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

Downsampling01:20

Downsampling

When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
Difference from Background: Limit of Detection01:05

Difference from Background: Limit of Detection

The limit of detection (LOD) is the smallest amount of analyte that can be distinguished from the background noise. The LOD value corresponds to the concentration at which the analyte signal is three times larger than the standard deviation of the blank signal. Below this value, the analyte signal cannot be differentiated from the background noise. It is calculated by dividing the calibration slope by 3 times the standard deviation of the blank signals.
The LOD indicates the presence or absence...
¹³C NMR: ¹H–¹³C Decoupling01:04

¹³C NMR: ¹H–¹³C Decoupling

The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
Phase Contrast and Differential Interference Contrast Microscopy01:26

Phase Contrast and Differential Interference Contrast Microscopy

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...
Deconvolution01:20

Deconvolution

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...
Upsampling01:22

Upsampling

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...

You might also read

Related Articles

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

Sort by
Same journal

Marginal-Aware Framework for 3D Shape Segmentation: Resolving Boundary-Internal Face Imbalance.

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

Semantic Composition via Optimal Transport for Composed Image Retrieval.

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

MultiTaskVIF: Segmentation-oriented visible and infrared image fusion via multi-task learning.

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

DTEA: Degradation-Aware Taylor Expansion Approximation Network for Pansharpening.

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

Noisy Tensor Completion for Sparse-Aperture Microwave Imaging in Distributed MIMO Radar Networks.

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

CGGS: Consistency-Augmented Geometric Gaussian Splatting for Ego-centric 3D Scene Generation.

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

Related Experiment Video

Updated: Jul 20, 2026

Troubleshooting and Quality Assurance in Hyperpolarized Xenon Magnetic Resonance Imaging: Tools for High-Quality Image Acquisition
09:55

Troubleshooting and Quality Assurance in Hyperpolarized Xenon Magnetic Resonance Imaging: Tools for High-Quality Image Acquisition

Published on: January 5, 2024

CCD noise removal in digital images.

Hilda Faraji1, W James MacLean

  • 1Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON M5S 3G4, Canada. hilda@eecg.toronto.edu

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|September 5, 2006
PubMed
Summary

This study introduces a new denoising method to fix images affected by CCD noise. Operating in light space proved more efficient for image restoration, simplifying filter design and improving results.

Related Experiment Videos

Last Updated: Jul 20, 2026

Troubleshooting and Quality Assurance in Hyperpolarized Xenon Magnetic Resonance Imaging: Tools for High-Quality Image Acquisition
09:55

Troubleshooting and Quality Assurance in Hyperpolarized Xenon Magnetic Resonance Imaging: Tools for High-Quality Image Acquisition

Published on: January 5, 2024

Area of Science:

  • Image processing
  • Computational imaging
  • Digital signal processing

Background:

  • Charge-Coupled Device (CCD) noise degrades image quality.
  • CCD noise models are complex due to camera nonlinearities.
  • Restoring images requires accounting for noise characteristics.

Purpose of the Study:

  • To propose an effective denoising scheme for CCD noise.
  • To develop adaptive restoration techniques in different image spaces.
  • To compare the efficiency of light space vs. image space denoising.

Main Methods:

  • Developed a CCD noise model in incident light space.
  • Created two adaptive restoration techniques: one in light space, one in image space.
  • Both methods utilize multiple adaptive filters and output merging.

Main Results:

  • Light space denoising demonstrated higher efficiency.
  • Simpler filter implementation is achievable in light space.
  • Effective restoration was shown on real images with synthetic and real noise.

Conclusions:

  • Denoising in light space is more efficient for CCD noise.
  • Adaptive filtering in light space simplifies implementation.
  • The proposed scheme effectively restores noisy images.