基于暗通道先验和自适应颜色校正的水下图像处理

Underwater Image Processing Based on Dark Channel Prior and Adaptive Color Correction

研究了基于暗通道先验和自适应颜色校正的密闭空间下的水下图像处理。针对传统水下图像去雾方法对光照强度不均的密闭空间内的图像处理效果不佳以及色彩失真问题,利用暗通道原理对水下图像进行去雾后,引入自适应红通道补偿参数,改善红光缺失现象;结合渐晕模型对水下图像亮度通道进行校正,降低光强对图像成像质量的影响。所提方法在真实的密闭水下环境中进行测试,实验结果表明,相比于传统去雾算法,所提方法可以在有效改善图像亮度的同时还原图像色彩。

This paper studies underwater image processing in closed space based on dark channel prior and adaptive color correction. For the problems of poor image processing effect and color distortion of traditional underwater image dehazing methods in closed space with uneven illumination intensity,this paper introduces adaptive red channel compensation parameters to avoid the phenomenon of red light loss after dehazing the underwater image by using dark channel principle,and uses the vignetting model to improve the brightness of underwater image. The channel is calibrated to reduce the influence of light intensity on image quality. The proposed method is tested in a real sealed underwater environment. The experimental results show that,compared with traditional dehazing algorithms,the proposed method can effectively improve the brightness of the image while restoring the color of the image.