揭示水下图像的光学特性

Yael Bekerman, S. Avidan, T. Treibitz
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引用次数: 10

摘要

水下场景的外观高度取决于水的光学特性(衰减和散射)。然而,大多数基于物理的水下图像重建方法的研究工作都集中在设计图像先验来估计场景传输,而对光学性质的估计较少。这限制了结果的质量。这项工作的重点是对水性质的鲁棒估计。首先,与之前使用固定值进行衰减的方法相反,我们从图像中的颜色分布来估计衰减。其次,我们估计场景中物体的遮光颜色,而不是看背景像素。我们在几个数据集上对我们的方法与最新方法进行了广泛的定性和定量评估。由于我们的估计更加稳健,我们的方法提供了更好的结果,包括具有挑战性的场景。
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Unveiling Optical Properties in Underwater Images
The appearance of underwater scenes is highly governed by the optical properties of the water (attenuation and scattering). However, most research effort in physics-based underwater image reconstruction methods is placed on devising image priors for estimating scene transmission, and less on estimating the optical properties. This limits the quality of the results. This work focuses on robust estimation of the water properties. First, as opposed to previous methods that used fixed values for attenuation, we estimate it from the color distribution in the image. Second, we estimate the veiling-light color from objects in the scene, contrary to looking at background pixels. We conduct an extensive qualitative and quantitative evaluation of our method vs. most recent methods on several datasets. As our estimation is more robust our method provides superior results including on challenging scenes.
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