Results 1 to 10 of about 6,108,061 (222)
Speckle Decorrelation and Dynamic Range in Speckle Noise Limited Imaging [PDF]
arXiv, 2003 The useful dynamic range of an image in the diffraction limited regime is usually limited by speckles caused by residual phase errors in the optical system forming the image. The technique of speckle decorrelation involves introducing many independent realizations of additional phase error into a wavefront during one speckle lifetime, changing the ...
Anand Sivaramakrishnan +3 more
openalex +3 more sources
Tailoring 3D Speckle Statistics [PDF]
, 2022 We experimentally generate three-dimensional speckles with customized intensity statistics. By modulating the phase front of a laser beam, far-field speckle patterns maintain the designed intensity probability density function while evolving to different spatial patterns upon axial propagation. We also create speckles with distinct intensity statistics
arxiv +1 more source
Optimizing Ghost Imaging via Analysis and Design of Speckle Patterns [PDF]
, 2022 We study the influence rules of the speckle size of light source on ghost imaging, and propose a new type of speckle patterns to improve the quality of ghost imaging. The results show that the image quality will first increase and then decrease with the increase of the speckle size, and there is an optimal speckle size for a specific object.
arxiv +1 more source
Circumventing the optical diffraction limit with customized speckles [PDF]
Optica Vol. 8, Issue 2, pp. 122-129 (2021), 2020 Speckle patterns have been widely used in imaging techniques such as ghost imaging, dynamic speckle illumination microscopy, structured illumination microscopy, and photoacoustic fluctuation imaging. Recent advances in the ability to control the statistical properties of speckles has enabled the customization of speckle patterns for specific imaging ...
arxiv +1 more source
Speckled speckled speckle [PDF]
, 2020 Speckle is the spatial fluctuation of irradiance seen when coherent light is reflected from a rough surface. It is due to light reflected from the surface's many nooks and crannies accumulating vastly-discrepant time delays, spanning much more than an optical period, en route to an observation point.
arxiv +1 more source
Multi-temporal speckle reduction with self-supervised deep neural networks [PDF]
, 2022 Speckle filtering is generally a prerequisite to the analysis of synthetic aperture radar (SAR) images. Tremendous progress has been achieved in the domain of single-image despeckling. Latest techniques rely on deep neural networks to restore the various structures and textures peculiar to SAR images.
arxiv +1 more source
A Practical Solution for SAR Despeckling With Adversarial Learning Generated Speckled-to-Speckled Images [PDF]
IEEE Geoscience and Remote Sensing Letters,(2020)1-5, 2019 In this letter, we aim to address a synthetic aperture radar (SAR) despeckling problem with the necessity of neither clean (speckle-free) SAR images nor independent speckled image pairs from the same scene, and a practical solution for SAR despeckling (PSD) is proposed.
arxiv +1 more source
Deep-learned speckle pattern and its application to ghost imaging [PDF]
arXiv, 2021 In this paper, we present a method for speckle pattern design using deep learning. The speckle patterns possess unique features after experiencing convolutions in Speckle-Net, our well-designed framework for speckle pattern generation. We then apply our method to the computational ghost imaging system.
arxiv
Speckle noise reduction techniques for high-dynamic range imaging [PDF]
ComptesRendusPhysique8:349-354,2007, 2007 High-dynamic range imaging from space in the visible, aiming in particular at the detection of terrestrial exoplanets, necessitates not only the use of a coronagraph, but also of adaptive optics to correct optical defects in real time. Indeed, these defects scatter light and give birth to speckles in the image plane.
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