By Topic

An Empirical Identification Method of Gaussian Blur Parameter for Image Deblurring

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)
Fen Chen ; Coll. of Autom., Univ. of Electron. Sci. & Technol. of China, Chengdu ; Jianglin Ma

In this paper, we propose an empirical identification method of the Gaussian blur parameter for image deblurring. The parameter estimate is chosen from a collection of candidate parameters. The blurred image is restored by these candidate parameters under the assumption that the candidate is equal to the true value. The estimate is selected to be at the maximum point of the differential coefficients of restored image Laplacian L1 norm curve. Experimental results are presented to demonstrate the performance of the proposed method.

Published in:

Signal Processing, IEEE Transactions on  (Volume:57 ,  Issue: 7 )