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Underwater image sharpening based on structure restoration and texture enhancement

机译：基于结构恢复和纹理增强的水下图像锐化

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摘要

Light can be absorbed and scattered when traveling through water, which results in underwater optical images suffering from blurring and color distortion. To improve the visual quality of underwater optical images, we propose a novel, to the best of our knowledge, image sharpening method. We utilize the relative total variation model to decompose images into structure and texture layers in a novel manner. On those two layers, the red-blue dark channel prior (RBDCP) and detail lifting algorithms are proposed, respectively. The RBDCP model calculates background light based on brightness, gradient discrimination, and hue judgment, which then generates transmission maps using red-blue channel attenuation characteristics. The linear combination of the Gaussian kernel and binary mask is employed in the proposed detail lifting algorithm. Furthermore, we combine the layers of restoration structure and enhancement texture for image sharpening, inspired by the concept of fusion. Our methodology has rich texture information and is effective in color correction and atomization removal through RBDCP. Extensive experimental results indicate that the proposed method effectively balances image hue, saturation, and clarity. (C) 2021 Optical Society of America
机译：光在水中传播时会被吸收和散射，导致水下光学图像模糊和颜色失真。为了提高水下光学图像的视觉质量，我们提出了一种新的图像锐化方法。我们利用相对全变分模型以一种新颖的方式将图像分解为结构层和纹理层。在这两层上，分别提出了红蓝暗通道先验（RBDCP）和细节提升算法。RBDCP模型根据亮度、梯度辨别和色调判断计算背景光，然后使用红蓝通道衰减特性生成透射贴图。提出的细节提升算法采用了高斯核和二值掩模的线性组合。此外，受融合概念的启发，我们将恢复结构层和增强纹理层结合起来进行图像锐化。我们的方法具有丰富的纹理信息，通过RBDCP可以有效地进行颜色校正和原子化去除。大量实验结果表明，该方法有效地平衡了图像的色调、饱和度和清晰度。（2021）美国光学学会

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  • 来源
    《Applied optics》 |2021年第15期|共12页
  • 作者

    Lin Sen; Chi Kaichen; Wei Tong; Tao Zhiyong;

  • 作者单位

    Shenyang Ligong Univ Sch Automat &

    Elect Engn Shenyang 110159 Peoples R China;

    Liaoning Tech Univ Sch Elect &

    Informat Engn Huludao 125105 Peoples R China;

    Eotvos Lorand Univ Fac Informat H-1117 Budapest Hungary;

    Liaoning Tech Univ Sch Elect &

    Informat Engn Huludao 125105 Peoples R China;

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