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

Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

1.8K
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
1.8K
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

699
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...
699
Deconvolution01:20

Deconvolution

548
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...
548
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

9.1K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
9.1K
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

1.4K
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
1.4K
Fischer Projections02:18

Fischer Projections

16.3K
Learning to draw Fischer projections of molecules and understanding their relevance plays a crucial role in the visual depiction of organic molecules. A Fischer projection is a two-dimensional projection on a planar surface to simplify the three-dimensional wedge–dash representation of molecules. This is especially helpful in the case of molecules with multiple chiral centers that can be difficult to draw. Here, all the bonds of interest are represented as horizontal or vertical lines. While...
16.3K

You might also read

Related Articles

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

Sort by
Same author

Hierarchical Color Constancy via Efficient Spectral Feature Extraction.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2025
Same author

IL-32γ Induced Autophagy Through Suppression of MET and mTOR Pathways in Liver Tumor Growth Inhibition.

International journal of molecular sciences·2024
Same author

RefQSR: Reference-Based Quantization for Image Super-Resolution Networks.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2024
Same author

Optimizing the photon ratio of red, green, and blue LEDs for lettuce seedlings: a mixture design approach.

Plant methods·2023
Same author

Deep Dichromatic Model Estimation Under AC Light Sources.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2021
Same author

Ghost-Free Deep High-Dynamic-Range Imaging Using Focus Pixels for Complex Motion Scenes.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2021
Same journal

Style-Aware Contrastive Test-Time Adaptation: A Dual-Cache Model for Robust Vision-Language Alignment.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Semantic Frame Interpolation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Physics-Guided Cross-Modal Decoupling with Test-Time Adaptation for Hyperspectral Image Restoration.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Change-Prior-Guided Unsupervised Change Detection of Heterogeneous Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

AgonicDreamer: Enhancing Multi-View Consistency in Text-to-3D Generation via Rectified Score Distillation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

BiCM-Prompt: Bidirectional Cross-Modal Prompt Tuning for Class-Incremental Learning on Multisource Remote Sensing Images.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
See all related articles

Related Experiment Video

Updated: Jan 19, 2026

Bringing the Visible Universe into Focus with Robo-AO
10:35

Bringing the Visible Universe into Focus with Robo-AO

Published on: February 12, 2013

20.1K

Noise-Robust Iterative Back-Projection.

Jun-Sang Yoo, Jong-Ok Kim

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |September 20, 2019
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel back-projection algorithm for noisy image super-resolution (SR). The method enhances SR images by estimating clean reconstruction error, improving noise robustness over traditional iterative back-projection (IBP).

    More Related Videos

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
    11:34

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

    Published on: December 3, 2013

    16.0K
    Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
    10:44

    Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

    Published on: June 21, 2024

    1.1K

    Related Experiment Videos

    Last Updated: Jan 19, 2026

    Bringing the Visible Universe into Focus with Robo-AO
    10:35

    Bringing the Visible Universe into Focus with Robo-AO

    Published on: February 12, 2013

    20.1K
    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
    11:34

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

    Published on: December 3, 2013

    16.0K
    Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
    10:44

    Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

    Published on: June 21, 2024

    1.1K

    Area of Science:

    • Computer Vision
    • Image Processing
    • Signal Processing

    Background:

    • Noisy image super-resolution (SR) is challenging due to denoising-induced smoothness.
    • Iterative back-projection (IBP) enhances SR images but requires a clean reference, which is unavailable in noisy scenarios.

    Purpose of the Study:

    • To propose a novel back-projection algorithm for noisy image SR.
    • To enhance SR image quality by ensuring consistency between low-resolution (LR) and SR images.
    • To develop a noise-robust method for SR post-processing.

    Main Methods:

    • A new cost function is formulated in the Principal Component Analysis (PCA) transform domain to estimate clean reconstruction error.
    • Region-adaptive combination of noisy and denoised reconstruction errors using texture probability.
    • Incorporation of sparsity constraint based on Laplacian characteristics of reconstruction error.
    • Eigenvector estimation method to minimize noise impact.

    Main Results:

    • The proposed method demonstrates superior noise robustness compared to conventional IBP.
    • Experimental results validate the effectiveness of the PCA domain cost function and eigenvector estimation.
    • The algorithm successfully performs back-projection in a noise-robust manner.

    Conclusions:

    • The novel back-projection algorithm effectively addresses challenges in noisy image SR.
    • The method provides a noise-robust post-processing solution compatible with existing SR techniques.
    • This approach improves SR image quality by mitigating noise while preserving details.