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Applied Physics 2023
气泡水平和温度梯度对水下鬼成像的影响
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Abstract:
计算鬼成像(CGI)是一种有望降低水下湍流信道带来的负面影响的方法。然而，基于水下湍流信道的CGI传输系统的理论研究鲜有报道。本文研究了基于水下湍流信道的CGI和压缩感知计算鬼成像(CSCGI)系统的峰值信噪比(PSNR)性能和结构相似度(SSIM)性能。并选取两种典型的强度波动模型作为理论信道模型。所选模型的概率密度函数(PDF)分别服从指数广义Gamma分布(EGG)和指数Gamma分布(EG)。通过设置适当的气泡水平和温度梯度参数，我们获得了上述方案的PSNR性能和SSIM性能以及可视化成像结果。我们的工作为未来研究基于水下湍流信道的实际CGI和CSCGI系统提供了理论参考。
Computational ghost imaging (CGI) is a promising method to reduce the negative effects of underwater turbulent channels. However, the theoretical research of CGI transmission system based on underwater turbulent channel is rarely reported. This paper studies the peak signal-to-noise ratio (PSNR) performance and structural similarity (SSIM) performance of CGI and compressed sensing computational ghost imaging (CSCGI) systems based on underwater turbu-lent channels. Two typical intensity fluctuation models are selected as theoretical channel models. The probability density function (PDF) of the selected model obeys exponential generalized Gamma distribution (EGG) and exponential Gamma distribution (EG), respectively. By setting the appropriate bubble level and temperature gradient parameters, we obtain the PSNR performance, SSIM performance and visual imaging results of the above scheme. Our work provides a theoretical reference for future research on actual CGI and CSCGI systems based on underwater turbulent channels.
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