Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Light Acquisition02:16

Light Acquisition

8.0K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
8.0K
Photoreceptors and Plant Responses to Light02:00

Photoreceptors and Plant Responses to Light

22.5K
Light plays a significant role in regulating the growth and development of plants. In addition to providing energy for photosynthesis, light provides other important cues to regulate a range of developmental and physiological responses in plants.
22.5K
Phase Contrast and Differential Interference Contrast Microscopy01:26

Phase Contrast and Differential Interference Contrast Microscopy

9.4K
Phase-Contrast Microscopes
In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...
9.4K
Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

12.3K
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...
12.3K

You might also read

Related Articles

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

Sort by
Same author

Atmospheric scattering model and dark channel prior constraint network for environmental monitoring under hazy conditions.

Journal of environmental sciences (China)·2024
Same author

A multi-feature spatial-temporal fusion network for traffic flow prediction.

Scientific reports·2024
Same author

An Innovative Approach for Removing Stripe Noise in Infrared Images.

Sensors (Basel, Switzerland)·2023
Same author

Vibration Detection and Degraded Image Restoration of Space Camera Based on Correlation Imaging of Rolling-Shutter CMOS.

Sensors (Basel, Switzerland)·2023
Same author

An Infrared Stripe Noise Removal Method Based on Multi-Scale Wavelet Transform and Multinomial Sparse Representation.

Computational intelligence and neuroscience·2022
Same author

A Novel Stripe Noise Removal Model for Infrared Images.

Sensors (Basel, Switzerland)·2022
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: May 6, 2026

Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

17.6K

Fast, Zero-Reference Low-Light Image Enhancement with Camera Response Model.

Xiaofeng Wang1,2, Liang Huang1, Mingxuan Li1

  • 1Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China.

Sensors (Basel, Switzerland)
|August 10, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces an efficient low-light image enhancement method using a novel Zero-Reference Camera Response Network. The technique rapidly improves image quality without needing paired data, outperforming existing solutions.

Keywords:
camera response modelconvolutional neural networklow-light image enhancementzero reference

More Related Videos

The Optokinetic Response as a Quantitative Measure of Visual Acuity in Zebrafish
04:56

The Optokinetic Response as a Quantitative Measure of Visual Acuity in Zebrafish

Published on: October 9, 2013

20.5K
Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

8.9K

Related Experiment Videos

Last Updated: May 6, 2026

Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

17.6K
The Optokinetic Response as a Quantitative Measure of Visual Acuity in Zebrafish
04:56

The Optokinetic Response as a Quantitative Measure of Visual Acuity in Zebrafish

Published on: October 9, 2013

20.5K
Visualizing Visual Adaptation
04:43

Visualizing Visual Adaptation

Published on: April 24, 2017

8.9K

Area of Science:

  • Computer Vision
  • Image Processing
  • Artificial Intelligence

Background:

  • Low-light images pose significant challenges in applications like intelligent monitoring due to reduced brightness.
  • Existing low-light image enhancement methods often suffer from complex network structures and slow processing speeds.

Purpose of the Study:

  • To propose an efficient and effective low-light image enhancement method.
  • To develop a network that enhances arbitrary low-light images without requiring reference data.

Main Methods:

  • A Zero-Reference Camera Response Network is proposed, utilizing a camera response model.
  • A streamlined, double-layer parameter-generating network extracts the exposure ratio (K) from a radiation map.
  • Brightness transformation is applied using K, incorporating contrast-preserving and edge-preserving losses.

Main Results:

  • The proposed method achieves efficient enhancement for arbitrary low-light images.
  • The enhancement process is simplified, achieving over twice the speed of similar methods.
  • Experiments demonstrate significant subjective and objective advantages on various low-light image enhancement (LLIE) and face detection datasets.

Conclusions:

  • The Zero-Reference Camera Response Network offers a fast and effective solution for low-light image enhancement.
  • The method successfully enhances image quality while preserving crucial information like contrast and edges.
  • This approach provides a valuable tool for applications requiring high-performance low-light image processing.