首页> 外文会议>ACRS 2011;Asian conference on remote sensing >EFFECT OF SPECTRAL CHANGE WIDTH IN RADIOMETRIC NORMALIZATION OF MULTITEMPORAL SATELLITE IMAGERY METHODES EFFICIENCY
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EFFECT OF SPECTRAL CHANGE WIDTH IN RADIOMETRIC NORMALIZATION OF MULTITEMPORAL SATELLITE IMAGERY METHODES EFFICIENCY

机译:光谱变化宽度在多时相卫星成像方法辐射归一化效率中的作用

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Multitemporal satellite optical images of the same terrain are very applicable in monitoring and quantifying large scale land cover change over time. These images are confounded in terms of radiometric consistency due to differences in sensor calibration parameters, illumination, geometric condition and variation in atmospheric effects. To analyze these images, it is necessary to omit mentioned differences. Relative radiometric normalization is used to prepare these images for stated applications. In this paper, different relative radiometric normalization methods are compared with each other. Images of Landsat-5 thematic mapper (TM) and Landsat-7 enhanced thematic mapper plus (ETM+) captured from Iran are used for this comparison. The results of various techniques have been evaluated with both visual inspection and statistical analysis i.e. Root Mean Square Error (RMSE) and Universal Quality Indicator (UQI) value between each pair of analogous band. Obtained results show intensity value of spectral changes affects quality of normalization. In images which have small area with intensified spectral changes, MS, HM and MM methods produce better results; while in images with intensified changes covering large area, PIF method generates the best results. Also among mentioned methods, MS method is the most stable with respect to changes.
机译:同一地形的多时相卫星光学图像非常适用于监视和量化随时间变化的大规模土地覆被变化。由于传感器校准参数,照度,几何条件和大气影响的变化,这些图像在辐射一致性方面会造成混淆。要分析这些图像,有必要忽略提到的差异。相对辐射归一化用于为指定应用准备这些图像。本文将不同的相对辐射归一化方法进行了比较。从伊朗捕获的Landsat-5主题映射器(TM)和Landsat-7增强型主题映射器(ETM +)的图像用于此比较。已通过目视检查和统计分析(即每对相似频带之间的均方根误差(RMSE)和通用质量指标(UQI)值)评估了各种技术的结果。获得的结果表明,光谱变化的强度值会影响归一化的质量。在光谱变化较小的小面积图像中,MS,HM和MM方法可产生更好的结果。而在大面积变化剧烈的图像中,PIF方法可产生最佳效果。在所提及的方法中,相对于变化,MS方法也是最稳定的。

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