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

Color Vision01:24

Color Vision

1.2K
Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.
1.2K
Deconvolution01:20

Deconvolution

450
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
450
Photoreceptors and Visual Pathways01:22

Photoreceptors and Visual Pathways

8.3K
At the molecular level, visual signals trigger transformations in photopigment molecules, resulting in changes in the photoreceptor cell's membrane potential. The photon's energy level is denoted by its wavelength, with each specific wavelength of visible light associated with a distinct color. The spectral range of visible light, classified as electromagnetic radiation, spans from 380 to 720 nm. Electromagnetic radiation wavelengths exceeding 720 nm fall under the infrared category,...
8.3K
Vision01:24

Vision

58.9K
Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
58.9K
Convolution Properties II01:17

Convolution Properties II

483
The important convolution properties include width, area, differentiation, and integration properties.
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
The area property asserts that the area under the...
483

You might also read

Related Articles

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

Sort by
Same author

Additive-Free Contact-Electro-Catalysis/Vacuum Ultraviolet System for Rapid Mitigation of Antimicrobial-Resistance-Associated Contaminants in Water.

Research (Washington, D.C.)·2026
Same author

Compositional Analysis of Polymeric Proanthocyanidins from <i>Vitis amurensis</i> Rupr. (Vitaceae) Seeds After Catechin-Assisted Sulfitolytic Cleavage.

Foods (Basel, Switzerland)·2026
Same author

Identification of a saddle point (SP) for safe sacral segment channel planning via data analysis and rapid physical prototyping.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society·2026
Same author

Interfacial Covalent Bonds Between Fe-MoS<sub>2</sub> Quantum Dots and CoFe-MOF Triggering the Strain Effect for Efficient Overall Water Splitting.

Small (Weinheim an der Bergstrasse, Germany)·2026
Same author

Effect of Acupuncture for Diminished Ovarian Reserve: A Randomized Sham-Controlled Trial.

International journal of women's health·2026
Same author

Superhydrophilic Ni(OH)<sub>2</sub>/materials of institute lavoisier-100 (Fe) integrated with hydrogel to construct gradient hierarchical pore channels for efficient quasi-solid water splitting.

Journal of colloid and interface science·2026

Related Experiment Video

Updated: Dec 9, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

875

A Colorization Framework for Monochrome-Color Dual-Lens Systems Using a Deep Convolutional Network.

Xuan Dong, Weixin Li, Xiaoyan Hu

    IEEE Transactions on Visualization and Computer Graphics
    |September 8, 2020
    PubMed
    Summary

    This study introduces a novel deep convolutional network for image colorization, enhancing monochrome images using color references. The framework accurately estimates colorization quality, outperforming existing methods.

    More Related Videos

    Lensless Fluorescent Microscopy on a Chip
    11:23

    Lensless Fluorescent Microscopy on a Chip

    Published on: August 17, 2011

    18.0K

    Related Experiment Videos

    Last Updated: Dec 9, 2025

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    875
    Lensless Fluorescent Microscopy on a Chip
    11:23

    Lensless Fluorescent Microscopy on a Chip

    Published on: August 17, 2011

    18.0K

    Area of Science:

    • Computer Vision
    • Image Processing
    • Deep Learning

    Background:

    • Monochrome cameras offer higher image quality than color cameras in dual-lens systems.
    • Colorizing monochrome images using reference color images is a key technique for high-quality color image generation.
    • Assessing the quality of colorization is crucial due to potential failures.

    Purpose of the Study:

    • To develop a robust deep convolutional network (CNN) framework for accurate image colorization and quality estimation.
    • To improve the utilization of reference color information for enhanced colorization results.
    • To introduce a novel method for estimating the quality of generated color images.

    Main Methods:

    • A deep CNN framework incorporating attention mechanisms, 3-D regularization, and color correction was developed for image colorization.
    • A novel colorization quality estimation module was proposed, leveraging the symmetry property of colorization by re-applying the CNN.
    • The CNN was used to re-colorize a grayscale version of the reference image, using the initial colorization as input, to estimate quality.

    Main Results:

    • The proposed method significantly outperforms state-of-the-art image colorization techniques.
    • The colorization quality estimation module accurately assesses the quality of the generated color images.
    • The framework effectively utilizes deep feature representations and attention for superior colorization.

    Conclusions:

    • The developed deep convolutional network framework provides a significant advancement in image colorization and quality estimation.
    • The novel quality estimation approach offers reliable assessment of colorization accuracy.
    • This method offers a promising solution for generating high-quality color images from monochrome sources.