Underwater image descattering and quality assessment
Underwater image descattering and quality assessment
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DOI：
10.1109/icip.2016.7532708
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发表时间：
2016-09
期刊：
影响因子：
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通讯作者：
Huimin Lu-;Yujie Li;Xing Xu;Li He;Yun Li;D. Dansereau;S. Serikawa
中科院分区：
文献类型：
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作者：
Huimin Lu-;Yujie Li;Xing Xu;Li He;Yun Li;D. Dansereau;S. Serikawa
基于视觉的水下导航和目标检测需要强大的计算机视觉算法在浑浊水中运行。许多传统方法旨在提高低浑浊水中的能见度。在本文中，我们提出了一种新的对比度增强，以增强高浑浊水下图像使用散射和色彩校正。所提出的增强方法消除了散射并保留了颜色。此外，作为比较不同图像增强算法性能的规则，提出了一个更全面的图像质量评价指标Qu。该指数综合了SSIM指数和颜色距离指数的优点。实验结果表明，该方法在统计上优于目前最先进的通用水下图像对比度增强算法。实验结果表明，该方法具有较好的图像分类效果。
Vision-based underwater navigation and object detection requires robust computer vision algorithms to operate in turbid water. Many conventional methods aimed at improving visibility in low turbid water. In this paper, we propose a novel contrast enhancement to enhance high turbid underwater images using descattering and color correction. The proposed enhancement method removes the scatter and preserves colors. In addition, as a rule to compare the performance of different image enhancement algorithms, a more comprehensive image quality assessment index Qu is proposed. The index combines the benefits of SSIM index and color distance index. Experimental results show that the proposed approach statistically outperforms state-of-the-art general purpose underwater image contrast enhancement algorithms. The experiment also demonstrated that the proposed method performs well for image classification.