面向有雾图像的透射率模型分析与研究
发布时间：2018-10-20 09:07
【摘要】：室外图像往往会因为空气中悬浮颗粒(雾霾颗粒等)的存在而产生图像降质的问题。而降质问题会严重影响室外视频监控及图像采集系统的工作效率,因此一直以来,研究者们都致力于除雾算法的研究来提升这些系统的鲁棒性及可靠性。另一方面,雾的存在是图像保持空间透视距离感的关键组成,研究者们对如何在CG场景中产生逼真的烟雾环境产生了浓厚的兴趣,烟雾等环境同时也能产生水墨画等的艺术效果。然而遗憾的是,目前却没有工作将除雾以及雾效模拟结合,而二者本质核心都是对透射率进行计算。因此,本文提出了面向有雾图像的透射率模型,同时可进行除雾及雾效模拟。算法首先对基本的大气散射模型进行转化,引入了最大能见度,将有雾图像之间联系起来,进而提出了新的自然透射率模型(雾效滤波模型),并辅以颜色校正和天空补偿来提升算法效果。对于算法核心的图像透射率估计,本文提出了两种不同的技术路线：一是根据单一暗原色先验知识进行估计,并使用暗原色快速算法,引导滤波进行加速,这种方法操作简单,计算迅速,保证了算法运算的效率,运算速度可达到10-1s数量级,基本达到实时性要求；二是引入了高斯过程回归算法,利用有雾图像及对应透射率的训练集,以透射率作为输出向量,利用多尺度多维度的特征向量学习获得有雾图像透射率,这种方法具有更高的通用性与适用性。实验结果表明,我的方法所得到的除雾图像具有良好的清晰度,真实度,对比度,与此同时雾效模拟的结果真实而自然。
[Abstract]:Outdoor images tend to degrade due to the presence of suspended particles (haze particles) in the air. However, the degradation problem will seriously affect the efficiency of outdoor video surveillance and image acquisition systems, so researchers have been working on de-fogging algorithm to improve the robustness and reliability of these systems. On the other hand, the presence of fog is a key component of the image's sense of distance from perspective. Researchers are interested in how to create realistic smog environments in CG scenes. The environment such as smoke can also produce the artistic effect of ink painting and so on. However, unfortunately, there is no work to combine fog removal and fog effect simulation, and the core of both is to calculate the transmittance. Therefore, a transmittance model for foggy images is proposed, which can be used to simulate fog removal and fog effect. The algorithm firstly transforms the basic atmospheric scattering model, and introduces the maximum visibility to link the fog images. Furthermore, a new natural transmittance model (fog effect filter model) is proposed, which is supplemented by color correction and sky compensation to improve the effectiveness of the algorithm. For the image transmittance estimation of the core of the algorithm, this paper proposes two different technical routes: one is to estimate the image transmittance according to the prior knowledge of single dark primary color, and to use the fast dark primary color algorithm to speed up the image transmission estimation by guiding filter. This method is simple to operate. The calculation is rapid, which ensures the efficiency of the algorithm, and the operation speed can reach the order of 10 ~ (-1) s, which basically meets the real-time requirements. Secondly, Gao Si's process regression algorithm is introduced, which makes use of the fog image and the corresponding transmittance training set. The transmittance is used as the output vector and the multi-scale and multi-dimensional eigenvector is used to obtain the transmittance of foggy image. This method is more general and applicable. The experimental results show that the defogging images obtained by my method have good sharpness, fidelity and contrast, while the simulation results of fog effect are real and natural.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP391.41
[Abstract]:Outdoor images tend to degrade due to the presence of suspended particles (haze particles) in the air. However, the degradation problem will seriously affect the efficiency of outdoor video surveillance and image acquisition systems, so researchers have been working on de-fogging algorithm to improve the robustness and reliability of these systems. On the other hand, the presence of fog is a key component of the image's sense of distance from perspective. Researchers are interested in how to create realistic smog environments in CG scenes. The environment such as smoke can also produce the artistic effect of ink painting and so on. However, unfortunately, there is no work to combine fog removal and fog effect simulation, and the core of both is to calculate the transmittance. Therefore, a transmittance model for foggy images is proposed, which can be used to simulate fog removal and fog effect. The algorithm firstly transforms the basic atmospheric scattering model, and introduces the maximum visibility to link the fog images. Furthermore, a new natural transmittance model (fog effect filter model) is proposed, which is supplemented by color correction and sky compensation to improve the effectiveness of the algorithm. For the image transmittance estimation of the core of the algorithm, this paper proposes two different technical routes: one is to estimate the image transmittance according to the prior knowledge of single dark primary color, and to use the fast dark primary color algorithm to speed up the image transmission estimation by guiding filter. This method is simple to operate. The calculation is rapid, which ensures the efficiency of the algorithm, and the operation speed can reach the order of 10 ~ (-1) s, which basically meets the real-time requirements. Secondly, Gao Si's process regression algorithm is introduced, which makes use of the fog image and the corresponding transmittance training set. The transmittance is used as the output vector and the multi-scale and multi-dimensional eigenvector is used to obtain the transmittance of foggy image. This method is more general and applicable. The experimental results show that the defogging images obtained by my method have good sharpness, fidelity and contrast, while the simulation results of fog effect are real and natural.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP391.41
【参考文献】
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