水下降质图像的偏振参数分区优化复原

Polarization parameter partition optimization restoration method for underwater degraded image

水下环境获取图像存在对比度下降、清晰度降低、信息衰减等问题。传统方法是对整幅图像的偏振信息进行估计处理,水下图像中目标具有复杂的偏振特性,导致某些目标区域的复原效果欠佳,发生退化。本文提出了一种水下降质图像偏振参数分区优化复原方法。首先经分块对比度加强和引导滤波对两幅偏振正交图像处理后提取高低偏物体的连通域,根据偏振度图像各像素点的值进行分区,优化了对低、高偏振度目标物区域的提取过程;其次分别估计各目标物的目标光偏振度,解决了传统方法中全局估计中复杂目标的错误估计问题;最后对后向散射光偏振度图像进行迭代优化,得到最优选区。实验表明:本文实验结果的主观视觉质量提升显著,前两组实验在低浑浊度下对比原始光强图,客观评价指标EME值提升平均达554%,对比度则平均提升528%,第三组实验在低照度高浑浊度环境下对比原始光强图,EME值提升达379%,对比度则提升956%。三组实验自然图像质量评价指标NIQE值表现良好,图像更加自然。本文的方法较传统方法能有效地复原水下浑浊图像,增加图像对比度,削弱信息衰减,实现更好的图像清晰化效果。

In real water environments,common imaging problems include contrast reduction,low defini-tion,and information attenuation.The traditional estimation method involves estimating the polarization information of the entire image.In real underwater images,the target has complex polarization characteris-tics,the restoration effects of some target areas are poor,and even degradation occurs.In this study,a method of polarization parameter partition optimization restoration for water-degraded images was pro-posed.First,the connected domain of an object with high and low polarizations was extracted after two images were processed with orthogonal polarization by block contrast enhancement and guided filtering.Based on the pixel values in the polarization image,the extraction process of high and low polarization ob-ject regions was optimized.Second,the polarization of each object was estimated,which solved the problem of incorrect estimation of complex objects in traditional global estimation methods.Finally,the image of po-larization degree of backscattered light was iteratively optimized to obtain the optimal selection.Experimen-tal results show that the subjective visual quality of the image is improved significantly.In two initial experi-ments,the original light intensity maps under low turbidity are compared.The measurement of enhancement by entropy(EME)value of the objective evaluation index and the contrast increases by 554%and 528%on average,respectively.In a third set of experiments,in which a comparison of the original light intensity maps in an environment of low illumination and high turbidity was conducted,the EME value and contrast are improved by 379%and 956%,respectively.Three sets of natural image quality evaluation(NIQE)indi-ces indicate the proposed method has good performance,and a more natural image is produced.Compared with the traditional method,the proposed method can effectively restore a turbid image,increase image con-trast,weaken information attenuation,and achieve a better image sharpening effect.