Identification of blur support size in blind image restoration with moderate/intense noise

Chunxiao Zhang; Yan Zhao; Dong Xu

doi:10.1117/12.807362

13 October 2008 Identification of blur support size in blind image restoration with moderate/intense noise

Chunxiao Zhang, Yan Zhao, Dong Xu

Proceedings Volume 7129, Seventh International Symposium on Instrumentation and Control Technology: Optoelectronic Technology and Instruments, Control Theory and Automation, and Space Exploration; 71290S (2008) https://doi.org/10.1117/12.807362
Event: Seventh International Symposium on Instrumentation and Control Technology, 2008, Beijing, China

Abstract

This paper makes improvements on the algorithm of identifying blur support size proposed by Li Chen in blind image restoration to accommodate to the moderate/intense noise circumstance. The prior method mainly constructs a whiten filter referring to the image characteristics based on ARMA (Autoregressive Moving Average) model, and calculates the correlation of whiten filtered image with different shifts, thus gets the estimated blur size equal to the shifts at the minimum of correlation. However, this method is difficult to accurately identify blur size even with moderate additive noise. Some procedures are taken before calculating the correlation to ameliorate the estimation accuracy, including regarding edge neighborhoods as valid regions for calculating correlation in the whiten filtered image and implementing filtering to further reduce noise interference. Experimental results represent that the correlation attains its minimum when the shift distance meets certain relationship with actual blur size, thus show the improvements are valid for the case of moderate/intense contamination.

Citation Download Citation

Chunxiao Zhang, Yan Zhao, and Dong Xu "Identification of blur support size in blind image restoration with moderate/intense noise", Proc. SPIE 7129, Seventh International Symposium on Instrumentation and Control Technology: Optoelectronic Technology and Instruments, Control Theory and Automation, and Space Exploration, 71290S (13 October 2008); https://doi.org/10.1117/12.807362

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image filtering

Autoregressive models

Image restoration

Deconvolution

Image processing

Lithium

Contamination

Show All Keywords

Keywords/Phrases

Search In:

Publication Years