New family of orthonormal transforms with time localizability based on DFT

Kook-Yeon Kwak; Richard A. Haddad

doi:10.1117/12.185875

16 September 1994 New family of orthonormal transforms with time localizability based on DFT

Kook-Yeon Kwak, Richard A. Haddad

Proceedings Volume 2308, Visual Communications and Image Processing '94; (1994) https://doi.org/10.1117/12.185875
Event: Visual Communications and Image Processing '94, 1994, Chicago, IL, United States

Abstract

The library of orthonormal bases includes Short Time Fourier Transform and Wavelet Transform bases. The widely-used DFT lacks flexibility in dealing with signals possessing a time-varying spectrum. Such signals require a variable time-frequency-localizability feature for adequate resolution. In this paper, we introduce new orthonormal transforms which are constructed from the DFT yet have variable time-frequency-localizability feature and fast computing capability. We create a framework for constructing Time Localization Linear Transform (TLLT) upon the concept that time localizability can be recovered by inverse transform of selected partial collection of forward transform coefficients. By coding the coefficients of TLLT, we can combine the adaptability of Vector Quantization with the speed of linear transform.

Citation Download Citation

Kook-Yeon Kwak and Richard A. Haddad "New family of orthonormal transforms with time localizability based on DFT", Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); https://doi.org/10.1117/12.185875

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available