DocumentCode :
593900
Title :
Image Restoration for Linear Local Motion-Blur Based on Cepstrum
Author :
Chao-Ho Chen ; Zhang Rui ; Kuo-Kun Tseng ; Jeng-Shyang Pan
Author_Institution :
Dept. of Electron. Eng., Nat. Kaohsiung Univ. of Appl. Sci., Kaohsiung, Taiwan
fYear :
2012
fDate :
25-28 Aug. 2012
Firstpage :
332
Lastpage :
335
Abstract :
This paper presents a real-time restoration method for linear local motion-blur image. for an image in which only the fast moving-object is blurred but the background is clear, the proposed basic strategy is to divide such an image into many sub images firstly and then detect the blurred sub image by the gradient distribution and the maximum of cepstrum. for a blurred sub image, the blur direction and blur length are estimated to calculate the parameters of point spread function (PSF) and Lucy-Richardson deconvolution algorithm is employed to restore this blurred sub image. Using many artificial and real blurred images, the experimental results show that the proposed approach is more accurate and robust than other methods.
Keywords :
cepstral analysis; deconvolution; gradient methods; image classification; image motion analysis; image restoration; object detection; optical transfer function; Lucy-Richardson deconvolution algorithm; PSF; blur direction estimation; blur length estimation; blurred subimage detection; cepstrum analysis; gradient distribution; image classification; image restoration; linear local motion blur image; point spread function; Approximation algorithms; Cepstrum; Deconvolution; Educational institutions; Estimation; Fourier transforms; Image restoration; blur detection; cepstrum; local motion blur; point spread function;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Genetic and Evolutionary Computing (ICGEC), 2012 Sixth International Conference on
Conference_Location :
Kitakushu
Print_ISBN :
978-1-4673-2138-9
Type :
conf
DOI :
10.1109/ICGEC.2012.102
Filename :
6457042
Link To Document :
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