应用改进的神经网络去除脉冲噪声

Chao Deng, Hong-Min Liu, Zhi-Heng Wang
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引用次数: 3

摘要

提出了一种新的基于改进神经网络的去噪算法,用于去除数字图像中的脉冲噪声。首先,利用改进的神经网络检测噪声像素,并将其与无噪声像素进行有效区分;其次,将噪声像素进一步替换为局部相似度最高的合适像素;最后,输出是无噪声像素和合适像素的组合。该算法能够有效地去除脉冲噪声。同时可以很好地保留更多的图像细节。实验结果表明,新算法比传统的滤波算法有更大的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Applying an improved neural network to impulse noise removal
A new noise removal algorithm based on improved neural network, is applied to remove the impulse noise of the digital images. First of all, an improved neural network is used to detect the noise-pixels and distinguish it from noise-free pixels efficiently; Second, the noise-pixels are replaced further by the suitable pixel which has the most local similarity; Finally, the output is the combination of the noise-free pixels and the suitable pixel. The proposed algorithm is capable of removing the impulse noise effectively. At the same time it can keep more image details well. Experiential results show that the new algorithm is more improved than the conventional filters.
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