Aiming at the problems of low light, low contrast, and high noise caused by shadows, a polarization distance intensity (PDI) model fused with the "hue-saturation-intensity" color space (HSI color space) is proposed based on the theory and algorithm of polarization distance using the biological polarization vision mechanism for reference to improve the detection and recognition accuracy of targets under shadows. The model uses the angle of polarization information as the estimation method to set the threshold range, fuse the polarization distance information and the original light intensity information into a new intensity channel, and fuse with the original hue and saturation information to finally obtain the mapping result of the PDI model. The actual measurement experimental device was set up, and four groups of comparative experiments were conducted. Compared to the other three existing target enhancement algorithms, the proposed algorithm achieves significant improvement in gray contrast, signal-to-clutter ratio, and Fish distance indicators, and could improve the difference between the target and the background under shadow significantly.