Fig. 1. Schematic diagram of image acquisition system for runway edge lights

Fig. 2. Structure of the RetinaNet

Fig. 3. Calculation process of standard convolution and depth separable convolution. (a) Standard convolution; (b) depthwise convolution; (c) pointwise convolution

Fig. 4. Structure of the linear inverted residual module. (a) Identity residual block; (b) convolutional residual block

Fig. 5. Structure of the FPN

Fig. 6. Data set image example. (a) Strong natural light image; (b) weak natural light image; (c) image without natural light; (d) image of 1-level light; (e) image of 2-level light; (f) image of 3-level light

Fig. 7. Runway edge light image after data enhancement

Fig. 8. Test results of the test set. (a) Image of 1-level light; (b) image of 2-level light; (c) image of 3-level light; (d) strong natural light image

Fig. 9. Images of runway edge lights with different focal lengths and weather conditions

Fig. 10. Detection results of different models on the same image. (a) Detection results of the model obtained from 3-level light image on 3-level light image; (b) detection results of the model obtained from 1-level light image on 3-level light image