Multi-Stage Image Restoration in High Noise and Blur Settings

S. Voronin
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Abstract

We describe a simple approach useful for improving noisy, blurred images. Our approach is based on the use of a parallel block-based low rank factorization technique for projection based reduction of matrix dimensions and on a customized iteratively reweighted CG approach followed by the use of a Fourier Wiener filter. The regularization scheme with a transform basis offers variable residual penalty and increased per-iteration performance. The outlined approach is particularly aimed at high blur and noise settings.
多阶段图像恢复在高噪点和模糊设置
我们描述了一个简单的方法,用于改善噪声,模糊的图像。我们的方法是基于使用并行的基于块的低秩分解技术,用于基于投影的矩阵维数降维,以及使用傅里叶维纳滤波器之后的自定义迭代重加权CG方法。具有变换基的正则化方案提供可变的残差惩罚和提高的每次迭代性能。概述的方法是特别针对高模糊和噪声设置。
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