Abstract
In many applications, the received image is degraded by unknown blur and noise. Traditional blind image deconvolution algorithms have drawback of noise amplification. For robustness against the influence of noise, this paper proposes a novel blind image deconvolution algorithm by combining the support vector regression (SVR) approach and the total variation approach. The proposed algorithm has a lower computational complexity and a good performance in image denoising and image deblurring. Illustrative examples show that the proposed blind image deconvolution algorithm and has better performance in improvement signal-to-noise ratio than two traditional blind image restoration algorithms.
Published Version
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