| 摘要: |
| 目的 针对工业环境下水下图像受到水中悬浮物影响,从而导致图像的清晰度过低以及对比度过高等问题,
提出一种基于图像熵线性加权的水下图像增强算法。 方法 该算法基于图像熵理论对白平衡算法、直方图均衡算法
和暗通道先验算法进行线性加权,继而通过实验环境确定调节系数输出高质量图像。 在深度为 1 m、1. 5 m 和 2 m
的不同水下环境拍摄图像,对获得的水下图像使用上述三种算法和该算法作对比处理,处理结果通过 PSNR 和
UIQM 作为评价指标进行评判。 结果 实验结果表明:使用 PSNR 指标评判该算法,相较于其他三种算法,水深 1 m
的水下图像质量提高了 22. 81%,水深 1. 5 m 的水下图像质量提高了 46. 67%,水深 2 m 的水下图像质量提高了
38. 94%,图像质量综合平均提高了 36. 14%;使用 UIQM 指标评判该算法,相较于其他三种算法,水深 1 m 的图像质
量提高了 1. 02%,水深 1. 5 m 的水下图像质量提高了 0. 73%,水深 2 m 的水下图像质量提高了 1. 82%,图像质量综
合平均提高了 1. 19%。 结论 由此可以证明该算法相对于其他传统算法对图像清晰度有着显著提升,并且能够适应
不同深度的水下环境,为工业环境下水下图像增强提供了一种新的解决思路。 |
| 关键词: 水下图像增强 线性加权 图像熵 图像融合 |
| DOI： |
| 分类号: |
| 基金项目: |
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| An Underwater Image Enhancement Algorithm Based on Image Entropy Linear Weighting |
|
WANG Yaqiang； WU Minghui ；GENG Fangqi ；FENG Yening ；ZHOU Wei
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School of Mechanical and Automotive Engineering Shanghai University of Engineering and Science Shanghai 201600
China
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| Abstract: |
| Objective Aiming at the problem that the underwater images in the industrial environment are affected by
suspended solids in water resulting in low image clarity and high contrast an underwater image enhancement algorithm
based on linear weighting of image entropy was proposed. Methods The algorithm linearly weighted the white balance
algorithm histogram equalization algorithm and dark channel prior algorithm based on the image entropy theory and
then determined the adjustment coefficient to output high-quality images through the experimental environment. Through
taking images in different underwater environments at depths of 1 m 1. 5 m and 2 m the obtained underwater images
were compared and processed by using the above three algorithms and this algorithm. The processing results were
evaluated by PSNR and UIQM as evaluation indicators. Results The experimental results showed that the proposed
algorithm judged by the PSNR index improved the underwater image quality by 22. 81% for the water depth of 1m
46. 67% for the water depth of 1. 5 m 38. 94% for the water depth of 2 m and improved the combined image quality by
36. 14% on average compared with the other three algorithms. The proposed algorithm judged by the UIQM index
improved the image quality by 1. 02% for the water depth of 1m 0. 73% for the water depth of 1. 5 m 1. 82% for the water depth of 2 m and improved the combined image quality by 1. 19% on average compared with the other three algorithms. Conclusion It can be proved that the proposed algorithm has significantly improved the image definition
compared with other traditional algorithms and this algorithm can adapt to different depths of underwater environments
providing a new solution for underwater image enhancement in industrial environments. |
| Key words: underwater image enhancement linear weighting image entropy image fusion |
