Turbidity Underwater Image Restoration Using Spectral Properties and Light Compensation
Turbidity Underwater Image Restoration Using Spectral Properties and Light Compensation
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DOI：
10.1587/transinf.2014edp7405
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发表时间：
2016-01-01
影响因子：
0.7
通讯作者：
Serikawa, Seiichi
中科院分区：
文献类型：
--
作者：
Lu, Huimin;Li, Yujie;Serikawa, Seiichi
吸收、散射和颜色失真是水下光学成像中的三个主要问题。穿过水的光线根据其波长被散射和吸收。散射是由大的悬浮颗粒引起的，它们会使水下光学图像退化。颜色失真的发生是因为不同的波长在水中衰减到不同的程度;因此，周围水下环境的图像以蓝色为主。本文提出了一种新的水下成像模型，该模型补偿了沿着衰减的差异，并提出了一种快速加权引导归一化卷积域滤波算法来增强水下光学图像。增强的图像的特征在于降低的噪声水平，更好地暴露在黑暗的区域，并提高整体对比度，其中最精细的细节和边缘显着增强。
Absorption, scattering, and color distortion are three major issues in underwater optical imaging. Light rays traveling through water are scattered and absorbed according to their wavelength. Scattering is caused by large suspended particles that degrade underwater optical images. Color distortion occurs because different wavelengths are attenuated to different degrees in water; consequently, images of ambient underwater environments are dominated by a bluish tone. In the present paper, we propose a novel underwater imaging model that compensates for the attenuation discrepancy along the propagation path. In addition, we develop a fast weighted guided normalized convolution domain filtering algorithm for enhancing underwater optical images. The enhanced images are characterized by a reduced noise level, better exposure in dark regions, and improved global contrast, by which the finest details and edges are enhanced significantly.