Traditional color night vision fusion methods usually suffered from the problems of blurry visual effects and the low color contrast between the target and the background, in order to obtain the more ideal color fusion effect, an improved color fusion method based on Non-subsampled Shearlet Transform (NSST) and color contrast enhancement was proposed. Firstly, NSST was employed to decompose the infrared and visible source images, respectively, and then the gray-level fusion image was obtained according to the self-adaptive fusion rules based on the S function and the local directional contrast. Secondly, the gray fusion image was assigned to the Y component, and the difference of the source images was respectively assigned to the U and V component, and then the false color fusion image was generated in YUV space. Finally, a natural daylight color image with similar color feature to the gray fusion image was selected as the reference image, meanwhile, transferring the color feature of the reference image to the false color fusion image based on the nonlinear color transfer technique in the uncorrelated YUV space, so as to enhance the color contrast of the hot target and cold background. Compared with the methods in recent years, Experimental results showed that the color fusion result based on ours contained more abundant details, and the hot target was highlighted. This method is applied to the field of color night vision that can make for enhancing the situation awareness and improve the target detectability.