Results of low-light image enhancement test.

<div><p>Metaheuristic optimization algorithms often face challenges such as complex modeling, limited adaptability, and a tendency to get trapped in local optima when solving complex optimization problems. To enhance algorithm performance, this paper proposes an enhanced Secretary Bird O...

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Bibliographic Details
Main Author:	Yuqi Xiong (12343771) (author)
Published:	2025
Subjects:	Biophysics Neuroscience Space Science Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified structural similarity index precise elimination mechanism mean squared error light image enhancement experimental validation shows enhance algorithm performance cec2022 test suite avoid inefficient searches 23 benchmark functions mesboa significantly outperforms mesboa performs better complex optimization tasks numerical optimization complex modeling mesboa provides solution space solution accuracy search range research indicates psnr ), premature convergence practical problems population structure paper proposes noise ratio local optima limited adaptability lens imaging get trapped etc .) eliminating individuals efficient solution effectively constrains convergence speed comparative algorithms boundary control best individual application case
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Results of low-light image enhancement test.

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