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

Tagging and Fusion Proteins01:24

Tagging and Fusion Proteins

6.6K
Proteins are involved in several cellular processes and biochemical reactions. Analyzing a specific protein of interest requires it to be isolated from the other proteins in the cell. This is achieved by overexpressing the specific gene in a suitable host to produce large quantities of the target protein. A tag or label is recombined with the gene to produce a fusion protein containing the target protein and the tag. The tags on these fusion proteins can then be used for easy detection and...
6.6K
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

151
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
151
Deconvolution01:20

Deconvolution

116
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...
116
Source Transformation01:15

Source Transformation

2.8K
Source transformation is a fundamental technique employed in circuit analysis, offering a valuable tool for simplifying complex electrical circuits. This technique involves the replacement of either a voltage source in series with a resistor by a current source in parallel with a resistor, or vice versa. The key concept here is that when the original sources are deactivated (turned off), the equivalent resistance at the circuit's end terminals remains the same.
It is essential to note that...
2.8K
Upsampling01:22

Upsampling

171
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
171
Aliasing01:18

Aliasing

103
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
103

You might also read

Related Articles

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

Sort by
Same author

Error analysis of Cm measurement under the whole-cell patch-clamp recording.

Journal of neuroscience methods·2009
Same author

Understanding the self-assembly of charged nanoparticles at the water/oil interface.

Physical chemistry chemical physics : PCCP·2009
Same author

[Development of new SSR markers from EST of SSH cDNA libraries on rose fragrance].

Yi chuan = Hereditas·2009
Same author

Crocin and geniposide profiles and radical scavenging activity of gardenia fruits (Gardenia jasminoides Ellis) from different cultivars and at the various stages of maturation.

Fitoterapia·2009
Same author

Small-molecule screening using a human primary cell model of HIV latency identifies compounds that reverse latency without cellular activation.

The Journal of clinical investigation·2009
Same author

Berberine lowers blood glucose in type 2 diabetes mellitus patients through increasing insulin receptor expression.

Metabolism: clinical and experimental·2009

Related Experiment Video

Updated: May 14, 2025

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

976

OmniFuse: Composite Degradation-Robust Image Fusion With Language-Driven Semantics.

Hao Zhang, Lei Cao, Xuhui Zuo

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |May 9, 2025
    PubMed
    Summary

    OmniFuse introduces a novel image fusion framework that overcomes composite degradation and enhances user control. This robust method leverages latent diffusion models and language-driven semantics for flexible, high-quality image fusion.

    More Related Videos

    Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development
    13:01

    Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

    Published on: April 10, 2016

    33.8K
    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

    436

    Related Experiment Videos

    Last Updated: May 14, 2025

    Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
    07:13

    Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

    Published on: October 27, 2023

    976
    Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development
    13:01

    Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

    Published on: April 10, 2016

    33.8K
    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

    436

    Area of Science:

    • Computer Vision
    • Artificial Intelligence
    • Image Processing

    Background:

    • Existing image fusion techniques lack robustness against composite degradation.
    • Current methods offer limited flexibility in controlling semantic object focus during fusion.

    Purpose of the Study:

    • To propose OmniFuse, a composite degradation-robust image fusion framework with language-driven semantics.
    • To enhance image fusion flexibility and accuracy through controllable semantic modulation.

    Main Methods:

    • A novel multi-modal information fusion paradigm based on the latent diffusion model (LDM).
    • Integration of information fusion within the LDM's latent space for robust degradation elimination.
    • Development of a language-driven controllable fusion strategy using a language-driven feature fusion module (LFFM).
    • Incorporation of visual enhancement regularization and reverse semantic driving for precise object highlighting and semantic attribute strengthening.

    Main Results:

    • OmniFuse demonstrates superior robustness in eliminating composite degradation during image fusion.
    • The framework achieves significant improvements in fusion flexibility through language-driven control.
    • Extensive experiments validate OmniFuse's superior performance compared to state-of-the-art methods.

    Conclusions:

    • OmniFuse offers an omnipotent solution for image fusion, addressing limitations of existing methods.
    • The proposed framework provides significant advantages in both robustness and user-controlled flexibility.
    • The open-source availability of OmniFuse facilitates further research and application in image fusion.