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An Image Filter for Eliminating Impulse Noise Based on Type-2 Fuzzy Sets

机译:用于消除基于Type-2模糊集的脉冲噪声的图像滤波器

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Large amount of information is random in image processing. To some extent, type-1 fuzzy sets can reduce the effect of uncertainties. Fuzzy sets theory can provide us with knowledge-based and robust tools for image processing. But there are many situations where it needs to be extended to type-2 fuzzy sets because it can also be difficult to determine the crisp membership function itself. By computing the fuzziness of the pixels' corrupted degree, a new image filter based on type-2 fuzzy sets for impulse noise is presented in this paper. Comparing with some other filters, this new filter is more effective. In the end, simulation results show that the new algorithm is feasible.
机译:大量信息在图像处理中是随机的。在某种程度上,1型模糊集可以降低不确定性的效果。模糊集理论可以为我们提供基于知识和鲁棒工具的图像处理。但是有许多情况需要扩展到类型-2模糊集,因为它也可能很难确定清脆的成员函数本身。通过计算像素损坏程度的模糊性,本文提出了一种基于用于脉冲噪声的2型模糊组的新图像滤波器。与其他滤波器相比,这个新的过滤器更有效。最后,仿真结果表明,新算法是可行的。

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