The balanced enhancement for color images refers to the ability of improving the visual quality of both highlights and dark areas. To this end, a symmetric Naka-Rushton formula (SNRF) is proposed. Particularly, SNRF is symmetric around a pixel-wise threshold which is devised as the adaptive criterion for highlights. Treating RGB channels separately, SNRF regulates each pixel according to the anisotropic local intensity, thus avoiding halos and protecting uniform areas. Further, the color-constancy extension of SNRF (SNRFCC) is presented by incorporating conventional image statistics with the adaptive threshold. Different from traditional color-constancy algorithms that focus on color correction, SNRFCC accomplishes color and lightness adaptation simultaneously. Finally, a postprocessing technique is designed to compensate for the slightly compressed contrast due to the balanced adaptation. Compared with other tone-mapping methods, SNRF achieves more vivid color and details especially in highlights. Besides, comparisons with other color-contrast enhancement algorithms confirm that SNRFCC features the merit of less residual color cast when implementing color constancy on images under varying light.