For the inherent misregistration between the two sets of spectral bands and its effect on the spectral purity of each pixel hyperspectral imagery, a sub-pixel image registration method was proposed based on the characteristic of the hyperspectral imagery. Firstly, band selection and principal component transformation were used to process the Visible Near Infrared (VNIR) and Short Wave Infrared (SWIR) spectral bands, and the first principal component was chosen as the input image. Then, the input image was evenly divided into the image block with a certain overlap rate. Furthermore, the phase correlation method was taken to estimate the sub-pixel motion and the phase correlation coefficient was used to remove a few mismatches in the correlation output and to generate an optical flow field. Finally, the spectrometer images were registered by the calculated optical flow filed. Experimental results show that the accuracy of registration is superior to 0. 1 pixel, which meets the accuracy requirement of advanced image processing.%针对超光谱成像遥感存在的光谱仪图像间失配变形,影响地物目标光谱信息纯度的问题,提出了一种结合超光谱图像特点的亚像素配准方法来校正图像间的失配变形.首先,对待配准的可见光近红外(VNIR)和短波红外(SWIR)光谱仪图像分别进行波段选择和主成分变换,将变换后的第一主分量图像作为待配准图像.然后,将待配准图像均匀划分为具有一定重叠率的图像块,利用相位相关方法估计对应图像块的亚像素平移参数,通过相位相关系数剔除错误的平移参数估计生成图像的光流场.最后,通过光流场来实现光谱仪图像的配准.实验结果显示,该方法配准精度优于0.1pixel,满足超光谱图像后续处理对配准精度的要求.
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