Denoising method in mixture noise image

doi:10.3778/j.issn.1002-8331.2009.29.043

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (29): 144-145.DOI: 10.3778/j.issn.1002-8331.2009.29.043

• 图形、图像、模式识别 • Previous Articles Next Articles

Denoising method in mixture noise image

QIAO Nao-sheng

School of Physics and Electronic，Hunan University of Arts and Science，Changde，Hunan 415000，China

Received:2008-11-13 Revised:2009-03-16 Online:2009-10-11 Published:2009-10-11
Contact: QIAO Nao-sheng

一种混合噪声图像去噪方法

乔闹生

湖南文理学院物理与电子科学学院，湖南常德 415000

通讯作者: 乔闹生

Abstract

Abstract: The reason why different denoising methods are used in the image that contains Gaussian white noise and impulse noise is analyzed firstly；The denoising methods of low frequency subband images and high frequency subband images that have been obtained after wavelet transform are given afterwards.The method of improved local average filter is used to denoise in the low frequency subband images.And the methods of median filter，threshold processing and enhancement of wavelet coefficient are used to denoise in the high frequency subband images；At last，the recovered image after using contrary wavelet transform in each subband image that has been processed is obtained；The results of experiment verifies the correctness of the theory analysis.

Key words: image denoising, wavelet transform, mixture noise, local average filter, median filter

摘要： 首先分析了含有高斯白噪声和脉冲噪声的图像必须采用不同去噪方法的原因；然后分别给出了小波变换后的低频子带图像与高频子带图像的去噪方法：用改进的邻域平均法对低频子带图像进行去噪处理。对高频子带图像采用中值滤波、阀值处理、小波系数增强方法去除脉冲噪声；最后对经过处理后的各子带图像进行小波逆变换得到恢复图像；实验结果证明了理论分析的正确性。

关键词: 图像去噪, 小波变换, 混合噪声, 邻域平均滤波, 中值滤波

CLC Number:

TP391.41

QIAO Nao-sheng. Denoising method in mixture noise image[J]. Computer Engineering and Applications, 2009, 45(29): 144-145.

乔闹生. 一种混合噪声图像去噪方法[J]. 计算机工程与应用, 2009, 45(29): 144-145.

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Denoising method in mixture noise image

一种混合噪声图像去噪方法

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