精度。
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| 关 键 词： | 闪电图像 通道识别 线支持区域 最大类间方差 阈值法 |
| 收稿时间： | 2016-03-10 |
Lightning Channel Image Recognition Based on Line Support Region |
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| Institution: | 1.Beijing Key Laboratory of Transportation Data Analysis and Mining, Beijing Jiaotong University, Beijing 1000442.Laboratory of Lightning Physics and Protection Engineering, State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 1000813.Chengdu University of Information Technology, Chengdu 610225 |
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| Abstract: | Lightning channel coordinates in digital images are often manually extracted to analyze the development and morphology of lightning channels, but this method is not efficient and its result is often subjective. Therefore, more and more researchers start to investigate approaches to recognize lightning channel information automatically. In general, lightning channel images are complex and diverse because of low contrast, occlusion of clouds, and interference of other environmental factors, so most traditional lightning channel segmentation algorithms do not work well for such lightning images. A new lightning channel segmentation algorithm named LLSR is brought forward based on line support regions. First, Gauss matched filtering and contrast stretching method are applied to enhance the contrast of lightning channels, according to the gray distribution characteristics of cross section of lightning channels. Second, line support regions, which include lightning channels within a minimum enclosing rectangle, are extracted as foreground area by a line segment detection method. In addition, line support regions are expanded in both the main direction and its perpendicular direction. In general, a line support region contains a segment of a lightning channel. Furthermore, it has better contrast between lightning channel and background. Finally, Otsu thresholding method is applied in each line support region to extract lightning channels, because the gray level distribution of each line support region is bimodal. Therefore, lightning channels are segmented from complicated background. A dataset including various types of lightning channel images, are constructed and manually marked to evaluate the proposed algorithm LLSR. Compared with traditional algorithms, global thresholding method (GThres), local thresholding method (LThres), and Canny thresholding method (CThres), the proposed LLSR has higher precision for lightning channel segmentation, and it obtains a better balance between recall rate and false positive rate. Besides, experiment results show that traditional algorithms are not robust enough for all types of lightning images, but the new method demonstrates better generality. LLSR can recognize not only the lightning channels with low contrast but also the lightning channels with complicated background, and the segmentation result is visually consistent with human eyes. |
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| Keywords: | lightning image channel identify line support region Otsu thresholding algorithm |
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