李荣华, 唐智超, 朴俊峰, 李宏亮. 偏振参数最优重构的水下降质图像清晰化方法[J]. 红外与激光工程, 2021, 50(6): 20200426. DOI: 10.3788/IRLA20200426
引用本文: 李荣华, 唐智超, 朴俊峰, 李宏亮. 偏振参数最优重构的水下降质图像清晰化方法[J]. 红外与激光工程, 2021, 50(6): 20200426. DOI: 10.3788/IRLA20200426
Li Ronghua, Tang Zhichao, Piao Junfeng, Li Hongliang. Underwater degraded image–sharpening method based on optimal polarization parameter reconstruction[J]. Infrared and Laser Engineering, 2021, 50(6): 20200426. DOI: 10.3788/IRLA20200426
Citation: Li Ronghua, Tang Zhichao, Piao Junfeng, Li Hongliang. Underwater degraded image–sharpening method based on optimal polarization parameter reconstruction[J]. Infrared and Laser Engineering, 2021, 50(6): 20200426. DOI: 10.3788/IRLA20200426

偏振参数最优重构的水下降质图像清晰化方法

Underwater degraded image–sharpening method based on optimal polarization parameter reconstruction

  • 摘要: 针对水体浑浊情况下,水中悬浮粒子对光的吸收和散射作用造成图像模糊、对比度低等问题,提出了一种偏振参数最优重构的水下降质图像清晰化方法。首先,通过局部最小值滤波估算水下背景光图像,引入 Stokes 矢量原理计算偏振度,通过归一化互信息进一步优化偏振度信息,获取成像区域最优的重构偏振参数;其次,采用形态学的方法重建图像自动估计水下无穷远处背景光值;最后,搭建了水下环境模拟平台,通过单通道偏振探测器实时获取水下偏振图像;为了验证算法的有效性,通过三种客观评价指标与其他复原方法进行比较,结果显示算法效果优于其他的水下图像复原方法。

     

    Abstract: In order to solve the problems of blurred image and low contrast caused by the absorption and scattering of underwater light by turbid water, an algorithm of underwater image optimal restoration based on global polarization parameter estimation was proposed. Firstly, the local minimum filter was used to estimate the underwater background light image, Stokes vector principle was introduced to calculate the degree of polarization image, and normalized mutual information was used to further optimize the degree of polarization information, to obtain the best reconstructed polarization parameters in the imaging region. Secondly, a method of image reconstruction based on morphology was used to estimate the infinite underwater background light intensity values automatically. Finally, the underwater simulated environment platform was built, and the underwater polarization image was acquired in real time through a single channel fast rotating polarization detector. In order to verify the effectiveness of the algorithm, the three objective evaluation indexes were adopted as quantification to evaluate indexes factors. The results show that the algorithm is better than the other underwater image restoration methods.

     

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