Cart (Loading....) | Create Account
Close category search window
 

Partial eigenvalue decomposition of large images using spatial temporal adaptive method

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
$31 $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

2 Author(s)
Murase, W. ; NTT Basic Res. Labs., Kanagawa, Japan ; Lindenbaum, M.

Finding eigenvectors of a sequence of real images has usually been considered to require too much computation to be practical. Our spatial temporal adaptive (STA) method reduces the computational complexity of the approximate partial eigenvalue decomposition based on image encoding. Spatial temporal encoding is used to reduce storage and computation, and then, singular value decomposition (SVD) is applied. After the adaptive discrete cosine transform (DCT) encoding, blocks that are similar in consecutive images are consolidated. The computational economy of our method was verified by tests on different large sets of images. The results show that this method is 6 to 10 times faster than the traditional SVD method for several kinds of real images. The economy of this algorithm increases with increasing correlation within the image and with increasing correlation between consecutive images within a set. This algorithm is useful for pattern recognition using eigenvectors, which is a research field that has been active recently

Published in:

Image Processing, IEEE Transactions on  (Volume:4 ,  Issue: 5 )

Date of Publication:

May 1995

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.