水下
RGB颜色模型
人工智能
计算机视觉
对比度(视觉)
颜色直方图
失真(音乐)
衰减
能见度
计算机科学
颜色校正
图像质量
光散射
彩色图像
颜色恒定性
散射
光学
图像处理
图像(数学)
地质学
物理
电信
放大器
海洋学
带宽(计算)
作者
Jingchun Zhou,Xiaojing Wei,Jianghong Shi,Weishen Chu,Weishi Zhang
标识
DOI:10.1016/j.compeleceng.2022.107898
摘要
Light is absorbed and scattered when propagating in water, which results in low quality and poor visibility of underwater optical images. Furthermore, the absorption of light by water causes color distortion, whereas the scattering of light by small particles suspended in water results in low image contrast. To enhance the underwater image quality, we developed a method based on light scattering characteristics. Firstly, we group the color cast into five categories according to the proportion of the average of the RGB channels. Then, we use the optical attenuation characteristics to calculate the color loss rate of the RGB channels of underwater images in different scenes and develop a multi-scene color restoration method to correct the color cast of underwater images. While keeping the color constant, we set a 64-block multi-contrast factor histogram stretching to enhance the contrast of the underwater image. The experimental results verify that the developed method has achieved image quality improvement via qualitative and quantitative evaluation. Our approach is proved to effectively improve the quality of underwater images with color distortion, low contrast, and detail loss.
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