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针对MODIS 1B原始数据严重的几何畸变直接影响传统重采样算法精度的具体问题,论文提出了一种新的适应遥感数据空间分布非均匀性的重采样方法——正态采样法。该方法首先采用直接映射法确认纠正后像素点的位置,然后根据卫星扫描角与像素分辨率的空间关系确定搜索窗口,再根据正态分布理论提出的加权插值法计算纠正后像素的属性值。对比分析表明,采用正态采样法处理的图像,信息失真少,精度高,视觉效果好,是一种有效的MODIS数据重采样方法。
Aiming at the specific problems that the severe geometric distortion of MODIS 1B data directly affects the accuracy of traditional resampling algorithms, a new resampling method that adapts to the spatial heterogeneity of remote sensing data is proposed. In this method, the position of the corrected pixel is first confirmed by the direct mapping method. Then, the search window is determined according to the spatial relationship between the satellite scanning angle and the pixel resolution. Then, the weighted interpolation method proposed by the normal distribution theory is used to calculate the corrected pixel attribute value. The comparative analysis shows that the image processed by the normal sampling method has less information distortion, high precision and good visual effect, and is an effective MODIS data resampling method.