Jove
Visualize
Contact Us

Related Concept Videos

Raman Spectroscopy Instrumentation: Overview01:26

Raman Spectroscopy Instrumentation: Overview

569
A conventional Raman spectrophotometer includes a laser source, a sample holding system, a wavelength selector, and a detector.
The monochromatic laser source, typically using visible or near-infrared radiation, generates a highly focused beam of light. This light interacts with the molecules of the sample, scattering some of the light. Liquid and gaseous samples are usually tested in ordinary glass capillaries, while solids can be analyzed as powders packed in capillaries or as potassium...
569
Raman Spectroscopy: Overview01:20

Raman Spectroscopy: Overview

702
The underlying principle of Raman spectroscopy is based on the interaction between light and matter, specifically molecules' inelastic scattering of photons. When a monochromatic beam of light, typically from a laser source, interacts with a sample, most scattered light has the same frequency as the incident light. This is known as Rayleigh scattering.
However, a small fraction of the scattered light exhibits a frequency shift due to the exchange of energy between the incident photons and...
702
Classification of Signals01:30

Classification of Signals

987
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
987
Classification of Titrimetric Analysis Based on Reaction Types01:01

Classification of Titrimetric Analysis Based on Reaction Types

883
Titrimetric analysis in solution chemistry involves measuring the volume of solutions and is often called volumetric analysis. The standard solution of known concentration in the burette is called the titrant, whereas the solution of unknown concentration in the flask is called the analyte, or titrand. Titrimetric analyses can be classified into four types based on the reactions between the titrant and analyte.
Titrations between an acid and a base lead to neutralization reactions that form...
883

You might also read

Related Articles

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

Sort by
Same author

Temporal structural coherence anisotropy.

Optics letters·2026
Same author

Polarization intrinsic coherence Poincaré sphere.

Journal of the Optical Society of America. A, Optics, image science, and vision·2026
Same author

Polarization coherence frustration generated with propagation.

Optics letters·2025
Same author

Photo-detection correlation degrees of a two-photon source.

Optics letters·2024
Same author

Extended-depth of field random illumination microscopy, EDF-RIM, provides super-resolved projective imaging.

Light, science & applications·2024
Same author

Optimal trade-off filters for compressed Raman classification and spectrum reconstruction.

Journal of the Optical Society of America. A, Optics, image science, and vision·2023
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 Experiment Video

Updated: Oct 2, 2025

Ultrafast Time-resolved Near-IR Stimulated Raman Measurements of Functional π-conjugate Systems
09:57

Ultrafast Time-resolved Near-IR Stimulated Raman Measurements of Functional π-conjugate Systems

Published on: February 10, 2020

7.3K

Compressed Raman method combining classification and estimation of spectra with optimized binary filters.

Timothée Justel, Frédéric Galland, Antoine Roueff

    Optics Letters
    |March 1, 2022
    PubMed
    Summary

    This study introduces optimized binary filters for compressed Raman spectroscopy, enabling rapid chemical classification pixel-by-pixel while allowing full spectrum reconstruction. The method enhances robustness against intensity variations.

    More Related Videos

    A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells
    10:37

    A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

    Published on: August 22, 2025

    457
    Resolving Water, Proteins, and Lipids from In Vivo Confocal Raman Spectra of Stratum Corneum through a Chemometric Approach
    09:32

    Resolving Water, Proteins, and Lipids from In Vivo Confocal Raman Spectra of Stratum Corneum through a Chemometric Approach

    Published on: September 26, 2019

    7.3K

    Related Experiment Videos

    Last Updated: Oct 2, 2025

    Ultrafast Time-resolved Near-IR Stimulated Raman Measurements of Functional π-conjugate Systems
    09:57

    Ultrafast Time-resolved Near-IR Stimulated Raman Measurements of Functional π-conjugate Systems

    Published on: February 10, 2020

    7.3K
    A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells
    10:37

    A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

    Published on: August 22, 2025

    457
    Resolving Water, Proteins, and Lipids from In Vivo Confocal Raman Spectra of Stratum Corneum through a Chemometric Approach
    09:32

    Resolving Water, Proteins, and Lipids from In Vivo Confocal Raman Spectra of Stratum Corneum through a Chemometric Approach

    Published on: September 26, 2019

    7.3K

    Area of Science:

    • Spectroscopy
    • Chemical Analysis
    • Optical Engineering

    Background:

    • Compressed Raman spectroscopy utilizes binary filters for efficient chemical species classification with minimal measurements.
    • Existing methods face challenges with pixel-to-pixel intensity variations, impacting classification accuracy.
    • Full spectrum reconstruction capability is often compromised in compressed sensing approaches.

    Purpose of the Study:

    • To develop an optimized methodology for binary filter design in compressed Raman spectroscopy.
    • To enable pixel-by-pixel chemical classification using few parallel measurements.
    • To maintain the ability to reconstruct full spectra from combined pixel measurements.

    Main Methods:

    • Proposed a binary filter optimization methodology adaptable for each pixel.
    • Employed a generalized Bhattacharyya bound for optimized filter performance.
    • Utilized the Cramér-Rao bound to enhance filter design and robustness.

    Main Results:

    • Achieved pixel-by-pixel classification with a limited number of parallel measurements.
    • Demonstrated robustness to intensity variations across different pixels.
    • Successfully retained the capability for full spectrum reconstruction by combining pixel data.

    Conclusions:

    • The proposed filter optimization methodology significantly enhances compressed Raman spectroscopy.
    • This approach offers a robust and efficient solution for chemical species identification.
    • The technique balances rapid classification with the preservation of detailed spectral information.