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首页> 外文期刊>Fuzzy sets and systems >Using an adaptive neuro-fuzzy inference system-based interpolant for impulsive noise suppression from highly distorted images
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Using an adaptive neuro-fuzzy inference system-based interpolant for impulsive noise suppression from highly distorted images

机译:使用基于自适应神经模糊推理系统的插值法从高度失真的图像中抑制脉冲噪声

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摘要

A new impulsive noise (IN) suppression filter, entitled Adaptive neuro-fuzzy inference system (ANFIS)-based impulsive noise suppression Filter, which shows a high performance at the restoration of images distorted by IN, is proposed in this paper. The extensive simulation results show that the proposed filter achieves a superior performance to the other filters mentioned in this paper in the cases of being effective in noise suppression and detail preservation, especially when the noise density is very high.
机译:提出了一种基于自适应神经模糊推理系统(ANFIS)的脉冲噪声抑制滤波器,该算法在恢复因IN失真的图像上具有很高的性能。广泛的仿真结果表明,在有效抑制噪声和保留细节的情况下,特别是当噪声密度很高时,所提出的滤波器比本文中提到的其他滤波器具有更好的性能。

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