Fig. 1. Infrared maritime images under backlight condition

Fig. 2. Histograms of sub-images in Fig. 1

Fig. 3. Target detection results under different maritime conditions using classical LCM. (a) Target detection result under backlight condition with ω₁=9 and k=3; (b) target detection result under backlight condition with ω₁=27 and k=3; (c) target detection result under heavy wave interference with ω₁=7 and k=3; (d) target detection result under heavy fog with ω₁=9 and k=3

Fig. 4. Schematic diagram of original histogram modification

Fig. 5. Results of new histogram equalization

Fig. 6. Structural element in filter and edge information after amplification. (a) Structural element in filter; (b) result of edge information of #1 in Fig.1 amplified by 10 times; (c) result of edge information of #3 in Fig.1 amplified by 10 times

Fig. 7. Flowchart of HEPLEF algorithm

Fig. 8. Enhancement results of HEPLEF algorithm. (a) Entire result and local target region of #1 in Fig.1; (b) enhancement result and local target region of #1 in Fig.1; (c) entire result and local target region of #3 in Fig.1; (d) enhancement result and local target region of #3 in Fig.1

Fig. 9. Comparison of enhancement results before and after edge information fusion. (a) After edge information fusion; (b) before edge information fusion

Fig. 10. Enhancement result of #4 in Fig. 1 by HEPLEF algorithm. (a) Original image; (b) enhancement result

Fig. 11. Principle for target detection based on local contrast saliency and minimum target detection unit under single scale. (a) Principle for target detection based on local contrast saliency; (b) minimum target detection unit under single scale

Fig. 12. Schematic diagram of target detection unit with multiple scale

Fig. 13. Pseudocode of LCMMBC algorithm

Fig. 14. Schematic diagram of target detection result and local contrast saliency by LCMMBC algorithm. (a) Schematic diagram of target detection result; (b) schematic diagram of local contrast saliency

Fig. 15. Comparison of enhancement results for #1 in Fig. 1 obtained by different algorithms. (a) Classical histogram equalization algorithm; (b) MMBEBHE algorithm; (c) ETHE algorithm (T_threshold=5); (d) Retinex algorithm (k=7)

Fig. 16. Comparison of enhancement results for #3 in Fig. 1 obtained by different algorithms. (a) Classical histogram equalization algorithm; (b) MMBEBHE algorithm; (c) ETHE algorithm (T_threshold=5); (d) Retinex algorithm (k=7)

Fig. 17. Target recognition result and three-dimensional diagram of local contrast saliency for #1 in Fig. 1 with w₁=9 and k=2.(a) Target recognition result; (b) three-dimensional diagram of local contrast saliency

Fig. 18. Target recognition result and three-dimensional diagram of local contrast saliency for enhancement result of #1 in Fig. 1 with w₁=9 and k=2. (a) Target recognition result; (b) three-dimensional diagram of local contrast saliency

Table 1. A_G of original image and enhancement algorithms

Table 2. Comparison of L_CG of different enhancement algorithms

Table 3. Comparison of target detection rates and target false alarm rates between different algorithms unit: %