In view of the low contrast, poor details and low color saturation of low-illumination images, by analyzing the non-linear relationship between the subjective brightness sensation of the human eye and the transmission characteristics of the receptive field in the retinal ganglion cells of the human eye, a bionic image enhancement algorithm combining top-hat transformation and bottom-hat transformation was proposed. Firstly, the RGB (Red, Green, Blue) color space of low-illumination image was converted into HSV (Hue, Saturation, Value) space, and the global brightness logarithmic transformation was performed on the brightness component. Secondly, the retinal neuron receptive wild tri-Gaussian model was used to adjust the contrast of the local edge of the image. Finally, top-hat transformation and bottom-hat transformation were used to assist the extraction of background with high brightness. The experimental results show that the low-illumination images enhanced by the proposed algorithm have clear details and high contrast, without the problems of uneven illumination and image depth of field in the images captured by the device. These enhanced images have high color saturation and strong visual sensation effect.