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

机译:基于第二类模糊集的脉冲噪声消除图像滤波器

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摘要

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。 1类模糊集可以在一定程度上减少不确定性的影响。模糊集理论可以为我们提供基于知识的健壮工具进行图像处理。但是,在许多情况下,需要将其扩展为2型模糊集,因为它也可能难以确定明晰的隶属函数本身。通过计算像素破坏度的模糊性,提出了一种基于2类模糊集的脉冲噪声图像滤波器。与其他一些过滤器相比,此新过滤器更有效。最后,仿真结果表明该算法是可行的。

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