激光与光电子学进展, 2020, 57 (16): 161010, 网络出版: 2020-08-05   

基于高低频分量融合的水下图像增强算法 下载: 974次

Underwater Image Enhancement Algorithm Based on Fusion of High and Low Frequency Components
作者单位
大连海事大学信息科学技术学院, 辽宁 大连 116026
摘要
针对退化的水下图像存在色彩失真,对比度低和视觉模糊的问题,提出一种基于高低频分量融合的水下图像增强算法。首先利用多尺度Retinex算法估计高频分量,并对其进行对比度受限的自适应直方图拉伸,在增强全局对比度的同时突显细节信息;为了防止在图像拉伸的过程中产生噪声以影响图像质量,对拉伸后的高频分量使用引导滤波进行去噪声处理;然后将原图与高频分量相除以获取低频分量,同时使用多尺度细节提取法获取细节信息;最后将去除噪声的对比度增强图像和高低频细节图像进行线性加权融合并进行颜色校正,获得最终的水下清晰图像。实验结果表明,所提算法能够有效地增强图像对比度和细节,明显改善图像的视觉效果。
Abstract
To address the problems of color distortion, low contrast, and blurred vision in degraded underwater images, an underwater image enhancement algorithm based on high and low frequency component fusion is proposed. First, multi-scale retinex algorithm is used to estimate high frequency components. Then, contrast-constrained adaptive histogram stretching is performed to enhance the global contrast while highlighting details. To prevent noise generated during image stretching from affecting the image quality, guided high frequency components are denoised via guided filtering. Then, the original image and high frequency components are divided to obtain low frequency components, and the multi-scale detail extraction method is used to obtain detailed information. Finally, the noise-removed contrast-enhanced image and the high and low frequency detail image are linearly weighted and color corrected to obtain the final underwater clear image. Experimental results show that the proposed algorithm can effectively enhance the image contrast and details and significantly improve the visual effect of the image.

邹沛煜, 张卫东, 史金余, 周景春. 基于高低频分量融合的水下图像增强算法[J]. 激光与光电子学进展, 2020, 57(16): 161010. Peiyu Zou, Weidong Zhang, Jinyu Shi, Jingchun Zhou. Underwater Image Enhancement Algorithm Based on Fusion of High and Low Frequency Components[J]. Laser & Optoelectronics Progress, 2020, 57(16): 161010.

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