ing at the problem of the severe image degradation under a low-light condition, a low-light image enhancement algorithm based on deep convolutional neural network (DCNN) is proposed. The training sample is synthesized by this algorithm according to the Retinex model. Then, the original low-light image is converted from RGB (Red Green Blue) space to HSI (Hue Saturation Intensity) color space. The luminance component is enhanced by using the DCNN while keeping the chrominance component and the saturation component unchanged. Finally, the image is turned back to the RGB space from HSI color space to get the finally enhanced image. The experimental results show that, compared with the existing excellent image enhancement algorithms, the proposed algorithm can not only effectively enhance the brightness and the contrast, but also can avoid the color distortion and the over-enhancement, and both the subjective vision and objective evaluation index are further improved.