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Underwater optical image processing based on double threshold judgements and optimized red dark channel prior method

机译:基于双阈值判断的水下光学图像处理和优化的红色暗声道先前方法

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摘要

Underwater images are prone to suffer from color distortion and low visibility because of the strong light attenuation. The traditional dark channel prior (DCP) method tends to fail when used for underwater image restoration. By exploring the differences in light attenuation between atmosphere and water, we propose an innovative image restoration method-optimized red dark channel prior (ORDCP) which adds a valid contrast indicator. In addition, we set double threshold judgments to determine the main color tone and calculate red channel transmission map. After getting the two estimated parameters including transmission maps and background light, we can restore underwater images using conventional underwater imaging model. The subjective evaluations indicate that the algorithm we proposed has better performance in terms of saturation, contrast and images edge details. What's more, the results of objective evaluation metrics show that the performances maximally increase by 32.32% in underwater images such as the ship and stone. The conclusion can be drawn that the proposed method is able to remove the noise and blur caused by complicated underwater environment and performs favorably against the state-of-the-art algorithms.
机译:由于强光衰减,水下图像易于遭受颜色变形和低可视性。当用于水下图像恢复时,传统的暗通道(DCP)方法趋于失效。通过探索大气和水之间的光衰减的差异,我们提出了一种创新的图像恢复方法 - 优化的红色暗频道(ORDCP),其添加有效的对比度指示器。此外,我们设置了双重阈值判断,以确定主色调并计算红色通道传输映射。在获得包括传输贴图和背景光的两个估计参数之后,我们可以使用传统的水下成像模型恢复水下图像。主观评估表明,我们提出的算法在饱和度,对比度和图像边缘细节方面具有更好的性能。更重要的是,客观评估度量的结果表明,在船舶和石头等水下图像中的性能最大程度地增加了32.32%。可以得出结论,所提出的方法能够去除由复杂的水下环境引起的噪声和模糊,并对最先进的算法进行有利地执行。

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