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The ability to form images through hair-thin optical fibres promises to open up new applications from biomedical imaging to industrial inspection. Unfortunately, deployment has been limited because small changes in mechanical deformation…

We present Intrinsic Image Diffusion, a generative model for appearance decomposition of indoor scenes. Given a single input view, we sample multiple possible material explanations represented as albedo, roughness, and metallic maps.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Peter Kocsis , Vincent Sitzmann , Matthias Nießner

Expansion of diffusion MRI (dMRI) both into the realm of strong gradients, and into accessible imaging with portable low-field devices, brings about the challenge of gradient nonlinearities. Spatial variations of the diffusion gradients…

Diffusion Tensor Imaging (DTI) is a non-invasive imaging technique that allows estimation of the location of white matter tracts in-vivo, based on the measurement of water diffusion properties. For each voxel, a second-order tensor can be…

Computer Vision and Pattern Recognition · Computer Science 2013-10-24 Miriam H. A. Bauer , Sebastiano Barbieri , Jan Klein , Jan Egger , Daniela Kuhnt , Bernd Freisleben , Horst K. Hahn , Christopher Nimsky

Anisotropic Diffusion is widely used for noise reduction with simultaneous preservation of vascular structures in maximum intensity projected (MIP) angiograms. However, extension to minimum intensity projected (mIP) venograms in…

Computer Vision and Pattern Recognition · Computer Science 2015-01-15 P. K. Akshara , J. S. Paul

This letter proposes a sparse diffusion steepest-descent algorithm for one bit compressed sensing in wireless sensor networks. The approach exploits the diffusion strategy from distributed learning in the one bit compressed sensing…

Machine Learning · Statistics 2016-01-05 Hadi Zayyani , Mehdi Korki , Farrokh Marvasti

The paper develops a new integral micromorphic elastic continuum model, which can describe dispersion properties of band-gap metamaterials, i.e., metamaterials that inhibit propagation of waves in a certain frequency range. The enrichment…

Applied Physics · Physics 2024-10-21 Michal Šmejkal , Milan Jirásek , Martin Horák

We propose a linear algebraic framework for performing density estimation. It consists of three simple steps: convolving the empirical distribution with certain smoothing kernels to remove the exponentially large variance; compressing the…

Numerical Analysis · Mathematics 2025-10-29 Yifan Peng , Siyao Yang , Yuehaw Khoo , Daren Wang

Diffusion magnetic resonance imaging (dMRI) is a crucial non-invasive technique for exploring the microstructure of the living human brain. Traditional hand-crafted and model-based tissue microstructure reconstruction methods often require…

Image and Video Processing · Electrical Eng. & Systems 2025-02-26 Xinrui Ma , Jian Cheng , Wenxin Fan , Ruoyou Wu , Yongquan Ye , Shanshan Wang

Diffusion-based image compression methods have achieved notable progress, delivering high perceptual quality at low bitrates. However, their practical deployment is hindered by significant inference latency and heavy computational overhead,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Yiwen Jia , Hao Wei , Yanhui Zhou , Chenyang Ge

In this paper, we introduce tensor involved peridynamics, a unified framework for simulating both isotropic and anisotropic materials. While traditional peridynamics models effectively simulate isotropic materials, they face challenges with…

Materials Science · Physics 2024-12-23 Hao Tian , Jinlong Shao , Chenguang Liu , Shuo Liu , Xu Guo

Conventional endoscopes comprise a bundle of optical fibers, associating one fiber for each pixel in the image. In principle, this can be reduced to a single multimode optical fiber (MMF), the width of a human hair, with one fiber…

Image and Video Processing · Electrical Eng. & Systems 2023-07-13 Abdullah Abdulaziz , Simon Peter Mekhail , Yoann Altmann , Miles J. Padgett , Stephen McLaughlin

In fully-developed pressure-driven flow, the spreading of a dissolved solute is enhanced in the flow direction due to transverse velocity variations in a phenomenon now commonly referred to as Taylor-Aris dispersion. It is well understood…

Fluid Dynamics · Physics 2022-10-04 Garam Lee , Alan Luner , Jeremy Marzuola , Daniel M. Harris

Anisotropic diffusion processes emerge in various fields such as transport in biological tissue and diffusion in liquid crystals. In such systems, the motion is described by a diffusion tensor. For a proper characterization of processes…

Data Analysis, Statistics and Probability · Physics 2013-11-14 Mario Heidernätsch , Michael Bauer , Günter Radons

We demonstrate that the diffusion coefficient, $D$, for ultrasound propagating in a multiple scattering medium, such as a dense granular suspension, can be measured using a time reversal experiment. This requires an unprecedented…

Soft Condensed Matter · Physics 2025-02-27 Y. Abraham , B. A. van Tiggelen , N. Benech , C. Negreira , X. Jia , A. Tourin

Control of dispersion in fibre optical waveguides is of critical importance to optical fibre communications systems and more recently for continuum generation from the ultraviolet to the mid-infrared. The wavelength at which the group…

Linear encoding of sparse vectors is widely popular, but is commonly data-independent -- missing any possible extra (but a priori unknown) structure beyond sparsity. In this paper we present a new method to learn linear encoders that adapt…

Diffusion-weighted magnetic resonance imaging (DW-MRI) can be used to characterise the microstructure of the nervous tissue, e.g. to delineate brain white matter connections in a non-invasive manner via fibre tracking. Magnetic Resonance…

In order to reach the sensitivity required to detect gravitational waves, pulsar timing array experiments need to mitigate as much noise as possible in timing data. A dominant amount of noise is likely due to variations in the dispersion…

Instrumentation and Methods for Astrophysics · Physics 2015-06-19 K. J. Lee , C. G. Bassa , G. H. Janssen , R. Karuppusamy , M. Kramer , K. Liu , D. Perrodin , R. Smits , B. W. Stappers , R. van Haasteren , L. Lentati

Blind deconvolution problems are severely ill-posed because neither the underlying signal nor the forward operator are not known exactly. Conventionally, these problems are solved by alternating between estimation of the image and kernel…

Image and Video Processing · Electrical Eng. & Systems 2023-12-06 Yash Sanghvi , Yiheng Chi , Stanley H. Chan