A fusion method was proposed to solve the problem that the single-energy X-ray cannot detect the complete decoration and disease information of the corroded ancient bronze mirror due to the uneven thickness of the mirror edge and the mirror center area. The method combined intuitionistic fuzzy set entropy measure and salient feature detection to fuse ancient bronze mirror X-ray images. Firstly， the effective guided filtering was introduced to enhance the contrast of the decorative structure of high-energy X-ray images. Secondly， a three-scale decomposition model was designed by using joint bilateral filtering and structure-texture decomposition strategy. The model extracted the energy layer， residual layer and detail layer information of different energy X-ray images. Then， the energy layer obtained the fused energy image through the l1-max rule. The residual layer used the intuitionistic fuzzy set entropy measure to construct a small-scale texture feature fusion module. And the detail layer combined the extended difference-of-Gaussians and spatial frequency enhancement operator to construct a composite saliency feature detection strategy. Finally， the energy fusion map， residual fusion map， and detail fusion map were added to obtain the final fusion result. The experimental results show that the six objective evaluation indexes AG， SF， SD， SCD， NAB/Fand SSIM of this method are improved by 22.19%， 22.66%， 15.01%， 44.69%， 17.07%， and 21.46% on average， respectively， compared with the other methods. The fusion results can effectively retain the clear decorative details of the ancient bronze mirror and the key features of the disease cracks. And it outperforms other comparison methods in terms of contrast and structure retention.