Image decomposition model Shearlet-Hilbert-L-2 with better performance for denoising in ESPI fringe patterns

Xu Wenjun; Tang Chen; Su Yonggang; Li Biyuan; Lei Zhenkun

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Image decomposition model Shearlet-Hilbert-L-2 with better performance for denoising in ESPI fringe patterns

机译：图像分解模型Shearlet-Hilbert-L-2具有更好的性能，用于ESPI边缘图案中的去噪

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In this paper, we propose an image decomposition model Shearlet-Hilbert-L-2 with better performance for denoising in electronic speckle pattern interferometry (ESPI) fringe patterns. In our model, the low-density fringes, high-density fringes, and noise are, respectively, described by shearlet smoothness spaces, adaptive Hilbert space, and L-2 space and processed individually. Because the shearlet transform has superior directional sensitivity, our proposed Shearlet-Hilbert-L-2 model achieves commendable filtering results for various types of ESPI fringe patterns, including uniform density fringe patterns, moderately variable density fringe patterns, and greatly variable density fringe patterns. We evaluate the performance of our proposed Shearlet-Hilbert-L-2 model via application to two computer-simulated and nine experimentally obtained ESPI fringe patterns with various densities and poor quality. Furthermore, we compare our proposed model with windowed Fourier filtering and coherence-enhancing diffusion, both of which are the state-of-the-art methods for ESPI fringe patterns denoising in transform domain and spatial domain, respectively. We also compare our proposed model with the previous image decomposition model BL-Hilbert-L-2. (C) 2018 Optical Society of America

机译：在本文中，我们提出了一种图像分解模型Shearlet-Hilbert-L-2，具有更好的性能，用于在电子散斑图案干涉法（ESPI）条纹图案中的去噪。在我们的模型中，低密度条纹，高密度条纹和噪声分别由Shearlet平滑度空间，自适应Hilbert空间和L-2空间描述并单独处理。由于Shearlet变换具有卓越的方向灵敏度，所以我们提出的Shearlet-Hilbert-L-2模型可实现各种类型的ESPI条纹图案的可称为滤波结果，包括均匀的密度条纹图案，适度可变密度条纹图案和极大的密度条纹图案。我们通过应用于两台计算机模拟和九个实验获得的ESPI条纹图案来评估我们提出的Shearlet-Hilbert-L-2模型的性能，具有各种密度和质量差。此外，我们将所提出的模型与窗帘傅里叶滤波和相干增强的扩散进行比较，这两者都分别是在变换域和空间域中脱颖而出的ESPI条纹图案的最先进的方法。我们还将所提出的模型与先前的图像分解模型BL-HILBERT-L-2进行比较。（c）2018年光学学会

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来源
《Applied optics》 |2018年第4期|共11页
作者
Xu Wenjun; Tang Chen; Su Yonggang; Li Biyuan; Lei Zhenkun;
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作者单位

Tianjin Univ Sch Elect &

Informat Engn Tianjin 300072 Peoples R China;

Tianjin Univ Sch Elect &

Informat Engn Tianjin 300072 Peoples R China;

Tianjin Univ Sch Elect &

Informat Engn Tianjin 300072 Peoples R China;

Tianjin Univ Sch Elect &

Informat Engn Tianjin 300072 Peoples R China;

Dalian Univ Technol State Key Lab Struct Anal Ind Equipment Dalian 116024 Peoples R China;

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Image decomposition model Shearlet-Hilbert-L-2 with better performance for denoising in ESPI fringe patterns

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