Natural color appearance is the key problem of color night vision field. In this paper, the color mood of daytime color image is transferred to the monochromic night vision image. This method gives the night image a natural color appearance. For each pixel in the night vision image, the best matching pixel in the color image is found based on texture similarity measure. Entropy, energy, contrast, homogeneity, and correlation features based on co-occurrence matrix are combined as texture similarity measure to find the corresponding pixels between the two images. We use a genetic algorithm (GA) to find the optimistic weighting factors assigned to the five different features. GA is also employed in searching the matching pixels to make the color transfer algorithm faster. When the best matching pixel in the color image is found, the chromaticity values are transferred to the corresponding pixel of the night vision image. The experiment results demonstrate the efficiency of this natural color transfer technique. Natural color appearance is the key problem of color night vision field. In this paper, the color mood of daytime color image is transferred to the monochromic night vision image. This method gives the night image a natural color appearance. vision image, the best matching pixel in the color image is found based on texture similarity measure. Entropy, energy, contrast, homogeneity, and correlation features based on co-occurrence matrix are combined as texture similarity measure to find the corresponding pixels between the two images. We use a genetic algorithm (GA) to find the optimistic weighting factors assigned to the five different features. GA is also employed in searching the matching pixels to make the color transfer algorithm faster. found, the chromaticity values ​​are transferred to the corresponding pixel of the night vision image. The experiment results demonstrate the efficiency of this natural co lor transfer technique.