Underwater image enhancement based on colour correction and fusion

Daqi Zhu, Zhiqiang Liu, Youmin Zhang
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引用次数: 6

Abstract

Underwater image processing has always been a very challenging problem. Under the influence of environmental factors, underwater images are prone to some problems, such as colour cast, low visibility, and few edge details. Here, an image enhancement algorithm is proposed to improve image degradation mainly caused by the absorption of light. First, colour compensation and white balance algorithm are used to restore the natural appearance of the image. Then the improved dark channel prior (DCP) is used to improve the visibility and avoid blocking artifacts which appear in traditional DCP. Unsharp masking (USM) is applied to enhance the texture features of the DCP image. Finally, wavelet fusion is used to fuse the DCP image and DCP + USM image. The fusion algorithm not only further improves the visibility and texture features, but also reduces the noise of DCP + USM. Compared with other methods, quantitative analysis results show that the enhanced images have higher visibility, more details and edge information.
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基于色彩校正和融合的水下图像增强
水下图像处理一直是一个非常具有挑战性的问题。在环境因素的影响下,水下图像容易出现偏色、可见度低、边缘细节少等问题。本文提出了一种图像增强算法,以改善主要由光吸收引起的图像退化。首先,利用色彩补偿和白平衡算法恢复图像的自然外观。然后利用改进的暗通道先验(DCP)提高图像的可见性,避免了传统DCP中出现的阻塞伪影。采用非锐化掩蔽(USM)增强DCP图像的纹理特征。最后,利用小波融合对DCP图像和DCP + USM图像进行融合。融合算法不仅进一步提高了图像的可见性和纹理特征,而且降低了DCP + USM的噪声。定量分析结果表明,与其他方法相比,增强后的图像具有更高的可见性、更多的细节和边缘信息。
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