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Speckle reconstruction method based on machine learning

机译:基于机器学习的斑点重建方法

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Scattering media would deteriorate an object image into unrecognizable speckle pattern. Machine learning is introduced to reconstruct the object image from speckle pattern. In the proposed method, a database containing two groups (i.e., face image-and-speckle-pattern pairs, non-face image-and-speckle-pattern pairs) is firstly established. Then support vector classification (SVC) is introduced to classify a given unknown speckle pattern into which group it belongs to. Taking advantage of support vector regression (SVR), the object image corresponding to the unknown speckle pattern can be reconstructed. Experiments are conducted to verify the effectiveness of the proposed method, as well as the necessity of the introduction of SVC.
机译:散布的介质会使物体图像变成无法识别的斑点图案。引入了机器学习以从斑点图案重建对象图像。在提出的方法中,首先建立包含两个组(即,面部图像和斑点图案对,非面部图像和斑点图案对)的数据库。然后引入支持向量分类(SVC)来将给定的未知散斑图案分类到其所属的组中。利用支持向量回归(SVR),可以重建与未知斑点图案相对应的对象图像。通过实验验证了该方法的有效性以及引入SVC的必要性。

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