Aiming at the problem of low detection accuracy due to unclear targets of ships at sea,this paper proposes a fusion method of ship infrared and infrared polarization images based on a deep learning framework to enhance the weak targets of ships at sea and improve the detection accuracy.Firstly,the source image is divided into ship contour part and feature part,and the contour part is fused by weighted average strategy,and the ship polarization image is denoised by using non-local mean.The feature part is extracted using VGG network,and then the fused image is reconstructed.Compared with the traditional image fusion methods,the proposed method can retain more infrared and polarization features of the ship,so that the fused image information is enhanced and has better contrast and signal-to-noise ratio,which provides a new method for ship target detection in complex sea surface background.