Infrared imaging technology can work a round the clock,ignoring the interference of weather factors,because it relies o n the temperature difference and thermal emissivity of the target to image.It al so has obvious disadvantages,such as high brightness but fuzzy details,low contr ast between the target and the background,smooth edges and general visual effect .Polarized images can obtain multi-dimensional details such as target and backg round roughness,water content,physicochemical properties and texture features be cause they only retain the special imaging mechanism of incident light in a spec ific direction.However,polarized images are generally low in brightness due to t he filtering of light in most directions.Aiming at the problem about weak inform ation and low contrast of single polarization parameter image,an infrared polari zation image fusion algorithm based on non-subsampling shear wave transform (NS ST) is proposed to effectively improve target recognition in complex background. First of all,the image of polarization degree and polarization angle are fused u sing an improved regional variance method to obtain the initial fusion image.The n perform NSST decomposition processing on the initial image and the infrared in tensity image,the low frequency component adopts the fusion rule that combines t he regional correlation degree and regional variance,while the fusion rules of t he high frequency component resort the regional characteristic energy.Experiment al results show that the subjective visual effect of this algorithm is excellent ,and the objective evaluation index is also better than other algorithms.