DocumentCode
3092009
Title
Fractional Fourier-Contourlet Deblurring of Space Variant Degradation Coupled with Noise
Author
Wan, Hui ; Tao, Ran ; Wang, Yue
Author_Institution
Dept. of Electron. Eng., Beijing Inst. of Technol., Beijing, China
fYear
2010
fDate
17-19 Sept. 2010
Firstpage
632
Lastpage
635
Abstract
Fourier domain deblurring methods are not fit for space variant degradation due to time invariant property of the Fourier transform (FT). Filtering in the fractional Fourier transform (FRFT) domain can deblur space variant degradation effectively, but hardly denoise substantially in the meantime. We propose a fractional Fourier-contourlet restoration algorithm to remove the space variant blur and the white Gaussian noise in images. The deblurring is realized by the fractional Fourier filtering while denoising through the coutourlet shrinkage. Our hybrid scheme is based on the MSE minimization principle. This scheme resolves the problem of contradiction between deblurring and denoising in a single transform domain. Experiments demonstrate that the proposed algorithm can yield favorable performance to satisfy both sides of deblurring and denoising.
Keywords
AWGN; Fourier transforms; image restoration; Fourier transform; fractional Fourier contourlet deblurring; fractional Fourier filtering; space variant blur; space variant degradation; white Gaussian noise; Computed tomography; Degradation; Filtering; Image restoration; Noise; Noise reduction; Wavelet transforms; bivariant shrinkage; contourlet transform; fracional Fourier transform; optimal filtering; space variant blur; white Gaussian noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Pervasive Computing Signal Processing and Applications (PCSPA), 2010 First International Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4244-8043-2
Electronic_ISBN
978-0-7695-4180-8
Type
conf
DOI
10.1109/PCSPA.2010.158
Filename
5636071
Link To Document