[HTML][HTML] Deep learning in optical metrology: a review
With the advances in scientific foundations and technological implementations, optical
metrology has become versatile problem-solving backbones in manufacturing, fundamental …
metrology has become versatile problem-solving backbones in manufacturing, fundamental …
Deep learning in the phase extraction of electronic speckle pattern interferometry
W Jiang, T Ren, Q Fu - Electronics, 2024 - mdpi.com
Electronic speckle pattern interferometry (ESPI) is widely used in fields such as materials
science, biomedical research, surface morphology analysis, and optical component …
science, biomedical research, surface morphology analysis, and optical component …
A novel diffusivity function-based image denoising for MRI medical images
Medical imaging is essential for accurate diagnosis. In medical imaging, various algorithms
for image denoising have been developed. However, some drawbacks have been identified …
for image denoising have been developed. However, some drawbacks have been identified …
Optical fringe patterns filtering based on multi-stage convolution neural network
B Lin, S Fu, C Zhang, F Wang, Y Li - Optics and Lasers in Engineering, 2020 - Elsevier
Optical fringe patterns are often contaminated by speckle noise, making it difficult to
accurately and robustly extract their phase fields. To deal with this problem, we propose a …
accurately and robustly extract their phase fields. To deal with this problem, we propose a …
Image denoising for magnetic resonance imaging medical images using improved generalized cross‐validation based on the diffusivity function
S Kollem, K Ramalinga Reddy… - … Journal of imaging …, 2022 - Wiley Online Library
Various image denoising algorithms have been developed for medical imaging. But some
disadvantages have been found, including the block effect, which increases smoothing, and …
disadvantages have been found, including the block effect, which increases smoothing, and …
Batch denoising of ESPI fringe patterns based on convolutional neural network
The denoising of electronic speckle pattern interferometry (ESPI) fringe patterns is a key step
in the application of ESPI. In this paper, we propose a method for batch denoising of ESPI …
in the application of ESPI. In this paper, we propose a method for batch denoising of ESPI …
Single shot fringe pattern phase demodulation using Hilbert-Huang transform aided by the principal component analysis
Hybrid single shot algorithm for accurate phase demodulation of complex fringe patterns is
proposed. It employs empirical mode decomposition based adaptive fringe pattern …
proposed. It employs empirical mode decomposition based adaptive fringe pattern …
U-Net based neural network for fringe pattern denoising
Fringe patterns from different optical measurement systems are widely used in scientific and
engineering applications. However, fringe patterns are often corrupted by speckle noise …
engineering applications. However, fringe patterns are often corrupted by speckle noise …
Fringe pattern denoising using coherence-enhancing diffusion
Electronic speckle pattern interferometry is one of the methods measuring the displacement
on object surfaces in which fringe patterns need to be evaluated. Noise is one of the key …
on object surfaces in which fringe patterns need to be evaluated. Noise is one of the key …
Efficient image denoising technique using the meshless method: Investigation of operator splitting RBF collocation method for two anisotropic diffusion-based PDEs
Images taken and stored digitally are often degraded by noise, so that the perceived image
quality is significantly decreased in the presence of noise and human gaze behavior is …
quality is significantly decreased in the presence of noise and human gaze behavior is …