paper-with-me

홈 › Papers

Multiscale Phase Retrieval

2020-12-09 · David J. Brady, Timothy J. Schulz, Chengyu Wang

While characterization of coherent wavefields is essential to laser, x-ray and electron imaging, sensors measure the squared magnitude of the field, rather than the field itself. Holography or phase retrieval must be used to characterize the field. The need for a reference severely restricts the utility of holography. Phase retrieval, in contrast, is theoretically consistent with sensors that directly measure coherent or partially coherent fields with no prior assumptions. Unfortunately, phase retrieval has not yet been successfully implemented for large-scale fields. Here we show that both holography and phase retrieval are capable of quantum-limited coherent signal estimation and we describe phase retrieval strategies that approach the quantum limit for >1 megapixel fields. These strategies rely on group testing using networks of interferometers, such as might be constructed using emerging integrated photonic, plasmonic and/or metamaterial devices. Phase-sensitive sensor planes using such devices could eliminate the need both for lenses and reference signals, creating a path to large aperture diffraction limited laser imaging.

📄 PDF Abstract BibTeX arXiv:2012.04891

Code (1)

djbradyAtOpticalSciencesArizona/photonLimitedPhaseRetrieval 공식 구현

Tasks

Retrieval

Similar Papers 제목 키워드 기반

Local Conditional Neural Fields for Versatile and Generalizable Large-Scale Reconstructions in Computational Imaging

2023-07-12 · Hao Wang, Jiabei Zhu, Yunzhe Li, QianWan Yang 외

Deep learning has transformed computational imaging, but traditional pixel-based representations limit their ability to capture continuous, multiscale details of objects. Here we introduce a novel Local Conditional Neura…

DecoderImage ReconstructionSuper-Resolution

Efficient texture retrieval using multiscale local extrema descriptors and covariance embedding

2018-08-03 · Minh-Tan Pham

This paper presents an efficient method for texture retrieval using multiscale feature extraction and embedding based on the local extrema keypoints. The idea is to first represent each texture image by its local maximum…

Retrieval

Deep multiscale convolutional feature learning for weakly supervised localization of chest pathologies in X-ray images

2018-08-22 · Suman Sedai, Dwarikanath Mahapatra, ZongYuan Ge, Rajib Chakravorty 외

Localization of chest pathologies in chest X-ray images is a challenging task because of their varying sizes and appearances. We propose a novel weakly supervised method to localize chest pathologies using class aware de…

General Classification

A multiscale analysis of mean-field transformers in the moderate interaction regime

2025-09-29 · Giuseppe Bruno, Federico Pasqualotto, Andrea Agazzi arxiv

In this paper, we study the evolution of tokens through the depth of encoder-only transformer models at inference time by modeling them as a system of particles interacting in a mean-field way and studying the correspond…

Machine learning enhanced data assimilation framework for multiscale carbonate rock characterization

2026-01-27 · Zhenkai Bo, Ahmed H. Elsheikh, Hannah P. Menke, Julien Maes 외 arxiv

Carbonate reservoirs offer significant capacity for subsurface carbon storage, oil production, and underground hydrogen storage. X-ray computed tomography (X-ray CT) coupled with numerical simulations is commonly used to…

Computational Efficiency