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
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;
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
DOI :
10.1109/PCSPA.2010.158