By Topic

AM-FM Image Analysis Using the Hilbert Huang Transform

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Peter C. Tay ; Dept. of Engineering and Technology, Western Carolina University, Cullowhee, NC 28723,

This paper explores the incorporation of the two dimensional (2D) empirical mode decomposition, which is used in the Hilbert-Huang Transform, into a meaningful AM-FM image model framework. A virtue of the empirical mode decomposition is that it decomposes a non-stationary signal into stationary intrinsic mode functions and a residue signal. The empirical mode decomposition attempts to produce intrinsic mode functions that are stationary and a residue function that is dominated by piecewise monotonic functions. When considering image pixel values as produced from a non-stationary process, the 2D empirical mode decomposition shows promise as a precursor step in determining AM-FM components where stationarity is needed.

Published in:

Image Analysis and Interpretation, 2008. SSIAI 2008. IEEE Southwest Symposium on

Date of Conference:

24-26 March 2008