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 Experiment Videos

A translation- and scale-invariant adaptive wavelet transform.

H Xiong1, T Zhang, Y S Moon

  • 1State Key Laboratory for Image Processing and Intelligence Control, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China. hlxiong@cse.cuhk.edu.hk

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 12, 2008
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

[Efficacy of endoscopic surgery versus microscopic surgery in the treatment of congenital ossicular malformations: a meta-analysis].

Zhonghua yi xue za zhi·2026
Same author

[Progress on the diagnosis and treatment of juvenile idiopathic inflammatory myopathies].

Zhonghua er ke za zhi = Chinese journal of pediatrics·2026
Same author

[Clinical characteristics and prognosis of basal ganglia infarction following minor trauma with basal ganglia calcification in children].

Zhonghua yi xue za zhi·2025
Same author

[Advances in CRISPR-Cas9 genome editing for the treatment of muscular dystrophies].

Zhonghua er ke za zhi = Chinese journal of pediatrics·2025
Same author

[Analysis of etiology and short-term prognosis of childhood arterial ischemic stroke based on the COIST classification].

Zhonghua yi xue za zhi·2025
Same author

[Efficacy and safety of rituximab in the treatment of pediatric myasthenia gravis].

Zhonghua er ke za zhi = Chinese journal of pediatrics·2024
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
Same journal

Location Matters: Frequency-Spatial Dual Space Adaptation for Cross-Domain Few-Shot Segmentation.

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

This study introduces adaptive wavelet invariant moments (AWIM) to solve translation and scale invariance issues in discrete wavelet transform (DWT). The novel method ensures AWIM are invariant to shifts and scaling, enabling effective texture identification.

Area of Science:

  • Signal Processing
  • Image Analysis
  • Wavelet Theory

Background:

  • The discrete wavelet transform (DWT) faces challenges with translation and scale invariance.
  • Existing methods often struggle to maintain feature consistency under geometric transformations.

Purpose of the Study:

  • To develop a novel approach for achieving translation- and scale-invariant discrete wavelet transform coefficients.
  • To introduce adaptive wavelet invariant moments (AWIM) for robust signal and image analysis.
  • To apply the new method for scale-invariant texture identification.

Main Methods:

  • Utilizing a signal-dependent filter based on the signal's first two moments and an orthonormal wavelet's scale function.
  • Adaptively renormalizing the signal before applying conventional DWT decomposition.

Related Experiment Videos

  • Defining a new textural feature derived from the adaptive wavelet decomposition.

    • Main Results:

    • The proposed adaptive wavelet decomposition yields coefficients (AWIM) that are invariant to translation and scale.
    • The newly defined textural feature demonstrates stability under shifts and scaling.
    • The method proves efficient for scale-invariant texture identification tasks.

    Conclusions:

    • The adaptive wavelet invariant moments (AWIM) effectively address the translation- and scale-invariant problem in DWT.
    • The developed approach provides a robust framework for scale-invariant texture analysis.
    • This method offers a significant advancement in signal processing and image analysis applications.