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Blind Image Restoration Algorithm Iteratively Using Wavelet Denoising and Total Variation Regularization |
Zhou Zuo-feng①② Shui Peng-lang① |
①(National Lab of Radar Signal Processing, Xidian University, Xi’an 710071, China) ②(Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an 710119, China) |
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Abstract Blind image restoration is to recover the original image form the observed degraded image with unknown the Point Spread Function (PSF). This paper proposes a blind image restoration algorithm iteratively using wavelet denoising and total variation regularization. The observation model is first divided into two mutually associated sub-models, and this representation converses the blind restoration into the two issues of image denoising and image restoration, which makes us to solve the problem by iteratively using image denoising and image restoration algorithms. The stage of the PSF identification uses Total Variation (TV) regularization and the stage of image restoration uses wavelet denoising and TV regularization. The experimental results show that the proposed algorithm achieves better performance than the existing algorithms.
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Received: 28 May 2007
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Corresponding Authors:
Zhou Zuo-feng
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