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Blind image restoration system using higher-order statistics and Radon transform

机译:使用高阶统计和Radon变换的盲图像恢复系统

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Abstract: We propose a complete system of blind image restoration. We have no restrictions about the blurring filter causing degradation to the original image. The blurring filter estimation part of this system consist of two main steps: the mapping of the blurred image into the Radon transform domain, and the blind blur identification in this domain. The mapping simplifies the computational complexity associated with our system from 2D to 1D domain. The blind blur identification is based on a modified optimization method which uses cumulants in the estimation of the filter coefficients. The deconvolution step is based on a least squares optimization method. Singular value decomposition technique is used in improving the optimization process in the estimation and deconvolution steps. Finally, the inverse Radon transform is computed to get the estimated restored image. !11
机译:摘要:建议一个完整的盲图像恢复系统。我们对模糊过滤器导致原始图像的劣化没有限制。该系统的模糊滤波器估计部分由两个主要步骤组成:模糊图像将模糊图像映射到氡变换域中,以及该域中的盲模糊识别。映射简化了与我们的系统相关联的计算复杂性,从2D到1D域。盲模糊识别基于修改的优化方法,其使用累积剂在滤波器系数的估计中。解卷积步骤基于最小二乘优化方法。奇异值分解技术用于提高估计和去卷积步骤中的优化过程。最后,计算逆氡变换以获得估计的恢复图像。 !11

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