A wave-front shaping optimization algorithm is proposed to image through scattering media with higher accuracy. Pearson correlation coefficient (PCC), structural similarity (SSIM), and gradient structural similarity (GSSIM) are introduced as the loss functions to recover images. We have concluded that GSSIM has the optimal detail recovery performance among complex multivalued targets, followed by SSIM and PCC. To find the optimal phase mask, we propose the squirrel search algorithm and compared it with two classical global optimization algorithms including the genetic algorithm, the simulated annealing algorithm, and the commonly used continuous sequence algorithm. The simulation and experimental results show that the proposed squirrel search algorithm has a faster convergence speed and higher robustness and stability, which indicates an improved reconstruction quality. This algorithm will help realize imaging through scattering media better and quicker, which is meaningful in dynamic biological tissue imaging and related fields such as optical detection. |
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CITATIONS
Cited by 1 scholarly publication.
Optimization (mathematics)
Image restoration
Scattering media
Detection and tracking algorithms
Reconstruction algorithms
Light scattering
Speckle pattern