DocumentCode :
2211287
Title :
Model-based robust variational method for motion de-blurring
Author :
Saito, Takahiro ; Sano, Taishi ; Komatsu, Takashi
Author_Institution :
Dept. of Electron. & Inf. Frontiers, Kanagawa Univ., Yokohama, Japan
fYear :
2006
fDate :
4-8 Sept. 2006
Firstpage :
1
Lastpage :
5
Abstract :
Once image motion is accurately estimated, we can utilize those motion estimates for image sharpening and we can remove motion blurs. First, this paper presents a variational motion de-blurring method using a spatially variant model of motion blurs. The standard variational method is not proper for the motion de-blurring, because it is sensitive to model errors, and occurrence of errors are inevitable in motion estimation. To improve the robustness against the model errors, we employ a nonlinear robust estimation function for measuring energy to be minimized. Secondly, we experimentally compare the variational method with our previously presented PDE-based method that does not need any accurate blur model.
Keywords :
image restoration; motion estimation; nonlinear estimation; PDE-based method; image motion deblurring; image sharpening; model error; model-based robust variational method; motion estimation; nonlinear robust estimation function; spatially variant model; standard variational method; Cost function; Mathematical model; Motion estimation; PSNR; Robustness; Standards; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference, 2006 14th European
Conference_Location :
Florence
ISSN :
2219-5491
Type :
conf
Filename :
7071030
Link To Document :
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