水下
计算机科学
人工智能
计算机视觉
能见度
RGB颜色模型
对比度(视觉)
图像质量
图像(数学)
光学
地质学
海洋学
物理
作者
Jieyu Yuan,Wei Cao,Zhanchuan Cai,Binghua Su
出处
期刊:IEEE Transactions on Geoscience and Remote Sensing
[Institute of Electrical and Electronics Engineers]
日期:2021-10-01
卷期号:59 (10): 8117-8128
被引量:36
标识
DOI:10.1109/tgrs.2020.3033407
摘要
Underwater images require further enhancement to improve the image qualities caused by medium scattering and light absorption. Based on Contour Bougie (CB) morphology, we propose a new enhancement method to enhance the scene contours and improve the visibility of images captured underwater. Two structuring elements with different sizes are considered as the roving windows. Multiple morphological operations are designed for highlighting the rich details on the origin images. The enhanced images are normalized and stretched to improve the white balance of RGB channels. The comprehensive study of state-of-the-art algorithms is conducted to interpret the improvement of image quality by the proposed method. In addition, we use 890 raw underwater degraded images as the testing data. The quantitative and qualitative evaluations of these data demonstrate that the proposed method achieves better visible contrast for highlighting the details of the undersea creatures. The comparison with different underwater scenes proves that the proposed method improves the color balances of the degraded images.
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