光在水中传播时受水的吸收作用和水中微粒的散射作用而发生衰减;因水的浊度变化,且水下拍摄时景深不一,导致水下获取的图像雾化程度和色彩偏差不同。传统的去雾算法用于处理这些模糊程度和色差多变的图像时效果欠佳。针对该问题,提出基于亮通道色彩补偿与融合的水下图像增强算法。首先,基于亮通道对原图像进行色彩补偿,获得色彩补偿的图像;再对色彩补偿的图像进行自适应对比度拉伸获得对比度高的清晰图像;最后采用多尺度融合策略对色彩补偿后的图像及对比度拉伸后的图像进行融合。结果表明,本文算法可广泛应用于多种水下降质图像,且在无任何先验信息的条件下,能有效提高水下图像对比度和平衡图像色彩。

Light is attenuated in underwater environments owing to the scattering and absorption effects. Because of the changes in water turbidity and different depths of the fields in underwater photography, the level of fuzziness and color deviation of the images captured underwater is different. Traditional defogging algorithms appear to have limited effectiveness in the case of these images with varying degrees of fuzziness and color deviation. Therefore, the color compensation based on the bright channel and the image fusion method for underwater image enhancement is proposed to resolve this problem. First, in order to obtain a color-compensated version of the original image, the color compensation based on the bright channel is performed on the original image. This color-compensated image is then subjected to adaptive contrast stretching to obtain a clear image with high contrast. Finally, the multiscale fusion strategy is adopted to fuse the color-corrected and contrast-stretched images. Experimental result shows that the proposed algorithm can be employed in a wide range of applications dealing with multiple underwater degraded images. Furthermore, the proposed method can effectively improve underwater image contrast and balance image color without any prior information.