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An approach of image decomposition for underwater target detection by inhomogeneous illumination based on G-Space and PDE

机译:基于G空间和PDE的不均匀光照水下目标检测的图像分解方法

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This paper presents a new approach of image decomposition for underwater target detection by inhomogeneous illumination based on G-Space and Partial Differential Equation( PDE). Underwater target images with high contrast visibility (less back-scattering) can be obtained within the inhomogeneous illumination field which power density is allocated inversely propotional to the rule of the light attenuation in water medium. Then the image f is decomposed into a sum of two functions u + v, where u component is modeled by a function of bounded variation (a cartoon or sketchy approximation of f), while v component representing the texture or noise is modeled by an oscillatory function. In this paper, the Vese-Osher(VO) model and Mumford-Shah-G(MS-G) model based on G-Space and PDE are introduced for texture image extraction. And the experimental results show that it's effective to obtain the cartoon and texture components as well as edge component of the underwater targets by MS-G model, which can be applied to further procedures such as image reconstruction and object recognition for underwater target detection.
机译:提出了一种基于G空间和偏微分方程(PDE)的非均匀光照水下目标检测图像分解新方法。可以在不均匀的照明区域内获得具有高对比度可见性(较少的反向散射)的水下目标图像,该区域的功率密度与水介质中的光衰减规则成反比。然后,将图像f分解为两个函数u + v的总和,其中u分量通过有界变化函数(f的卡通或粗略近似)建模,而代表纹理或噪声的v分量通过振荡模型建模功能。本文介绍了基于G-Space和PDE的Vese-Osher(VO)模型和Mumford-Shah-G(MS-G)模型进行纹理图像提取。实验结果表明,通过MS-G模型获得水下目标的卡通,纹理成分以及边缘成分是有效的,可应用于水下目标检测的图像重建和目标识别等进一步程序。

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