为了改善主动光在水下传播过程中由散射与吸收效应导致的深海图像对比度低下以及颜色失真问题，提出一种水下图像增强算法.不同于传统方法利用最亮点的强度值作为背景光，提出基于物体与背景光非相关性的背景光估计方法，有效避免了前景处的亮像素或白色物体像素对背景光的误判，同时确保了去散射的精确性，提高水下图像的对比度；针对人造光源的颜色增益和光路衰减导致的图像色偏等问题，在去散射图像上选取离光源最近的灰色像素，利用其对光源的敏感性，将光照强度分离出来.最终，通过估计并去除光源本身的颜色增益，同时补偿光在传播过程中的损失，实现图像的颜色校正.实验结果表明，所提算法可以有效去除水下图像的散射效应，较好地恢复图像色彩，进而获得较优的增强图像.相比于其他算法，增强后的图像信息熵和水下图像质量评价指标值较高，说明该算法能显著提升水下图像的质量，同时保留图像有用信息.

To solve the low contrast and color distortion problem of deep sea image caused by active light scattering and absorption effects in the underwater environment, an underwater image enhancement method is proposed. Different from the previous methods, which estimate the background light with the brightest pixels, background light is estimated based on the non-correlation of the object and the background light, to alleviate the disturbance of the pixels in the white objects or the illuminated foreground region, while keeping its accuracy in removing scattering, and improve the underwater image contrast. Aiming at the color distortion caused by the color gain of artificial light source color and the optical attenuation, the grey pixels, which are close to the light source, are picked in the dehazed image. Then the light intensity can be derived with the detected pixels according to the sensitivity to the source. With the estimated light intensity, the light source color is achievable. At last, color distortion can be corrected by removing the source color while compensating for the optical attenuation. Experimental results demonstrate the proposed method can effectively remove haze, recover the relatively genuine color, and further obtain the enhanced image. The information entropy and the underwater image quality evaluation values of the proposed method are higher than that of the existing methods, which indicates that the proposed method can improve the underwater image quality significantly while preserving the efficient information.