The paper aims to propose a new color image fusion algorithm based on NSST and IHS color space to solve the problem that the traditional fusion algorithm of infrared and color visible images cannot give good consideration to the fusion quality of image clarity, contrast and color distortion. Firstly, the RGB image of the source color visible image was transformed into the IHS color space of the least correlation among the channels, and the luminance and chroma components were separated. Secondly, the brightness components of color visible image and infrared image were decomposed by NSST. The low-frequency coefficients obtained by NSST decomposition were selected based on adaptive Gaussian fuzzy logic function, and the high-frequency coefficients were selected based on the absolute value of the pixel points. Then the selected low and high frequency coefficients were inversely transformed by NSST, and the fused image was taken as a new luminance component, and then inversely transformed back to RGB space by combining the existing chroma components to get the final fused image. The fusion of infrared and color visible images in two scenes was simulated. Compared with LPT, SWT and NSCT, subjective evaluation and objective evaluation indexes such as IE, AG, SF and SD showed that the scene details were the clearest, the infrared hidden objects had the highest contrast, and the color was not distorted obviously. The image fusion quality was the highest. Compared with the traditional infrared and color visible image fusion, the proposed algorithm integrally improves the quality of the fused image, showing the superiority of the algorithm.