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
Link To Document :
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