水下
亮度
人工智能
计算机视觉
颜色校正
直方图
计算机科学
失真(音乐)
直方图均衡化
对比度(视觉)
光学
颜色直方图
图像复原
小波
彩色图像
图像处理
物理
图像(数学)
地质学
海洋学
放大器
带宽(计算)
计算机网络
作者
Jingchun Zhou,Xiaojing Wei,Jianghong Shi,Weishen Chu,Yi Lin
出处
期刊:Optics Express
[The Optical Society]
日期:2022-05-04
卷期号:30 (10): 17290-17290
被引量:6
摘要
Underwater images suffer color distortions and low contrast. This is because the light is absorbed and scattered when it travels through water. Different underwater scenes result in different color deviations and levels of detail loss in underwater images. To address these issues of color distortion and low contrast, an underwater image enhancement method that includes two-level wavelet decomposition maximum brightness color restoration, and edge refinement histogram stretching is proposed. First, according to the Jaffe-McGlamery underwater optical imaging model, the proportions of the maximum bright channel were obtained to correct the color of underwater images. Then, edge refinement histogram stretching was designed, and edge refinement and denoising processing were performed while stretching the histogram to enhance contrast and noise removal. Finally, wavelet two-level decomposition of the color-corrected and contrast-stretched underwater images was performed, and the decomposed components in equal proportions were fused. The proposed method can restore the color and detail and enhance the contrast of the underwater image. Extensive experiments demonstrated that the proposed method achieves superior performance against state-of-the-art methods in visual quality and quantitative metrics.
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