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

Deconvolution01:20

Deconvolution

669
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...
669
Convolution: Math, Graphics, and Discrete Signals01:24

Convolution: Math, Graphics, and Discrete Signals

1.1K
In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...
1.1K
Convolution Properties II01:17

Convolution Properties II

641
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...
641
Convolution Properties I01:20

Convolution Properties I

656
Convolution computations can be simplified by utilizing their inherent properties.
The commutative property reveals that the input and the impulse response of an LTI (Linear Time-Invariant) system can be interchanged without affecting the output:
656
Phase Contrast and Differential Interference Contrast Microscopy01:26

Phase Contrast and Differential Interference Contrast Microscopy

15.0K
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...
15.0K
Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

12.1K
Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
12.1K

You might also read

Related Articles

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

Sort by
Same author

Few-shot trained single-lens diffractive neural network for all-optical image denoising.

Optics express·2025
Same author

Preliminary evaluation of a predictive controller for a rotary blood pump based on pulmonary oxygen gas exchange.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine·2019
Same author

A Destructive New Disease of Citrus in China Caused by Cryptosporiopsis citricarpa sp. nov.

Plant disease·2019
Same author

Effects of membrane reference state on shape memory of a red blood cell.

Computer methods in biomechanics and biomedical engineering·2019
Same author

Ultrafast Photovoltaic-Type Deep Ultraviolet Photodetectors Using Hybrid Zero-/Two-Dimensional Heterojunctions.

ACS applied materials & interfaces·2019
Same author

Phenolic profile and antioxidant properties of sand rice (Agriophyllum squarrosum) as affected by cooking and in vitro digestion.

Journal of the science of food and agriculture·2019

Related Experiment Video

Updated: Mar 19, 2026

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
09:43

Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

Published on: March 20, 2017

10.4K

Inverse design of incoherent multiple image differentiation with spatial multiplexing optical convolution.

Feng Huang, Guofeng Zhu, Hewen Wang

    Applied Optics
    |March 17, 2026
    PubMed
    Summary
    This summary is machine-generated.

    Researchers developed a novel incoherent optical edge detection method using spatial multiplexing optical convolution. This technique enables intelligent design and integrates multifunctional imaging processors into compact, low-consumption optical systems.

    More Related Videos

    Whole-cell Super-Resolution Imaging via DNA-PAINT on a Spinning Disk Confocal with Optical Photon Reassignment
    07:12

    Whole-cell Super-Resolution Imaging via DNA-PAINT on a Spinning Disk Confocal with Optical Photon Reassignment

    Published on: January 6, 2026

    594
    Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
    06:25

    Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

    Published on: February 12, 2014

    8.9K

    Related Experiment Videos

    Last Updated: Mar 19, 2026

    Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
    09:43

    Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

    Published on: March 20, 2017

    10.4K
    Whole-cell Super-Resolution Imaging via DNA-PAINT on a Spinning Disk Confocal with Optical Photon Reassignment
    07:12

    Whole-cell Super-Resolution Imaging via DNA-PAINT on a Spinning Disk Confocal with Optical Photon Reassignment

    Published on: January 6, 2026

    594
    Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
    06:25

    Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

    Published on: February 12, 2014

    8.9K

    Area of Science:

    • Optics
    • Machine Vision
    • Image Processing

    Background:

    • Incoherent optical imaging systems face challenges in direct edge detection due to linearity with light intensity.
    • Designing bipolar point spread functions (PSFs) for edge detection in incoherent systems is difficult.

    Purpose of the Study:

    • To propose and demonstrate a method for incoherent multiple image differentiation using spatial multiplexing optical convolution.
    • To enable intelligent design and integration of multifunctional optical imaging processors.

    Main Methods:

    • Utilized a differentiable light field model for phase mask optimization via inverse design.
    • Designed a phase mask to implement spatial tiling non-negative optical convolutional kernels.
    • Achieved spatial differentiation (x and y) and isotropic edge detection through digital subtraction.

    Main Results:

    • Experimentally demonstrated incoherent multiple image differentiation.
    • Successfully implemented optical convolution for edge detection tasks.
    • Showcased simultaneous spatial differentiation and isotropic edge detection.

    Conclusions:

    • The proposed method offers intelligent design, reduced device complexity, and increased scalability for optical edge detection.
    • A single optimized phase mask functions as a versatile convolution processor, enhancing optical system integration.
    • This scheme provides a flexible approach for compact, low-consumption multifunctional imaging processors under incoherent illumination.