Polarization provides valuable physical information, making it beneficial for various computer vision tasks. However, haze reduces both the color and polarization information of a scene. While existing single-image dehazing methods can restore color information, they are poor at recovering polarization information. Furthermore, current polarization-based dehazing approaches neglect the physical mechanisms of polarization degradation, resulting in inaccurate reconstruction of polarization information. In this paper, we propose a novel polarization dehazing algorithm, along with a polarization degradation model, to accurately recover both polarization and color information. First, we combine two key characteristics (the polarization achromatism prior and polarization attenuation prior) with the polarization degradation model to precisely reconstruct the scene's polarization. Then, we utilize the reconstructed polarization information to recover the color information of the scene. Finally, a multi-scale fusion optimization framework is introduced to further enhance the image quality. Our method shows excellent performance on both real-world indoor and outdoor polarized images, outperforming existing dehazing algorithms in both objective evaluation metrics and subjective visual assessment.