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Contrast enhancement for images in turbid water

机译:混浊水中图像的对比度增强

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摘要

Absorption, scattering, and color distortion are three major degradation factors in underwater optical imaging. Light rays are absorbed while passing through water, and absorption rates depend on the wavelength of the light. Scattering is caused by large suspended particles, which are always observed in an underwater environment. Color distortion occurs because the attenuation ratio is inversely proportional to the wavelength of light when light passes through a unit length in water. Consequently, underwater images are dark, low contrast, and dominated by a bluish tone. In this paper, we propose a novel underwater imaging model that compensates for the attenuation discrepancy along the propagation path. In addition, we develop a robust color lines-based ambient light estimator and a locally adaptive filtering algorithm for enhancing underwater images in shallow oceans. Furthermore, we propose a spectral characteristic-based color correction algorithm to recover the distorted color. The enhanced images have a reasonable noise level after the illumination compensation in the dark regions, and demonstrate an improved global contrast by which the finest details and edges are enhanced significantly. (C) 2015 Optical Society of America
机译:吸收,散射和颜色失真是水下光学成像中的三个主要退化因素。光线在穿过水时会被吸收,吸收率取决于光的波长。散射是由大的悬浮颗粒引起的,这些颗粒通常在水下环境中观察到。发生颜色失真是因为当光穿过水中的单位长度时,衰减率与光的波长成反比。因此,水下图像是暗的,低对比度的,并且以蓝色为主。在本文中,我们提出了一种新颖的水下成像模型,该模型可以补偿沿传播路径的衰减差异。此外,我们开发了一种基于色线的鲁棒环境光估计器和一种用于增强浅海水下图像的局部自适应滤波算法。此外,我们提出了一种基于光谱特征的色彩校正算法来恢复失真的色彩。增强的图像在暗区进行照明补偿后具有合理的噪声水平,并显示出改善的全局对比度,通过该全局对比度可以显着增强最细微的细节和边缘。 (C)2015年美国眼镜学会

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