针对不存在天空区域的偏振遥感图像，提出基于独立成分分析的大气校正算法。根据大气光和场景光高频信息的独立性，由独立成分分析和互信息最优化原则估算大气偏振度，再结合源图像中的先验知识和大气散射物理模型估算无穷远处大气光强。通过实验对比分析，得到的大气信息结果与理论值相匹配，验证了大气信息估算的合理性。同时，为抑制大气介质造成的遥感图像退化影响，提出基于模糊规则修正线偏振度，校正大气光信息A ，改善了图像质量。校正后的偏振遥感图像更准确地反映了地物目标特征，提高了目标探测和识别能力。

when the sky is not in the field of view, the atmospheric correction algorithm based on independent component analysis is proposed. According to the independence of the high frequency information of the atmosphere and scene light, the polarization degree of atmosphere is estimated by independent component analysis and mutual information optimization principle, and the airlight intensity at infinity is estimated with prior knowledge of the source image and atmospheric scattering physical model. Through experimental contrast analysis, the obtained atmospheric information results match the theoretical value, and the reasonability of atmospheric information estimation is verified. Meanwhile, for the influence of sensing image degradation caused by atmospheric medium, the linear polarization degree is fixed based on fuzzy rule, the airlight information is corrected, and the image quality is improved. The polarization remote sensing image reflects the terrain target characteristics more accurately after correction, and the ability of target detection and recognition is improved.