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基于散斑图案分类的支持向量回归实现透过散射介质成像。

Imaging through scattering media using speckle pattern classification based support vector regression.

作者信息

Chen Hui, Gao Yesheng, Liu Xingzhao, Zhou Zhixin

出版信息

Opt Express. 2018 Oct 1;26(20):26663-26678. doi: 10.1364/OE.26.026663.

Abstract

Imaging through scattering media is a common practice in many applications of biomedical imaging. Object image would deteriorate into unrecognizable speckle pattern when scattering media is presented. Many methods have been investigated to reconstruct the object image when only speckle pattern is available. In this paper, we demonstrate a method of single-shot imaging through scattering media. This method is based on classification and support vector regression of the measured speckle pattern. We prove the possibility of speckle pattern classification and related formulas are presented. The specified and limited imaging capability without speckle pattern classification is demonstrated. Our proposed approach, that is, speckle pattern classification based support vector regression method, makes up the deficiency. Experimental results show that, with our approach, speckle patterns could be utilized for classification when object images are unavailable, and object images can be reconstructed with high fidelity. The proposed approach for imaging through scattering media is expected to be applicable to various sensing schemes.

摘要

在生物医学成像的许多应用中,透过散射介质成像很常见。当存在散射介质时,物体图像会退化为无法识别的散斑图案。当仅有散斑图案可用时,人们研究了许多方法来重建物体图像。在本文中,我们展示了一种透过散射介质的单次成像方法。该方法基于对测量的散斑图案进行分类和支持向量回归。我们证明了散斑图案分类的可能性并给出了相关公式。展示了在没有散斑图案分类情况下特定且有限的成像能力。我们提出的方法,即基于散斑图案分类的支持向量回归方法,弥补了这一不足。实验结果表明,使用我们的方法,在没有物体图像时散斑图案可用于分类,并且物体图像能够以高保真度重建。所提出的透过散射介质成像的方法有望应用于各种传感方案。

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