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In the reconstruction process of unknown multiple scattering objects in inverse medium scattering problems, the first important step is to effectively locate some approximate domains that contain all inhomogeneous media. Without such an…

Numerical Analysis · Mathematics 2015-06-12 Keji Liu , Jun Zou

Diffraction tomography aims to recover an object's scattering potential from measured wave fields. In the classical setting, the object is illuminated by plane waves from many directions, and the Fourier diffraction theorem provides a…

Numerical Analysis · Mathematics 2026-03-11 Peter Elbau , Noemi Naujoks

Multiple scattering of waves in disordered media is a nightmare whether it be for detection or imaging purposes. The best approach so far to get rid of multiple scattering is optical coherence tomography. It basically combines confocal…

Deconvolution of astronomical images is a key aspect of recovering the intrinsic properties of celestial objects, especially when considering ground-based observations. This paper explores the use of diffusion models (DMs) and the Diffusion…

Instrumentation and Methods for Astrophysics · Physics 2025-01-22 Alessio Spagnoletti , Alexandre Boucaud , Marc Huertas-Company , Wassim Kabalan , Biswajit Biswas

We have developed a method for the linear reconstruction of an image from undersampled, dithered data. The algorithm, known as Variable-Pixel Linear Reconstruction, or informally as Drizzle, preserves photometry and resolution, can weight…

Astrophysics · Physics 2011-08-11 A. S. Fruchter , R. N. Hook

In this paper, we present a novel reconstruction method for diffuse optical spectroscopic imaging with a commonly used tissue model of optical absorption and scattering. It is based on linearization and group sparsity, which allows…

Numerical Analysis · Mathematics 2019-03-06 Habib Ammari , Bangti Jin , Wenlong Zhang

Inverse scattering in layered media has a wide range of applications, examples including geophysical exploration, medical imaging, and remote sensing. In this paper, we develop a selective focusing method for identifying multiple unknown…

Numerical Analysis · Mathematics 2025-05-27 Jun Lai , Jinrui Zhang

The distortion of light's degrees of freedom when passing through complex random media is of great interest across a diversity of fields, e.g., scattering in biological studies. Emulating such media in a controlled laboratory setting…

Optics · Physics 2026-05-13 Kelsey Everts , Cade Peters , Andrew Forbes

Convergent beam electron diffraction (CBED) performed on two-dimensional (2D) materials recently emerged as a powerful tool to study structural and stacking defects, adsorbates, atomic 3D displacements in the layers, and the interlayer…

Mesoscale and Nanoscale Physics · Physics 2022-01-25 Tatiana Latychevskaia , Sarah Haigh , Kostya Novoselov

In optical imaging, light propagation is affected by the inhomogeneities of the medium. Sample-induced aberrations and multiple scattering can strongly degrade the image resolution and contrast. Based on a dynamic correction of the incident…

Multiple optical scattering occurs when light propagates in a non-uniform medium. During the multiple scattering, images were distorted and the spatial information they carried became scrambled. However, the image information is not lost…

Computer Vision and Pattern Recognition · Computer Science 2021-07-30 Xinyu Gao , Yi Li , Yanqing Qiu , Bangning Mao , Miaogen Chen , Yanlong Meng , Chunliu Zhao , Juan Kang , Yong Guo , Changyu Shen

This work is motivated by multimodality breast cancer imaging data, which is quite challenging in that the signals of discrete tumor-associated microvesicles (TMVs) are randomly distributed with heterogeneous patterns. This imposes a…

Machine Learning · Statistics 2019-03-22 Xiwei Tang , Xuan Bi , Annie Qu

We present Wideband Back-Projection Diffusion, an end-to-end probabilistic framework for approximating the posterior distribution induced by the inverse scattering map from wideband scattering data. This framework produces highly accurate…

Machine Learning · Computer Science 2025-05-20 Borong Zhang , Martín Guerra , Qin Li , Leonardo Zepeda-Núñez

Electron backscatter diffraction is a widely used technique for nano- to micro-scale analysis of crystal structure and orientation. Backscatter patterns produced by an alloy solid solution matrix and its ordered superlattice exhibit only…

Materials Science · Physics 2020-10-13 Thomas P McAuliffe , David Dye , T Ben Britton

Mesoscopic interference effects in multiple scattering of photons depend crucially on the internal structure of the scatterers. In the present article, we develop the analytical theory of multiple photon scattering by cold atoms with…

Hyperspectral imaging is useful for applications ranging from medical diagnostics to agricultural crop monitoring; however, traditional scanning hyperspectral imagers are prohibitively slow and expensive for widespread adoption. Snapshot…

Image and Video Processing · Electrical Eng. & Systems 2020-09-30 Kristina Monakhova , Kyrollos Yanny , Neerja Aggarwal , Laura Waller

High-fidelity spectrum cartography is pivotal for spectrum management and wireless situational awareness, yet it remains a challenging ill-posed inverse problem due to the sparsity and irregularity of observations. Furthermore, existing…

Information Theory · Computer Science 2025-12-24 Yuntong Gu , Xiangming meng , Zhiyuan Lin , Sheng Wu , Linling Kuang

In both light optics and electron optics, the amplitude of a wave scattered by an object is an observable that is usually recorded in the form of an intensity distribution in a real space image or a diffraction image. In contrast, retrieval…

This paper proposes a non-computational method of counteracting the effect of image degradation introduced by the diffraction phenomenon in lensless microscopy. All the optical images (whether focused by lenses or not) are diffraction…

Optics · Physics 2021-04-08 Sanjeev Kumar , Manjunatha Mahadevappa , Pranab Kumar Dutta

In this paper, we propose Neural Spectrum Decomposition, a generic decomposition framework for dataset distillation. Unlike previous methods, we consider the entire dataset as a high-dimensional observation that is low-rank across all…

Computer Vision and Pattern Recognition · Computer Science 2024-08-30 Shaolei Yang , Shen Cheng , Mingbo Hong , Haoqiang Fan , Xing Wei , Shuaicheng Liu
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