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干旱区地理 ›› 2001, Vol. 24 ›› Issue (1): 9-22.doi: 10.13826/j.cnki.cn65-1103/x.2001.01.002

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成像光谱图像的噪声分析与消除方法研究——以北京顺义区成像光谱图像为例

姜小光1, 王长耀1, 王成2   

  1. 1.中国科学院遥感应用研究所, 北京 100101;
    2.南京师范大学地理科学学院, 南京 210097
  • 收稿日期:2000-06-22 修回日期:2000-11-06 发布日期:2025-12-31

NOISE ANALYSIS AND ELIMINATION FOR IMAGING SPECTROMETER DATA

JIANG Xiao-guang1, WANG Chang yao1, WANC Cheng2   

  1. 1. LARSIS, Instit ute of Remote Sensing Applications, CAs, Beijing 100101;
    2. Institute of Geography Science, Nanjing Normal University, Nanjing, 210097
  • Received:2000-06-22 Revised:2000-11-06 Online:2025-12-31

摘要: 以北京顺义区32通道成像光谱数据为例, 从数据的统计参数入手, 分别从数据的方差、动态范围、相关性、直方图等方面分析研究噪声及特点, 在此基础上提出局部邻域自动噪声查找与消除算法。

关键词: 成像光谱数据, 噪声, 消除

Abstract: Noise elimination is one of the important step in image preprocessing. T'his paper, taking the imaging spectrometer data of Shunyi, Beijing as an example, deals with the research on noise analysis and elimination.Statis-tical met hod, combined with image processing technique, is used to analyze the existence and feature of noise. There are two types of noise in imaging spectrometer image of Shunyi.One type takes the form of speckleswhich exist in all the channels at random. The other type takes the form of strips which distribute in dark ob-jects such as river and pond. There are dfferent types noise in remote sensing imagery which influence the quali-ty of image along the scanning direction and appear only in channel 18, 19, 20 and 21. The noise is eliminated bydifferent methods according to the feature of noises.T'he speckle noise is eliminated by median filler quite well. While the second type noise is very special and can not be eliminated by conventional method. Therefore, a localneighboring algorithm is developed to eliminate it. The procedure is: automatically searching the noise along theline of image, when some pixel meets the demand of limit preset, replace its grey value by the average value of 5×5 pixel matrix in neighbor with uniform value. In this way the special noise can be eliminated effectivelywithout damaging the raw data because the algorithm don 't perform any processing on normal pixels.
lt can be seen from the processing result of study area that the proposed method is effective in analyzing andeliminating noise of imaging spectrometer data.

Key words: imaging spectrometer data, noise, elimination.

中图分类号: 

  • TP79