Focusing light through scattering media using the harmony search algorithm for phase optimization of wavefront shaping

Wu, Yulin; Zhang, Xiuda; Yan, Hao

doi:10.1016/j.ijleo.2017.12.196

Cited by 17 publications

(3 citation statements)

References 16 publications

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“…In Vellekoop and Mosk's first demonstration of feedback assisted wavefront shaping, they utilized a simple iterative algorithm (IA) to perform optimization. Since then a variety of new optimization algorithms have been developed and tested, including: partitioning [43], simple genetic [44][45][46][47][48], microgenetic [45], n-parent genetic [49], simple genetic with interleaved segment correction [50], simulated annealing [51,52], particle swarm [53][54][55], transmission matrix estimation [56], fourelement division [57], harmony search [58], and neural networks [59]. While these algorithms approach the optimization problem in several different ways, they were all developed with the goal of faster optimization, better noise resistance, and larger enhancements than obtainable using the iterative algorithm.…”

Section: Introductionmentioning

confidence: 99%

Genetic algorithms for focusing inside opaque media

Anderson

Eilers

2020

J. Opt.

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We characterize the performance of standard and micro genetic algorithms when applied to focusing inside of an opaque media using feedback from a fluorescent guidestar particle. Using this feedback modality we find that the algorithms optimize more quickly (but to a lower enhancement) than when using reflective feedback, with the underlying mechanism being the fluorescence signal’s multimodal nature and lower signal-to-noise ratio. We also find that both algorithms’ performance decrease at very large numbers of bins due to decoherence effects related to a bin-dependent iteration time. To mitigate this effect we implement multithreaded functionality in the genetic algorithms and find that for our specific computer we obtain a 3.3 × improvement in speed utilizing multithreading. These results demonstrate the usefulness of both algorithms for focusing inside of opaque media, which has applications in biological imaging and the study of subsurface chemical reactions in heterogeneous materials.

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Section: Introductionmentioning

confidence: 99%

Genetic algorithms for focusing inside opaque media

Anderson

Eilers

2020

J. Opt.

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“…The harmony search algorithm (HSA) is a MA that was used widely in the last years to solve complex optimization problems with high performance and accuracy. Since the publication of HSA in [15], it has been adapted in applications such as vanishing point detection [16], block matching for motion estimation [17], phase optimization of wavefront shaping [18], etc. The virtues of HSA are a straightforward implementation, good convergence, and low computational cost.…”

Section: Introductionmentioning

confidence: 99%

An Evolutionary Approach to Improve the Halftoning Process

et al. 2020

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The techniques of halftoning are widely used in marketing because they reduce the cost of impression and maintain the quality of graphics. Halftoning converts a digital image into a binary image conformed by dots. The output of the halftoning contains less visual information; a possible benefit of this task is the reduction of ink when graphics are printed. The human eye is not able to detect the absence of information, but the printed image stills have good quality. The most used method for halftoning is called Floyd-Steinberger, and it defines a specific matrix for the halftoning conversion. However, most of the proposed techniques in halftoning use predefined kernels that do not permit adaptation to different images. This article introduces the use of the harmony search algorithm (HSA) for halftoning. The HSA is a popular evolutionary algorithm inspired by the musical improvisation. The different operators of the HSA permit an efficient exploration of the search space. The HSA is applied to find the best configuration of the kernel in halftoning; meanwhile, as an objective function, the use of the structural similarity index (SSIM) is proposed. A set of rules are also introduced to reduce the regular patterns that could be created by non-appropriate kernels. The SSIM is used due to the fact that it is a perception model used as a metric that permits comparing images to interpret the differences between them numerically. The aim of combining the HSA with the SSIM for halftoning is to generate an adaptive method that permits estimating the best kernel for each image based on its intrinsic attributes. The graphical quality of the proposed algorithm has been compared with classical halftoning methodologies. Experimental results and comparisons provide evidence regarding the quality of the images obtained by the proposed optimization-based approach. In this context, classical algorithms have a lower graphical quality in comparison with our proposal. The results have been validated by a statistical analysis based on independent experiments over the set of benchmark images by using the mean and standard deviation.

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“…In feedback-based wavefront shaping, various algorithms have been proposed and demonstrated to search for the optimum phase map, including a stepwise sequential algorithm (SSA), 19 a continuous sequential algorithm (CSA), 20 a partitioning algorithm (PA), 20 a simulated annealing algorithm (SA), 21 a genetic algorithm (GA), 18,22,23 a particle swarm, 22,24 a four-element division, 25 a harmony search algorithms 26 and a Hadamard encoding algorithm (HEA). 27 Each algorithm has its own pros and cons, which has been well discussed in many literatures.…”

Section: Introductionmentioning

confidence: 99%

A thorough study on genetic algorithms in feedback-based wavefront shaping

Luo

et al. 2019

J. Innov. Opt. Health Sci.

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Feedback-based wavefront shaping focuses light through scattering media by employing phase optimization algorithms. Genetic algorithms (GAs), inspired by the process of natural selection, are well suited for phase optimization in wavefront shaping problems. In 2012, Conkey et al. first introduced a GA into feedback-based wavefront shaping to find the optimum phase map. Since then, due to its superior performance in noisy environment, the GA has been widely adopted by lots of implementations. However, there have been limited studies discussing and optimizing the detailed procedures of the GA. To fill this blank, in this study, we performed a thorough study on the performance of the GA for focusing light through scattering media. Using numerical tools, we evaluated certain procedures that can be potentially improved and provided guidance on how to choose certain parameters appropriately. This study is beneficial in improving the performance of wavefront shaping systems with GAs.

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Focusing light through scattering media using the harmony search algorithm for phase optimization of wavefront shaping

Cited by 17 publications

References 16 publications

Genetic algorithms for focusing inside opaque media

Genetic algorithms for focusing inside opaque media

An Evolutionary Approach to Improve the Halftoning Process

A thorough study on genetic algorithms in feedback-based wavefront shaping

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