We propose quantitative localization measurement of a known object with subpixel accuracy using compressive holography. We analyze the theoretical optimal solution in the compressive sampling framework and experimentally demonstrate localization accuracy of 1/45 pixel, in good agreement with the analysis.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1364/OL.37.003357 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
We propose a non-cascaded and crosstalk-free multi-image encryption method based on optical scanning holography and 2D orthogonal compressive sensing. This approach enables the simultaneous recording and encryption of multiple plaintext images without mechanical scanning, while allows for independent retrieval of each image with exceptional quality and no crosstalk. Two features would bring about more substantial security and privacy.
View Article and Find Full Text PDFCustomized Pore Creation Strategies for Hyperelastic, Robust, Insulating Multifunctional MXene Aerogels for Microwave Absorption.
ACS Appl Mater Interfaces
September 2024
Laboratory of Advanced Materials, Shanghai Key Lab of Molecular Catalysis and Innovative Materials, Academy for Engineering & Technology, Fudan University, Shanghai 200438, China.
The construction of heterogeneous microstructure and the selection of multicomponents have turned into a research hotspot in developing ultralight, multifunctional, high-efficiency electromagnetic wave absorbing (EMA) materials. Although aerogels are promising materials to fulfill the above requirements, the increase in functional fillers inevitably leads to the deterioration of intrinsic properties. Tuning the electromagnetic properties from the structural design point of view remains a difficult challenge.
View Article and Find Full Text PDFSparse reconstruction of sound field using pattern-coupled Bayesian compressive sensing.
J Acoust Soc Am
July 2024
School of Mechanical Engineering, Nanchang Institute of Technology, Nanchang 330099, People's Republic of China.
Article Synopsis
- Conventional near-field acoustic holography often struggles with accurately reconstructing sound fields due to inadequate handling of block-sparse structures and mismatched block partitions.
- This paper introduces a novel method using pattern-coupled Bayesian compressive sensing that leverages a hierarchical Gaussian-Gamma model to improve sparse reconstruction of sound fields.
- The new approach allows for better identification of equivalent source strengths by employing hyperparameters that govern the sparsity of coefficients while considering neighboring elements, leading to enhanced reconstruction performance validated through simulations and experiments.
Single-pixel Fresnel incoherent correlation holography compressed imaging using a Trumpet network.
Sci Rep
June 2024
School of Electronics and Information, Guangdong Polytechnic Normal University, Guangzhou, 510665, China.
Article Synopsis
- Fresnel incoherent correlation holography (FINCH) traditionally faces challenges with its high bandwidth requirements and expensive high-resolution imaging hardware, which limits its practical applications.
- A new method called single-pixel Fresnel incoherent correlation holography (SP-FINCH) has been introduced, which utilizes a single-pixel detector and employs a Trumpet network for improved cost-effectiveness and resolution.
- This innovative approach demonstrates significantly better image reconstruction quality at lower sampling rates when compared to standard single-pixel methods, without needing phase-shifting processes, backed by numerical simulations and experimental results.
Fast 3D volume imaging methods have been playing increasingly important roles in biological studies. In this article, we present the design and characterization of a multi-focus line-scanning two-photon microscope. Specifically, a digital micromirror device (DMD) is employed to generate a randomly distributed focus array on a plane (i.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!