The low-contrast images taken by digital cameras or camera phones are not always satisfactory due to the limitation of the capturing devices or improper illumination/exposure conditions. Conventional image contrast enhancement methods may either fail to produce satisfactory and undistorted images, or they cannot improve every region of interest appropriately, especially faces. In this paper, a histogram equalization (HE) approach exploiting the just-noticeable-difference (JND) model of the human visual system (HVS), denoted by JND-HE, is proposed for generic image contrast enhancement. Further, the proposed JND-HE approach is combined with the exposure correction (EC) method (denoted by JND-HE-EC) for face image enhancement. The proposed JND-HE-EC approach can improve the contrast in face regions and provide proper illumination in the background. Experimental results on both generic images and faces have shown that our proposed approach can produce more pleasing and appealing enhanced images than other methods.