基于偏振成像和显著区域自补偿的水下显著目标检测

Underwater salient target detection based on polarization imaging and salient region self-compensation

在浑浊的水下环境中,受水体多重散射以及噪声的影响,造成水下成像质量大幅下降,现有显著性目标检测算法无法满足目标检测准确性的任务需求。因此,提出一种基于偏振成像和显著区域自补偿的水下显著目标检测算法。提出的算法分为两个阶段:采用基于偏振角估计后向散射光的方法去除后向散射的影响,同时引入引导滤波进行水下去噪,再通过PSF函数去除前向散射造成的模糊效应;利用改进的栅格扫描算法结合局部特征描述符识别前景超像素,根据前景超像素生成显著区域对网络进行优化补偿,再结合DeepLabv3+网络生成最终的分割图。在浑浊水下环境进行了多组对比实验结果表明,所提复原算法可以有效地增强目标,提高了目标的对比度和清晰度,所提显著目标检测算法能够准确地检测出水下显著目标,并且可以保留细节信息。结合偏振成像模型的优点,该算法能够较好地克服水下复杂的光学成像环境,并且能快速准确地检测出水下显著目标。

In the turbid underwater environment,due to the influence of multiple scattering and noise,the underwater imaging quality is greatly reduced.The existing significant target detection algorithms can’t meet the task requirements of target detection accuracy.Therefore,this paper proposed an underwater salient target detection algorithm based on polarization imaging and salient region self-compensation.It divided the proposed algorithm into two stages.Firstly it used the method of estimating backscattered light based on polarization angle to remove the influence of backscattering,and introduced guided filter for underwater noise,and then removed the fuzzy effect caused by forward scattering through PSF function.Secondly it used an improved raster scanning algorithm combined with local feature descriptors to identify foreground superpixels,generated salient regions based on foreground superpixels to optimize and compensate the network,and then combined with DeepLabv3+network to generate the final segmentation map.This paper conducted multiple sets of comparative experiments in a turbid underwater environment.The results show that the proposed restoration algorithm can effectively enhance the target,improve the contrast and clarity of the target,and the proposed salient target detection algorithm can accurately detect the underwater salient target and retain the detailed information.Combining the advantages of the polarization imaging model,this algorithm can better overcome the underwater complex optical imaging environment,and quickly and accurately detect significant underwater targets.