Blind Image Blur Identification in Cepstrum Domain

The type and extent of blur affect image quality and therefore its evaluation. This paper presents an accurate method for blur identification and parameter estimation from one image without a priori knowledge. The key idea of the proposed method is to perform Fourier transform of logarithm spectrum...

Full description

Saved in:
Bibliographic Details
Published in2007 16th International Conference on Computer Communications and Networks pp. 1166 - 1171
Main Authors Shiqian Wu, Zhongkang Lu, Ee Ping Ong, Weisi Lin
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2007
Subjects
Additive noise
Autoregressive processes
blur identificationt
blur pattern
Cepstrum
Convolution
Degradation
Fourier transforms
Image processing
Image quality
Noise robustness
Parameter estimation
Online AccessGet full text
ISBN9781424412501
1424412501
ISSN1095-2055
DOI10.1109/ICCCN.2007.4317977

Cover

More Information
Summary:The type and extent of blur affect image quality and therefore its evaluation. This paper presents an accurate method for blur identification and parameter estimation from one image without a priori knowledge. The key idea of the proposed method is to perform Fourier transform of logarithm spectrum to detect the periodic blur pattern in cepstrum domain instead of spectral nulls. Accordingly, the estimation of blur parameters is more accurate and robust to noise. The experimental results validate the accuracy of the proposed method.
ISBN:9781424412501
1424412501
ISSN:1095-2055
DOI:10.1109/ICCCN.2007.4317977