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基于变分图像分解的梯度向量场用于具有可变密度的电子散斑图案干涉条纹图案的骨架化及其应用。

Gradient vector fields based on variational image decomposition for skeletonization of electronic speckle pattern interferometry fringe patterns with variable density and their applications.

作者信息

Chen Xia, Tang Chen, Li Biyuan, Su Yonggang

出版信息

Appl Opt. 2016 Sep 1;55(25):6893-902. doi: 10.1364/AO.55.006893.

Abstract

The skeletonization methods based on gradient vector fields (GVFs) have been a powerful tool for electronic speckle pattern interferometry (ESPI) fringe patterns. However, the skeletonization of ESPI fringe patterns with variable density has been an open problem in this area. In this paper, we propose a novel method for calculating GVFs based on the variational image decomposition of ESPI fringe patterns with variable density. In the proposed method, the GVFs of low-density regions are described in Beppo-Levi space, the high-density regions in Hilbert space and the noise regions in curvelet space. The GVFs of a whole image are the sum of the decomposed GVFs of low-density regions and high-density regions. The skeletons of ESPI fringe patterns with variable density can be obtained based on the topological analysis of the GVFs of a whole image. We apply the proposed method to a computer-simulated and two experimentally obtained ESPI fringe patterns with variable density and compare them with the related skeleton methods based on GVFs. The experimental results have demonstrated that the proposed method outperforms the other methods, even when the quality of the ESPI fringe patterns is considerably low.

摘要

基于梯度向量场(GVFs)的骨架化方法一直是电子散斑图案干涉术(ESPI)条纹图案的有力工具。然而,可变密度的ESPI条纹图案的骨架化在该领域一直是一个未解决的问题。在本文中,我们提出了一种基于可变密度的ESPI条纹图案变分图像分解来计算GVFs的新方法。在所提出的方法中,低密度区域的GVFs在贝波 - 列维空间中描述,高密度区域在希尔伯特空间中描述,噪声区域在曲波空间中描述。整个图像的GVFs是低密度区域和高密度区域分解后的GVFs之和。基于整个图像GVFs的拓扑分析,可以得到可变密度的ESPI条纹图案的骨架。我们将所提出的方法应用于计算机模拟的以及两个实验获得的可变密度的ESPI条纹图案,并将它们与基于GVFs的相关骨架方法进行比较。实验结果表明,即使ESPI条纹图案的质量相当低,所提出的方法也优于其他方法。

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