DocumentCode
190977
Title
Parameter estimation for image deblurring
Author
Yongfei Gao ; Zelong Wang ; Jubo Zhu
Author_Institution
Coll. of Sci., Nat. Univ. of Defense Technol., Changsha, China
fYear
2014
fDate
5-8 Aug. 2014
Firstpage
572
Lastpage
577
Abstract
Blurred images usually come from all kinds of imaging equipments, which may provide important prior information about the possible MTF models with unknown parameters. Based on this prior, we aim to estimate their corresponding parameters for image deblurring. From the fractal model of the original distinct image and the image degradation model, we firstly analyze the statistical character of the blurred image; and then we estimate the noise level by the high frequency energy of the blurred image. For the given MTF degradation model, we estimate the fractal parameters and the MTF parameters by Maximum Likelihood Estimation (MLE), which is achieved numerically by alternating optimization scheme.
Keywords
fractals; image denoising; image restoration; maximum likelihood estimation; MLE; MTF degradation model; MTF model parameter estimation; blurred images; distinct image; fractal model parameter estimation; high-frequency energy; image deblurring; image degradation model; imaging equipments; maximum likelihood estimation; noise level estimation; numerical analysis; statistical character analysis; unknown parameters; Degradation; Equations; Estimation; Fractals; Frequency-domain analysis; Mathematical model; Noise; Maximum Likelihood Estimation; image deblurring; image fractal model;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing, Communications and Computing (ICSPCC), 2014 IEEE International Conference on
Conference_Location
Guilin
Print_ISBN
978-1-4799-5272-4
Type
conf
DOI
10.1109/ICSPCC.2014.6986258
Filename
6986258
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