偏振遥感图像的大气校正

为了实现对遥感图像快速、精确的大气校正，提出了一种联合偏振光强度信息和偏振度信息的图像大气校正算法。该算法首先采用矢量偏振辐射传输模型（vectorized linearized discrete ordinate radiative transfer, VLIDORT）建立一个由观测几何、目标偏振信息、大气条件、气溶胶模式等参数组成的查找表，然后通过查找表插值方法对输入的图像进行大气校正。实验结果表明，偏振图像大气校正算法在雾天成像条件下，使得图像对比度提高了41.84%，图像信息熵值提高了0.44，很好地去除了雾对图像的影响。进而说明偏振图像大气校正算法能够很好地还原目标强度信息和偏振度信息，提高图像的对比度，增加图像的信息熵值。

Atmospheric Correction for Polarized Image of Optical Remote Sensing

To carry out a computationally fast and accurate atmospheric correction based on polarized image, an algorithm of atmospheric correction was proposed by combining the intensity and polarization degree information of polarized light. Firstly, based on the vectorized linearized discrete ordinate radiative transfer(VLIDORT) model, a look-up tables (LUTs) which is composed of observation geometry, atmospheric parameters, aerosol model, and surface polarization characteristic were set up. Then the atmospheric correction was carried out through the look-up tables by interpolation method. The experimental results show that the algorithm has a good effect on foggy days,which is a good way to remove the negative impact of fog. After the correction, the image information entropy increased by 0.44 and the contrast increased by 41.84%. And then it is proved that the algorithm can restore the target's intensity and degree of polarization. It also has a good performance on enhancing the image amount of information and contrast.