Using correlation calculation to further subdivide gray project data, precision of image motion characteristic position information was improved, and sub pixel image motion vector could be gotten.
而通过采用相关计算进一步细分灰度投影数据，可以提高图像运动特征位置信息的精度，获得亚像元级的图像运动矢量。
With the larger pixel scale, standard deviation of LAI increased, but the correlation coefficients of vegetation index and LAI are not reduced.
随着像元尺度变大，LAI的标准差增大，但植被指数与LAI的相关系数并不降低。
A zero-padding algorithm based on correlation-based image analysis theory with the accuracy of sub-pixel class was presented to determine the benchmarks in different digital images.
基于图像相关分析理论提出了一种新的补零相关分析算法以确定不同数字图像上的相关标记点，其测量精度可达亚像素量级。
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