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Multi-core Median Redescending M-Estimator for Impulsive Denoising in Color Images

机译:彩色图像中冲动去噪的多核中位数重建M估计

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In this paper, to reduce impulsive noise in color images we propose an extension of the Median Redescending M-Estimator. For that purpose, a multitasking approach was developed such as a multi-core processing in order to reduce in parallel the noise on R, G and B color channels. With this paradigm, an acceleration up to three times can be guaranteed compared to the sequential paradigm, while having the ability to reduce corrupted data up to densities of 80% of fixed-value and 40% of random-value impulsive noises, guaranteeing the preservation of edges. The effectiveness of our proposal is verified by quantitative and qualitative results.
机译:在本文中,为了减少彩色图像中的脉冲噪声,我们提出了中位重建M估计的延伸。 为此目的,开发了一种多址处理方法,例如多核处理,以便在R,G和B颜色通道上并行降低噪声。 通过这种范例,与顺序范式相比,可以保证高达三次的加速度,同时能够将损坏的数据减少到80%的固定值和40%的随机价值脉冲噪声的密度,保证保存 边缘。 我们提案的有效性是通过定量和定性结果验证的。

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