Ge WenYi, Lin Yi, Wang Zhitao, Yang Tongyu
Opt Express. 2022 Jul 4;30(14):24295-24309. doi: 10.1364/OE.463865.
Captured underwater images usually suffer from severe color cast and low contrast due to wavelength-dependent light absorption and scattering. These degradation issues affect the accuracy of target detection and visual understanding. The underwater image formation model is widely used to improve the visual quality of underwater images. Accurate transmission map and background light estimation are the keys to obtaining clear images. We develop a multi-priors underwater image restoration method with adaptive transmission (MUAT). Concretely, we first propose a calculation method of the dominant channel transmission to cope with pixel interference, which combines two priors of the difference between atmospheric light and pixel values and the difference between the red channel and the blue-green channel. Besides, the attenuation ratio between the superior and inferior channels is adaptively calculated with the background light to solve the color distortion and detail blur caused by the imaging distance. Ultimately, the global white balance method is introduced to solve the color distortion. Experiments on several underwater scene images show that our method obtains accurate transmission and yields better visual results than state-of-the-art methods.
由于与波长相关的光吸收和散射，水下拍摄的图像通常会出现严重的色偏和低对比度问题。这些退化问题会影响目标检测和视觉理解的准确性。水下图像形成模型被广泛用于提高水下图像的视觉质量。准确的透射图和背景光估计是获得清晰图像的关键。我们开发了一种具有自适应透射的多先验水下图像恢复方法（MUAT）。具体来说，我们首先提出了一种主导通道透射的计算方法来应对像素干扰，该方法结合了大气光与像素值之间的差异以及红色通道与蓝绿色通道之间的差异这两个先验。此外，利用背景光自适应计算上下通道之间的衰减率，以解决成像距离导致的颜色失真和细节模糊问题。最终，引入全局白平衡方法来解决颜色失真问题。对几幅水下场景图像的实验表明，我们的方法能够获得准确的透射结果，并且比现有方法产生更好的视觉效果。
