Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Super-resolution Fluorescence Microscopy

Super-resolution Fluorescence Microscopy

Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Valuation of the cultural adaptation and psychometric properties of the Chinese version of the hidden curriculum evaluation scale in nursing education.

Nurse education in practice·2024

Same author

Advanced Polymeric Nanoagents for Oral Cancer Theranostics: A Mini Review.

Frontiers in chemistry·2022

Same author

Compressive Sensing via Nonlocal Smoothed Rank Function.

PloS one·2016

Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026

Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026

Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026

Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026

Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026

Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Aug 9, 2025

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

Robust Superpixel Segmentation for Hyperspectral-Image Restoration.

¹School of Mathematics, Southwest Minzu University, Chengdu 610041, China.

Entropy (Basel, Switzerland)

|February 25, 2023

Summary

This summary is machine-generated.

This study introduces a new superpixel segmentation strategy for hyperspectral image (HSI) restoration, enhancing low-rank properties and improving noise removal for better remote sensing data processing.

Keywords:

hyperspectral-image restoration principal component robust superpixel segmentation weighted nuclear norm

More Related Videos

RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols

RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols

Published on: August 8, 2017

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Published on: August 22, 2019

Related Experiment Videos

Last Updated: Aug 9, 2025

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols

RGB and Spectral Root Imaging for Plant Phenotyping and Physiological Research: Experimental Setup and Imaging Protocols

Published on: August 8, 2017

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Published on: August 22, 2019

Area of Science:

Remote Sensing
Image Processing
Computer Vision

Background:

Hyperspectral image (HSI) restoration is crucial for remote sensing.
Superpixel segmentation-based low-rank methods show promise but have limitations.
Current methods often use suboptimal segmentation based on the first principal component.

Purpose of the Study:

To propose a robust superpixel segmentation strategy for HSI restoration.
To enhance the low-rank attribute of hyperspectral images.
To improve the efficiency of mixed noise removal in degraded HSIs.

Main Methods:

Integrating superpixel segmentation with principal component analysis for improved HSI segmentation.
Developing a weighted nuclear norm with three weighting types for noise removal.
Applying the proposed method to simulated and real hyperspectral image data.

Main Results:

The proposed robust superpixel segmentation strategy effectively enhances the low-rank attribute of HSIs.
The weighted nuclear norm efficiently removes mixed noise from degraded HSIs.
Experimental results demonstrate superior performance compared to existing methods.

Conclusions:

The developed method offers a significant advancement in hyperspectral image restoration.
The enhanced segmentation and noise removal techniques improve the quality of processed remote sensing data.
The approach is validated on both synthetic and real-world hyperspectral datasets.