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Underwater image enhancement based on DCP and depth transmission map

机译:基于DCP和深度传输地图的水下图像增强

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Seeing that the light in the water is affected by absorption and scattering, underwater image will suffer degradation including low contrast, low visibility and color deviation. Therefore, the key issue of underwater image enhancement is to improve the visibility and the contrast of underwater images. In this paper, we proposed an underwater image dehazing algorithm combining three main steps of homomorphic filtering, double transmission map and dual-image wavelet fusion. First at all, we removed the color deviation in the underwater image by homomorphic filtering. Then, we obtained the enhanced image by depth map which calculate the difference between the light and dark channels. Finally, the dual-image wavelet fusion technique is used to combine the enhanced image obtained by the depth map with the enhanced image obtained by the dark channel. In addition, we obtained the contrast enhanced image which use Contrast-Limited Adaptive Histogram Equalization (CLAHE) method. Through simulation experiments, the proposed method has better visual effects and better effect on entropy, average gradient and underwater color image quality evaluation (UCIQE) compared with other popular methods.
机译:看到水中的光受吸收和散射的影响,水下图像会遭受降低,包括低对比度,低可视性和颜色偏差。因此,水下图像增强的关键问题是提高水下图像的可见性和对比度。在本文中,我们提出了一种组合均匀滤波,双传输图和双图像小波融合的三个主要步骤的水下图像去析算法。首先,我们通过同态滤波除去了水下图像中的颜色偏差。然后,我们通过深度映射获得了增强的图像,该深度映射计算了光和暗通道之间的差异。最后,双图像小波融合技术用于将深度图获得的增强图像与由暗通道获得的增强图像组合。此外,我们获得了对比增强图像,该图像使用对比限制自适应直方图均衡(CLAHE)方法。通过模拟实验,与其他流行方法相比,该方法具有更好的视觉效果和对熵,平均梯度和水下彩色图像质量评估(UCIQE)的影响。

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