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A Novel Blind Image Restoration Algorithm Using A SVR-Based Noise Reduction Technique

机译:一种新颖的盲图像恢复算法使用基于SVR的降噪技术

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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.
机译:在许多应用中,所接收的图像被未知的模糊和噪声劣化。传统的盲图像解卷积算法具有噪声放大的缺点。对于噪声影响的鲁棒性,本文通过组合支持向量回归(SVR)方法和总变化方法来提出一种新颖的盲图像解卷积算法。所提出的算法具有较低的计算复杂性和图像去噪和图像去纹理的良好性能。说明性示例示出了所提出的盲图像解卷积算法并且具有比两个传统的盲图像恢复算法的提高信噪比具有更好的性能。

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