Low-light image enhancement algorithms can improve the subjective visual quality of low-light images and support the extraction of valuable information for some computer vision techniques. Although many low-light image enhancement algorithms have been developed in recent years, the assessment methods for enhanced images are still open topics. In this paper, we use multi-exposure image sequences and a camera response model to calculate the color distortion of enhanced images. Specifically, we first select the useful information from a multi-exposure image sequence to form a reference image based on the illumination of the enhanced image. Then, we calculate the exposure ratio map between the reference image and the enhanced image for each color channel using the camera response model. Finally, the color distortion is calculated based on the difference between three color channel exposure ratios. Experiment results show that the Pearson’s linear correction coefficient (PLCC) and Spearman’s rank correlation coefficient (SRCC) between the results of our reduced-reference method and that of the full-reference CIE Lab color difference method (∆Eab ) are close to 1. Meanwhile, our method is significantly superior to the existing enhanced image color metrics.