Jove
Visualize
Contact Us

Related Concept Videos

Inverse z-Transform by Partial Fraction Expansion01:20

Inverse z-Transform by Partial Fraction Expansion

The inverse z-transform is a crucial technique for converting a function from its z-domain representation back to the time domain. One effective method for finding the inverse z-transform is the Partial Fraction Method, which involves decomposing a function into simpler fractions with distinct coefficients. These fractions correspond to known z-transform pairs, facilitating the inverse transformation process.
To begin the process, the poles of the function are identified and the function is...
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...
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

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 sampling...
Region of Convergence of Laplace Tarnsform01:20

Region of Convergence of Laplace Tarnsform

The Region of Convergence (ROC) is a fundamental concept in signal processing and system analysis, particularly associated with the Laplace transform. The ROC represents an area in the complex plane where the Laplace transform of a given signal converges, determining the transform's applicability and utility.
Consider a decaying exponential signal that begins at a specific time. When deriving its Laplace transform, the time-domain variable is replaced with a complex variable. This substitution...
Region of Convergence01:17

Region of Convergence

The z-transform is a powerful mathematical tool used in the analysis of discrete-time signals and systems. It is a crucial tool in the analysis of discrete-time systems, but its convergence is limited to specific values of the complex variable z. This range of values, known as the Region of Convergence (ROC), is fundamental in determining the behavior and stability of a system or signal. The ROC defines the region in the complex plane where the z-transform converges, which can take various...
Wald-Wolfowitz Runs Test I01:17

Wald-Wolfowitz Runs Test I

The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
The test works...

You might also read

Related Articles

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

Sort by
Same author

Machine learning reveals country-specific drivers of global cancer outcomes.

Annals of oncology : official journal of the European Society for Medical Oncology·2026
Same author

International guidelines for the delineation of the postoperative clinical target volumes (CTV) for parotid and submandibular gland cancers.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology·2025
Same author

"Primer shot" fractionation with an early treatment break is theoretically superior to consecutive weekday fractionation schemes for early-stage non-small cell lung cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology·2023
Same author

Increased salivary syndecan-1 level is associated with salivary gland function and inflammation in patients with Sjögren's syndrome.

Scandinavian journal of rheumatology·2021
Same author

Incidence and Distribution of the Pathogens Causing Central Nervous System Infections at the University Hospital of Korea.

Clinical laboratory·2021
Same author

Incidence and Distribution of Respiratory Microorganisms Causing Acute Respiratory Infections at the University Hospital of Korea.

Clinical laboratory·2020
Same journal

Through the Looking Glass: A Dual Perspective on Weakly-Supervised Few-Shot Segmentation.

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

Mask-guided Asymmetric Contrastive and Semantic Alignment for Unsupervised Person Re-Identification.

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

Hyperbolic Cycle Alignment for Infrared-Visible Image Fusion.

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

Learning Gaze Synthesizer via 3D-eye Controlled Diffusion and Cross-domain Feature Alignment.

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

Underlying Semantic Diffusion for Effective and Efficient In-Context Learning.

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

DiffRES: Unleashing Text-to-Image Diffusion Models for Generative Referring Expression Segmentation without Information Leakage.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
See all related articles
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: Jul 7, 2026

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
08:42

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Published on: September 3, 2021

Wavelet methods for inverting the Radon transform with noisy data.

N Y Lee1, B J Lucier

  • 1Department of Control and Instrumentation Engineering, Kangwon National University, Chunchon 200-701, Korea. nylee@cc.kangwon.ac.kr

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 6, 2008
PubMed
Summary
This summary is machine-generated.

Noise in Radon data is amplified by the inverse Radon transform. Wavelet-vaguelette decomposition (WVD) with wavelet shrinkage offers a solution, improving image reconstruction from noisy data.

More Related Videos

Applying X-ray Imaging Crystal Spectroscopy for Use as a High Temperature Plasma Diagnostic
06:46

Applying X-ray Imaging Crystal Spectroscopy for Use as a High Temperature Plasma Diagnostic

Published on: August 25, 2016

Related Experiment Videos

Last Updated: Jul 7, 2026

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method
08:42

Measurement of the Directional Information Flow in fNIRS-Hyperscanning Data using the Partial Wavelet Transform Coherence Method

Published on: September 3, 2021

Applying X-ray Imaging Crystal Spectroscopy for Use as a High Temperature Plasma Diagnostic
06:46

Applying X-ray Imaging Crystal Spectroscopy for Use as a High Temperature Plasma Diagnostic

Published on: August 25, 2016

Area of Science:

  • Image reconstruction
  • Signal processing
  • Applied mathematics

Background:

  • The Radon transform amplifies noise during inverse transformation, complicating image reconstruction.
  • Wavelet-vaguelette decomposition (WVD) with wavelet shrinkage is a known method to mitigate this noise amplification.
  • Existing methods require refinement for optimal performance in noisy inverse problems.

Purpose of the Study:

  • To extend existing results on wavelet shrinkage for inverse problems, specifically for the Radon transform.
  • To introduce a new condition for wavelets enabling WVD.
  • To develop an improved method for image reconstruction from noisy Radon data.

Main Methods:

  • Introduced a new sufficient condition for wavelets to generate WVD.
  • Derived a variant of Donoho's method as a minimizer of a variational problem using Besov norms.
  • Provided a new proof for the rate of convergence of wavelet shrinkage.
  • Estimated optimal shrinkage parameters based on Besov-space properties of the image.

Main Results:

  • A new sufficient condition for wavelets in WVD was established.
  • The proposed method, minimizing a Besov norm, offers a robust approach to inverse problems.
  • A refined estimation of shrinkage parameters was achieved, improving image recovery from noise.
  • Computational results demonstrated superior performance compared to existing methods.

Conclusions:

  • The enhanced WVD method with optimized shrinkage parameters significantly improves tomographic reconstruction.
  • The approach provides a more accurate and robust solution for inverse problems involving noisy data.
  • This work advances the application of wavelet-based methods in image processing and scientific computing.