Fig 1.
Precision elimination strategy.
Fig 2.
Lens imaging opposition-based learning.
Table 1.
Compare algorithm parameter settings.
Table 2.
Results obtained by different algorithms on 23 benchmark functions.
Fig 3.
Convergence curves obtained by different algorithms on 23 benchmark functions.
Fig 4.
Ranking distribution and average ranking on 23 benchmark functions.
Table 3.
Results obtained by different algorithms on CEC2022 benchmark functions.
Fig 5.
Convergence curves obtained by different algorithms on CEC2022 benchmark functions.
Fig 6.
Ranking distribution and average ranking on CEC2022 benchmark functions.
Fig 7.
Different algorithms in 23 benchmark functions to obtain partial boxplot.
Table 4.
-value on 23 benchmark functions (dim = 30).
Table 5.
-value on CEC2022 (dim = 20).
Fig 8.
Comparison of computational cost between SBOA and MESBOA.
Fig 9.
Four typical nonlinear transformation function curves.
Fig 10.
Flowchart of low-light image enhancement based on MESBOA.
Fig 11.
Flowchart of low-light image enhancement based on MESBOA.
Fig 12.
Results of low-light image enhancement test.
Table 6.
Evaluation metrics obtained by SBOA and MESBOA.