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Parallel Implementation of Collaborative Filtering Technique for Denoising of CT Images

机译:CT图像去噪的协同过滤技术的平行实现

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In the paper parallelization of the collaborative filtering technique for image denoising is presented. The filter is compared with several other available methods for image denoising such as Anisotropic diffusion, Wavelet packets, Total Variation denoising, Gaussian blur, Adaptive Wiener filter and Non-Local Means filter. Application of the filter is intended for denoising of the medical CT images as a part of image pre-processing before image segmentation. The paper is evaluating the filter denoising quality and describes effective parallelization of the filtering algorithm. Results of the parallelization are presented in terms of strong and weak scalability together with algorithm speed-up compared to the typical sequential version of the algorithm.
机译:介绍了对图像去噪的协同过滤技术的纸张并行化。将过滤器与几种其他可用方法进行比较,用于图像去噪,例如各向异性扩散,小波包,总变化的噪声,高斯模糊,自适应维纳滤波器和非局部装置滤波器。滤波器的应用旨在用于在图像分割之前作为图像预处理的一部分去噪。本文正在评估过滤器去噪质量,并描述过滤算法的有效并行化。与算法的算法相比,并行化的结果与算法加速,与算法的算法相比速度较强。

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