LMMSE restoration of blurred and noisy image sequences

Mehmet K. Ozkan; M. Ibrahim Sezan; A. Tanju Erdem; A. Murat Tekalp

doi:10.1117/12.50330

1 November 1991 LMMSE restoration of blurred and noisy image sequences

Mehmet K. Ozkan, M. Ibrahim Sezan, A. Tanju Erdem, A. Murat Tekalp

Proceedings Volume 1606, Visual Communications and Image Processing '91: Image Processing; (1991) https://doi.org/10.1117/12.50330
Event: Visual Communications, '91, 1991, Boston, MA, United States

Abstract

In this paper we propose a computationally efficient multiframe Wiener filtering algorithm, called the cross-correlated multiframe (CCMF) Wiener filtering, for restoring image sequences that are degraded by both blur and noise. The CCMF approach accounts for both intraframe (spatial) and interframe (temporal) correlations by directly utilizing power and cross-power spectra of the frames. We propose an efficient implementation of the CCMF filter which requires the inversion of only N X N matrices, where N is the number of frames used in the restoration. Furthermore, is it shown that if the auto and cross-power spectra are estimated based on a three-dimensional (3-D) multiframe autoregressive (AR) model, no matrix inversion is required. We present restoration results using the proposed approach, and compare them with those obtained by restoring each frame independently using a single-frame Wiener filter. In addition, we provide the results of an extensive study on the performance and robustness of the proposed algorithm in the case of varying blur, noise, and power and cross- power spectra estimation methods using different image sequences.

Citation Download Citation

Mehmet K. Ozkan, M. Ibrahim Sezan, A. Tanju Erdem, and A. Murat Tekalp "LMMSE restoration of blurred and noisy image sequences", Proc. SPIE 1606, Visual Communications and Image Processing '91: Image Processing, (1 November 1991); https://doi.org/10.1117/12.50330

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