Fig. 1. Flow chart of enhancing algorithm

Fig. 2. Window for side window filtering

Fig. 3. Eight different types of side windows. (a) Left and right side windows; (b) upper and lower side windows; (c) northwest and southwest side windows; (d) northeast and southeast side windows

Fig. 4. Filtering kernel of edge window filtering. (a) Left window; (b) right window; (c) upper window; (d) lower window; (e) northwest side window; (f) northeast side window; (g) southwest side window; (h) southeast side window

Fig. 5. Filtering results of bilateral filtering, guided filtering, and proposed method. (a) Model images of step edge, slope edge, roof edge; (b) curve of data in the 100th line of the image and filtered results; (c) local amplification

Fig. 6. Filtering results of bilateral filtering, guided filtering, and proposed method. (a) Infrared image containing edge area; (b) curve of data in the 284th column of infrared image and filtered results; (c) enlargement of area a; (d) enlargement of area b; (e) enlargement of area c; (f) enlargement of area d

Fig. 7. Basic component processing results and their histograms. (a) Automatic gain control; (b) histogram projection; (c) platform histogram; (d) proposed method

Fig. 8. Results processed by different methods for scenes with strong edges

Fig. 9. Results processed by different methods for scenes with low contrast details

Fig. 10. Results processed by different methods for sky background scene with noise

Fig. 11. Results processed by different methods for scenes with high dynamic range

Table 1. EME results for the test images