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基于图像退化模型的天气现象识别 被引量:4

The Weather Phenomena Identification Based on Image Degradation Model
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摘要 在不同的天气条件下,由于气溶胶对光波的散射作用,通过成像系统获得的图像都会有一定程度的退化。利用图像的退化模型可以获取与天气现象相关的参量,从而达到识别天气的目的。对不同天气条件下得到的同一场景图进行研究,运用多垂线检测法,检测出不同天气条件下直线模糊边缘上的灰度值,采用Sigmoid函数拟合出刃边函数,进而求出线扩散函数。通过分析线扩散函数的变化规律,总结出其与天气现象之间的紧密联系。测试结果表明,应用该方法对于晴天、薄雾、雨、霾、沙尘暴等天气现象具有一定的判别效果。 The images obtained from imaging system will have a certain degree of degradation due to the role of aerosols scattering on light under different weather conditions.The weather-related parameters can be acquired by using the degradation model of image and to achieve?the purpose of identifying the weather.In this paper,the same scene images obtained in different weather condition were studied,the method of multi-vertical detection was used to detect gray value on straight blur edge,and obtained the edge spread function fitted by Sigmoid function,then got the line spread function.Ultimately The relationship between weather phenomena and the line spread function is concluded by analyzing the variation of the line spread function.Test results show that the method presented in this paper have a certain discrimination effect for the sunny,mist,haze,rain, dust storms and other weather phenomena.
作者 宋晓建 杨玲
出处 《成都信息工程学院学报》 2011年第2期132-136,共5页 Journal of Chengdu University of Information Technology
关键词 天气条件 模糊边界 散射 天气现象识别 线扩散函数 weather condition blur edge scatter weather phenomena identification line spread function
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  • 1刘凯,黄峰,寇正.基于纹理和区域特征的台风卫星云图分割方法[J].计算机工程与应用,2004,40(33):219-220. 被引量:4
  • 2洪光烈,张寅超,周孟然,曹开发,周军.基于Raman激光雷达反演大气污染气体浓度几种方法[J].光谱学与光谱分析,2006,26(7):1249-1252. 被引量:13
  • 3赵忠明,朱重光.遥感图象中薄云的去除方法[J].环境遥感,1996,11(3):195-199. 被引量:65
  • 4Tabatabai A J, Mitchell O R. Edge location to subpixel values in digital imagery [ J ]. IEEE Trans on Pattern Analysis and Machine Intelligence, 1984,6 ( 2 ) : 188- 201.
  • 5Lyvers E P, Mitchell O R, Akey M L, et al. Subpixel measurements using a moment-based edge operator [ J ]. IEEE Trans on Pattern Analysis and Machine Intelligence, 1989,11 ( 12 ) : 1 293-1 309.
  • 6Ghosa S, Rajiv M. Orthogonal moment operators for subpixel edge detection [ J ]. Pattern Recognition, 1993,26 (2) : 295 -306.
  • 7Hussmann S,Ho T H. A high-speed subpixel edge detector implementation inside a FPGA [ J ]. Real-Time Imaging,2003,9(5 ) :361-368.
  • 8Truchetet, F, Nicolier F, Laligant O. Subpixel edge detection for dimension control by artificial vision [ J ]. Journal of Electronic Imaging,2001,10:234-239.
  • 9Jensen K, Anastassiuo D. Subpixel edge localization and the interpolation of still images [ J ]. IEEE Trans on Image Processing, 1995,4 ( 3 ) : 285- 295.
  • 10Hueckel M F. An operator which locates edges in digitized pictures [ J ]. Journal of the Association for Computing Machinery, 1971,18 ( 1 ) : 113-125.

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