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The accurate determination and control of the wavelength of light is fundamental to many fields of science. Speckle patterns resulting from the interference of multiple reflections in disordered media are well-known to scramble the…

Laser speckle, the granular intensity pattern arising from random optical interference, provides a high-dimensional encoding of spectral information that can be exploited for precision metrology. Speckle-based spectrometers have advanced…

Laser speckle can provide a powerful tool that may be used for metrology, for example measurements of the incident laser wavelength with a resolution beyond that which may be achieved in a commercial device. However, to realise highest…

Optics · Physics 2020-03-23 Laura O'Donnell , Kishan Dholakia , Graham D. Bruce

We propose an end-to-end deep learning framework that comprehensively solves the inverse wave scattering problem across all length scales. Our framework consists of the newly introduced wide-band butterfly network coupled with a simple…

Numerical Analysis · Mathematics 2021-06-03 Matthew Li , Laurent Demanet , Leonardo Zepeda-Núñez

We demonstrate the use of deep learning for fast spectral deconstruction of speckle patterns. The artificial neural network can be effectively trained using numerically constructed multispectral datasets taken from a measured spectral…

Image and Video Processing · Electrical Eng. & Systems 2019-07-16 Ulas Kürüm , P. R. Wiecha , Rebecca French , Otto L. Muskens

Many areas of optical science require an accurate measurement of optical spectra. Devices based on laser speckle promise compact wavelength measurement, with attometer-level sensitivity demonstrated for single wavelength laser fields. The…

Microscopes and various forms of interferometers have been used for decades in optical metrology of objects that are typically larger than the wavelength of light {\lambda}. However, metrology of subwavelength objects was deemed impossible…

Laser cutting is a widely adopted technology in material processing across various industries, but it generates a significant amount of dust, smoke, and aerosols during operation, posing a risk to both the environment and workers' health.…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Mohamed Abdallah Salem , Hamdy Ahmed Ashur , Ahmed Elshinnawy

The measurement of the wavelength of light using speckle is a promising tool for the realization of compact and precise wavemeters and spectrometers. However, the resolution of these devices is limited by strong correlations between the…

Optics · Physics 2019-09-04 Graham D. Bruce , Laura O'Donnell , Mingzhou Chen , Kishan Dholakia

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…

Computer Vision and Pattern Recognition · Computer Science 2019-07-01 Taylor L. Bobrow , Faisal Mahmood , Miguel Inserni , Nicholas J. Durr

Ultrafast lasers ($< 500$ fs) have enabled laser-matter interactions at intensities exceeding $10^{18} \rm{Wcm}^{-2}$ with only millijoules of laser energy. However, as pulse durations become shorter, larger spectral bandwidths are…

Speckle is a wave interference phenomenon that has been studied in various fields, including optics, hydrodynamics and acoustics. Speckle patterns contain spectral information of the interfering waves, and of the scattering medium that…

We present a design concept for a speckle based wavemeter that combines high spectral resolution and fast response times. Our device uses a fixed disperse medium with small coherence length as an optical pre-processor and a series of…

Optics · Physics 2023-03-02 Lucas Rodrigo Mendicino , Christian Tomás Schmiegelow

Synthetic aperture radar (SAR) images are affected by a spatially-correlated and signal-dependent noise called speckle, which is very severe and may hinder image exploitation. Despeckling is an important task that aims at removing such…

Image and Video Processing · Electrical Eng. & Systems 2021-05-04 Giulia Fracastoro , Enrico Magli , Giovanni Poggi , Giuseppe Scarpa , Diego Valsesia , Luisa Verdoliva

Machine Learning and Deep Learning are computational tools that fall within the domain of artificial intelligence. In recent years, numerous research works have advanced the application of machine and deep learning in various fields,…

The growing field of nano nuclear magnetic resonance (nano-NMR) seeks to estimate spectra or discriminate between spectra of minuscule amounts of complex molecules. While this field holds great promise, nano-NMR experiments suffer from…

Quantum Physics · Physics 2019-12-02 Nati Aharon , Amit Rotem , Liam P. McGuinness , Fedor Jelezko , Alex Retzker , Zohar Ringel

Far-field characterization of small objects is severely constrained by the diffraction limit. Existing tools achieving sub-diffraction resolution often utilize point-by-point image reconstruction via scanning or labelling. Here, we present…

Spectroscopy has played the key role in revealing, and thereby understanding, the structure of atoms and molecules. A central drive in this field is the pursuit of higher precision and accuracy so that ever more subtle effects might be…

In this paper, we proposed to investigate unsupervised anomaly detection in Synthetic Aperture Radar (SAR) images. Our approach considers anomalies as abnormal patterns that deviate from their surroundings but without any prior knowledge of…

Computer Vision and Pattern Recognition · Computer Science 2022-10-31 Max Muzeau , Chengfang Ren , Sébastien Angelliaume , Mihai Datcu , Jean-Philippe Ovarlez

We demonstrate a smart laser-diffraction analysis technique for particle mixture identification. We retrieve information about the size, geometry, and ratio concentration of two-component heterogeneous particle mixtures with an efficiency…

Image and Video Processing · Electrical Eng. & Systems 2022-02-03 Arturo Villegas , Mario A. Quiroz-Juarez , Alfred U'Ren , Juan P. Torres , Roberto de J. Leon-Montiel
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