The dissolved particles and their resultant scattering are the underlying cause of low contrast and blur thereby producing poor quality underwater images. Single-shot shallow coastal underwater images are much in need of the preprocessing steps viz. image enhancement and restoration. The underwater image processing operations like classification, object detection and computer vision require an enhancement/restoration preprocessing. The paper aims to restore the visibility of objects in turbid water images with its effective edge aware restoration cum enhancement model. The restricted rolling guidance filter on the DCP-based restoration method produces better edge aware restoration and denoised output image. The model-based (MB) dark channel prior (DCP) along with an edge emphasis and contrast enhancement achieves the essential dehazing and improvement in contrast for the heavily blurred underwater images. The subjective and objective projections are an evidence for the same. This edge preserving and denoising nature of the model is also exhibited with comparisons made with promising algorithms over the decade.

中文翻译：

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单一浅海沿岸水图像去噪、边缘感知恢复与增强

溶解的颗粒及其产生的散射是低对比度和模糊的根本原因，从而产生质量差的水下图像。单次拍摄的浅海岸水下图像非常需要预处理步骤，即。图像增强和恢复。分类、目标检测和计算机视觉等水下图像处理操作需要增强/恢复预处理。本文旨在通过有效的边缘感知恢复和增强模型恢复浑水图像中物体的可见性。基于 DCP 的恢复方法上的受限滚动引导滤波器可产生更好的边缘感知恢复和去噪输出图像。基于模型的 (MB) 暗通道先验 (DCP) 以及边缘强调和对比度增强实现了对严重模糊的水下图像的基本去雾和对比度改进。主观和客观的预测是相同的证据。该模型的这种边缘保留和去噪特性也通过与十年来有前途的算法进行的比较得到了体现。