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基于二维三次样条小波与红通道先验的水下图像增强方法
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Abstract:
针对水下图像所出现的对比度低、细节模糊和颜色失真等问题，本文提出二维三次样条小波与暗通道先验的水下图像增强方法。将水下图像使用红通道先验方法去除雾状模糊，然后将其归一化以进行白平衡。同时将原始水下图像使用二维三次样条小波进行加性小波分解，产生低频子图和高频子图。将高频子图系数放大以增强细节信息。最后将处理后的高频子图和白平衡后的图像相加得到增强的图像。实验结果表明，本文算法能够有效消除图像颜色失真，增强的图像呈现出高对比度和清晰的细节。与目前水下图像增强相关典型方法相比，它在对比度、颜色、边缘保留和自然度等方面有明显改进。
To address the problems of low contrast, blurred details and color distortion that occur in underwater images, this paper proposes a two-dimensional cubic spline wavelet with a dark channel prior for underwater image enhancement. The underwater image is removed from the fog blur using the red channel a priori method and then normalized for white balance. The original underwater image is also subjected to additive wavelet decomposition using two-dimensional cubic spline wavelets to produce low-frequency and high-frequency sub-images. The high-frequency sub-images coefficients are scaled up to enhance the detail information. Finally, the processed high-frequency sub-images and the white-balanced image are summed to obtain the enhanced image. The experimental results show that the algorithm in this paper can effectively eliminate the image color distortion and the enhanced image presents high contrast and clear details. It offers significant improvements in contrast, color, edge retention and naturalness compared to the typical methods related to current underwater image enhancement.
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