Underwater image color correction and adaptive contrast algorithm improvement based on fusion algorithm

Hengjun Zhu, Tianluo Wang, Lihao Ma
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Abstract

Due to the characteristics of water and the particles in water, the underwater images will have problems of color deviation, low contrast and uneven brightness. Therefore, a statistical approach based on variance is proposed in this paper to correct color-biased images and then equalize the image brightness using the Gamma algorithm. Secondly, a local adaptive contrast enhancement algorithm improved by contrast code images and a restricted contrast adaptive histogram equalization algorithm are used to improve the contrast of underwater images. Finally, two different contrast enhanced images after color correction are fused by a multi-scale fusion algorithm to obtain high-quality underwater images. The results of the comparison experiments with some existing underwater image enhancement algorithms show that our algorithm can effectively improve the quality of underwater images.
基于融合算法的水下图像色彩校正与自适应对比度算法改进
由于水和水中粒子的特性,水下图像会出现色彩偏差、对比度低、亮度不均匀等问题。因此,本文提出了一种基于方差的统计方法来校正颜色偏差图像,然后使用Gamma算法均衡图像亮度。其次,采用对比度编码图像改进的局部自适应对比度增强算法和受限对比度自适应直方图均衡化算法对水下图像进行对比度增强;最后,采用多尺度融合算法对两幅经过色彩校正的对比度增强图像进行融合,得到高质量的水下图像。与现有的一些水下图像增强算法的对比实验结果表明,本文算法可以有效地提高水下图像的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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