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A Hybrid Method of Image Restoration and Denoise of CT Images

机译:CT图像的图像恢复和去噪的混合方法

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Image degradation is a universal problem in imaging system for the hardware restriction. Digital image processing can be used to enhance resolution and noise reduction effectively; thus to improve image quality with less cost. Aiming at reducing noise in CT imaging, this paper proposes a hybrid algorithm with several improvements on existing algorithms including the constrained least-square-filter algorithm, the Lucy-Richardson algorithm, non-local-means-filter algorithm, and wavelet-filter algorithm. Comparing the results with these algorithms, we conclude that the algorithm combining with Lucy-Richardson algorithm and non-local means filter algorithm achieves better performs in de-noising and thus raising image resolution. This proposed hybrid algorithm for super-resolution images can apparently increase image resolution from 5lp/cm to 11.5lp/cm and significantly reduce mean standard error from 92 to 18.
机译:图像劣化是硬件限制的成像系统中的一个普遍问题。数字图像处理可用于有效增强分辨率和降噪;因此,以更少的成本提高图像质量。旨在降低CT成像中的噪声,本文提出了一种混合算法,其具有若干改进的现有算法,包括约束最小二乘滤波器算法,Lucy-Richardson算法,非本地均值滤波算法和小波滤波算法。将结果与这些算法进行比较,我们得出结论,与Lucy-Richardson算法和非局部意义滤波算法的算法实现更好地执行去噪,从而提高图像分辨率。这种用于超分辨率图像的提出的混合算法可以显然将图像分辨率从5LP / cm到11.5LP / cm增加,并显着减少92至18的平均标准误差。

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