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中国物理学会期刊

基于自适应遗传算法的背向散射光场调控

CSTR: 32037.14.aps.74.20250455

Backscattered light field control based on self-adaptive genetic algorithm

CSTR: 32037.14.aps.74.20250455
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  • 调控经散射介质散射后的光场在生物组织成像、军事反恐和光信息传输等领域具有潜在的应用价值. 然而, 经散射介质反射后的光子传播方向变得无序, 导致携带光信息的波前被扰乱. 将一种新的波前振幅调制方法即自适应遗传算法(self-adaption genetic algorithm, SAGA)引入到背向散射光场调控中. 根据环境变化, 种群自适应的选择基因的突变或交叉, 极大地提高了寻找最优解的收敛速度. 通过实验研究验证了SAGA在背向散射光场调控方面的有效性, 并表明相较于遗传算法(genetic algorithm, GA), SAGA在调控速度和抗噪声方面都存在明显优势. 研究结果表明, SAGA在较少的迭代次数内即可获得高对比度的光聚焦和图像投影, 并收敛于最优解. 相较于GA, 其在进行散射聚焦和图像投影时的调控速度分别快8.3倍和14.38倍. 这种快速的散射光场调控技术为光信息传输领域的研究提供了新思路, 具有广泛的应用潜力.

     

    Modulating the light field scattered by scattering media has potential applications in biological tissue imaging, military anti-terrorism, and optical information transmission. However, light reflected by complex scattering media, such as biological tissues, clouds and fog, multi-mode fiber, and white paper, will produce disorderly scattering, and then disturb the wavefront of incident light. It has always been the main obstacle to optical imaging and effective information transmission. Therefore, the control of backscattered light field is also a research field worthy of attention, which is of great significance for the transmission of non-line-of-sight optical information. It is also very important to find a method of efficiently controlling backscattered light field for the breakthrough of related applications. It has been found that iterative wavefront shaping technology is an effective solution, which gradually modulates the amplitude or phase distribution of wavefront according to the feedback of the light intensity distribution in the target area of charge coupled device (CCD). An improved genetic algorithm, self-adaptation genetic algorithm (SAGA), is proposed, which can be used to rapidly modulate the backscattered light field. The amplitude distribution of wavefront is controlled, which makes it form the required pattern at the target position through the interference of light. During the implementation of the algorithm, the SAGA performs gene crossover and mutation separately, and selects gene crossover and mutation operations according to the number of iterations. At the beginning of evolution, the probability of selecting gene mutations is higher because the population needs to adapt to the environment, while at the end of evolution, the probability of selecting gene mutations is lower because it gradually adapts to the environment. In the experimental measurement, the effective modulation area of digital-micromirror device (DMD) is 1024×1024, which is divided into 64×64 modulation segments by pixel merging. Each segment number is assigned a value of 0 or 1. Focusing and image projection performance of scattered light field are evaluated based on peak-to-background ratio (PBR) and Pearson correlation coefficient (Cor), respectively. By comparing the scattered light focusing and image projection of SAGA and genetic algorithm (GA), it is found that SAGA can accurately control the backscattered light field and converge to the optimal value in a few iterations. After 1000 iterations, the GA still has a clear speckle background. With the increase of iteration times, GA will also show bright focus and clear projection image. Compared with GA, SAGA has a modulation speed that is 8.3 times faster in light focusing and 14.38 times faster in image projection, greatly improving the modulation speed of the scattered light field. The fast control technology for scattered light field can lead to numerous new optical communication applications and offer fresh insights into the study of optics and information science.

     

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