Speckle masking is a method for reconstructing high-resolution images of general astronomical objects from stellar speckle interferograms. In speckle masking no unresolvable star is required within the isoplanatic patch of the object. We present digital applications of speckle masking to close spectroscopic double stars. The speckle interferograms were recorded with the European Southern Observatory's 3.6-m telescope. Diffraction-limited resolution (0.03 arc see) was achieved, which is about 30 times higher than the resolution of conventional astrophotography.
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http://dx.doi.org/10.1364/ol.8.000389 | DOI Listing |
Transl Vis Sci Technol
December 2024
Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria.
Purpose: Currently, no standard for the measurement of retinal oxygen extraction exists. Here, we present a novel approach for measurement of retinal oxygen extraction based on two commercially available devices, namely laser speckle flowgraphy (LSFG) and retinal oximetry.
Methods: The study was conducted in a randomized, double-masked design.
Sci Total Environ
October 2024
Department of Global Smart City, Sungkyunkwan University, Suwon 440-746, Republic of Korea; Department of Water Resources, Graduate School of Water Resources, Sungkyunkwan University, Suwon 440-746, Republic of Korea; School of Civil, Architectural Engineering & Landscape Architecture, Sungkyunkwan University, Suwon 440-746, Republic of Korea. Electronic address:
Continuous monitoring of reservoirs and dams is essential for efficient water management. Synthetic Aperture Radar (SAR) imagery offers the potential for continuous monitoring of surface water through all-weather ground observation. The objective of this study is to enhance the accuracy of water body detection and water quantity estimation by applying 64 combinations of speckle filtering and object detection techniques to Sentinel-1 imagery.
View Article and Find Full Text PDFBiomed Opt Express
April 2024
Centre for Ophthalmology and Visual Science, Medical School, University of Western Australia (UWA), WA, Australia.
OCT is a widely used clinical ophthalmic imaging technique, but the presence of speckle noise can obscure important pathological features and hinder accurate segmentation. This paper presents a novel method for denoising optical coherence tomography (OCT) images using a combination of texture loss and generative adversarial networks (GANs). Previous approaches have integrated deep learning techniques, starting with denoising Convolutional Neural Networks (CNNs) that employed pixel-wise losses.
View Article and Find Full Text PDFWe experimentally generate nondiffracting speckles that carry non-Markovian properties by encoding the wavefront of a monochromatic laser beam with ring-shaped non-Markovian phases. The resulting non-Markovian nondiffracting fields present a ring-shaped pattern and central dark notches, which are analyzed with an expression of the orbital angular momentum spectra of the wavefront possessing ring-shaped non-Markovian phases. Furthermore, we demonstrate that the intensity profiles of these non-Markovian nondiffracting fields exhibit stability over multiple Rayleigh ranges, and their statistical properties could be controlled with the non-Markovianity of the input phase masks.
View Article and Find Full Text PDFRecently, deep learning-based methods have emerged as the preferred approach for ultrasound data analysis. However, these methods often require large-scale annotated datasets for training deep models, which are not readily available in practical scenarios. Additionally, the presence of speckle noise and other imaging artifacts can introduce numerous hard examples for ultrasound data classification.
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