Results 51 to 60 of about 111,380 (310)
Denoising of Wrapped Phase in Digital Speckle Shearography Based on Convolutional Neural Network
Applied SciencesSpeckle-shearing technology is widely used in defect detection due to its high precision and non-contact characteristics. However, the wrapped-phase recording defect information is often accompanied by a lot of speckle noise, which affects the evaluation
Hao Zhang, Dawei Huang, Kaifu Wang
doaj +1 more source
Speckle Temporal Stability in eXtreme Adaptive Optics Coronagraphic Images [PDF]
, 2012 The major noise source limiting high-contrast imaging is due to the presence of quasi-static speckles. Speckle noise originates from wavefront errors caused by various independent sources, and it evolves on different timescales pending to their nature.
arxiv +1 more source
Toward ground-truth optical coherence tomography via three-dimensional unsupervised deep learning processing and data [PDF]
arXiv, 2023 Optical coherence tomography (OCT) can perform non-invasive high-resolution three-dimensional (3D) imaging and has been widely used in biomedical fields, while it is inevitably affected by coherence speckle noise which degrades OCT imaging performance and restricts its applications.
arxiv
Single-shot x-ray speckle-based imaging of a single-material object [PDF]
Phys. Rev. Applied 13, 054023 (2020), 2019 We develop a means for speckle-based phase imaging of the projected thickness of a single-material object, under the assumption of illumination by spatially random time-independent x-ray speckles. These speckles are generated by passing x rays through a suitable spatially random mask.
arxiv +1 more source
DeepLSR: a deep learning approach for laser speckle reduction [PDF]
, 2018 Speckle artifacts degrade image quality in virtually all modalities that utilize coherent energy, including optical coherence tomography, reflectance confocal microscopy, ultrasound, and widefield imaging with laser illumination. We present an adversarial deep learning framework for laser speckle reduction, called DeepLSR (https://durr.jhu.edu/DeepLSR),
arxiv +1 more source
Suppression of Speckle Noise in Digital Holography With Spatial and Temporal Domain Depolarization
IEEE Access, 2020 Speckle noise in digital holography has a great influence on image quality, and one of the reasons for the formation of speckle noise is that the degree of coherence for the reference light and the object light is too high and unnecessary noise is ...
Tongyao Du +4 more
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A review of artificial intelligence in brachytherapy
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Artificial intelligence (AI) has the potential to revolutionize brachytherapy's clinical workflow. This review comprehensively examines the application of AI, focusing on machine learning and deep learning, in various aspects of brachytherapy.
Jingchu Chen +4 more
wiley +1 more source
Speckle Reduction in Digital Holography by Fast Logistic Adaptive Non-Local Means Filtering
PhotonicsDigital holography is a promising imaging technology. However, there is speckle noise in the reconstructed image of a digital hologram. Speckle degrades the quality of the reconstructed image.
Yiping Fu, Junmin Leng, Zhenqi Xu
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Heliyon, 2023 Optical coherence tomography (OCT) imaging is a technique that is frequently used to diagnose medical conditions. However, coherent noise, sometimes referred to as speckle noise, can dramatically reduce the quality of OCT images, which has an adverse ...
Ying Fang +3 more
doaj
arXiv, 2022 Speckle patterns are formed by random interferences of mutually coherent beams. While speckles are often considered as an unwanted noise in many areas, they also formed the foundation for the development of numerous speckle-based imaging, holography and sensing technologies.
arxiv