Maximum entropy Kalman filter for image reconstruction and compression

Nastooh Avesta; Tyseer Aboulnasr

doi:10.1117/1.1789135

1 October 2004 Maximum entropy Kalman filter for image reconstruction and compression

Nastooh Avesta, Tyseer Aboulnasr

Author Affiliations +

Journal of Electronic Imaging, Vol. 13, Issue 4, (October 2004). https://doi.org/10.1117/1.1789135

Abstract

Adaptive processes often attempt to minimize the mean square error (MSE) to filter a partially observed digital signal. While mathematically tractable, the MSE criterion often causes oversmoothing of the filtered signal. In this paper, we propose using maximum entropy (ME) as the optimization criterion to avoid the oversmoothing of signals. This criterion is motivated by the fact that ME methods make no assumptions regarding the unobserved data, aside from explicitly stated ones. The maximum entropy Kalman filter presented in this paper employs ME as its optimization criterion to explicitly identify the appropriate parameters of the standard Kalman filter, for the purpose of image compression and reconstruction.

©(2004) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Nastooh Avesta and Tyseer Aboulnasr "Maximum entropy Kalman filter for image reconstruction and compression," Journal of Electronic Imaging 13(4), (1 October 2004). https://doi.org/10.1117/1.1789135

Published: 1 October 2004

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