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

An estimation algorithm for 2-D polynomial phase signals.

B Friedlander1, J M Francos

  • 1Dept. of Electr. and Comput. Eng., California Univ., Davis, CA.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|January 1, 1996
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

Parametric estimation of the orientation of textured planar surfaces.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2008
Same author

Intercostal video-assisted mediastinal surgery through an intercostal window (IVAMS): a simpler approach to perform mediastinal parathyroidectomy.

Surgery·2007
Same author

Are African-American nuclear workers at lower mortality risk than Caucasians?

Journal of occupational and environmental medicine·2001
Same author

Adaptive restoration of textured images with mixed spectra.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·1996
Same author

Texture coding using a Wold decomposition model.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·1996
Same author

Maximum likelihood parameter estimation of textures using a Wold-decomposition based model.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·1995
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 a new method for analyzing nonhomogeneous 2-D signals using a polynomial-phase model. The developed algorithm efficiently estimates model parameters, improving signal analysis techniques.

Area of Science:

  • Signal Processing
  • Polynomial Phase Signal Analysis

Background:

  • Nonhomogeneous 2-D signals are common in various applications.
  • Existing models may not fully capture the complexity of these signals.
  • Constant modulus polynomial-phase models offer a promising representation.

Purpose of the Study:

  • To develop a computationally efficient algorithm for parameter estimation of nonhomogeneous 2-D signals.
  • To introduce a novel 2-D phase differencing operator for this purpose.

Main Methods:

  • Development of a novel 2-D phase differencing operator.
  • Application of the operator to a constant modulus polynomial-phase model.
  • Creation of an efficient parameter estimation algorithm.

Main Results:

Related Experiment Videos

  • The proposed algorithm effectively estimates parameters for the specified signal model.
  • The 2-D phase differencing operator facilitates computationally efficient analysis.
  • Algorithm performance is demonstrated through an illustrative example.

Conclusions:

  • The novel 2-D phase differencing operator enables efficient parameter estimation for nonhomogeneous 2-D signals.
  • The developed algorithm provides a valuable tool for analyzing signals represented by constant modulus polynomial-phase models.