摘要： 水下物理环境复杂多变，导致获取的水下图像颜色失真、对比度低且细节模糊，影响了水下场景探测的准确性。结合衰减补偿和直方图拉伸技术，提出水下图像增强算法ACHS。根据不同颜色通道的衰减特性，设计基于衰减补偿的颜色校正方法解决水下图像颜色失真问题。将需要颜色校正的水下图像从RGB颜色模型转换到LAB颜色模型，使用引导滤波将亮度通道L分解为基础层和细节层，同时提出基于K-means聚类的双直方图增强算法用于增强基础层的对比度，通过Gamma校正突显细节层的纹理结构。在此基础上，累加亮度通道L的基础层和细节层，并将其从LAB颜色模型转换到RGB颜色模型以获取最终的增强图像。实验结果表明，与GDCP、REBE、WaterNet等算法相比，经该算法增强的水下图像可视度较高，并且具有自然的颜色和清晰的细节。

关键词: 水下图像增强, 衰减补偿, 双直方图, 颜色校正, 细节增强

Abstract: The complex and changeable underwater physical environment leads to the color distortion, low contrast and fuzzy details of the acquired underwater image, which affects the accuracy of underwater scene detection.An underwater image enhancement algorithm based on attenuation compensation and histogram stretching, named ACHS, is proposed.Firstly, a color correction method based on attenuation compensation is proposed according to the attenuation characteristics of different color channels, which can effectively solve color distortion in underwater images.Then, the color-corrected underwater image is converted from the RGB color model to the LAB color model, and the brightness channel L is decomposed into the base and detail layers using a guided filter.Meanwhile, a K-means clustering-based dual histogram enhancement algorithm is proposed to enhance the contrast of the base layer, and gamma correction is used to highlight the texture structure of the detail layer.Finally, the base and detail layers of the brightness channel L are accumulated and converted from the LAB color model to the RGB color model to obtain the final enhanced image.The experimental results show that, compared with GDCP, REBE, WaterNet algorithms, et al, underwater images enhanced using the proposed algorithm exhibit natural colors, high visibility, and clear details.

Key words: underwater image enhancement, attenuation compensation, dual histogram, color correction, details enhancement

中图分类号: 

• TP391