| 基于EMD-CLEAN的图像去噪方法 |
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| 引用本文：曾展挺.基于EMD-CLEAN的图像去噪方法[J].计算技术与自动化,2022,(1):112-116 |
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| 中文摘要:噪声的存在会影响对图像中有用信息的提取。针对经验模态分解(Empirical Mode Decomposition，EMD)方法噪声抑制后图像质量下降的问题，提出了一种基于EMD-CLEAN的图像去噪方法。首先利用EMD对含噪图像进行分析，将其自动分解为一系列本征模函数(Intrinsic Mode Function，IMF)，然后利用信息熵差值自动确定高频含噪IMF的数量，并利用CLEAN 算法对高频含噪IMF进行噪声抑制，最后将低频IMF与噪声抑制后的高频IMF叠加获得重构图像。采用仿真数据的实验结果表明，所提方法能够有效抑制噪声分量，同时较好地保留图像中的细节信息，具有一定的应用前景。 |
| 中文关键词:图像去噪 经验模态分解 信息熵 CLEAN算法 |
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| Image Denoising Method Based on EMD-CLEAN |
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| Abstract:The existence of noise will affect the extraction of useful information from the image. To solve the problem of image quality degradation after empirical mode decomposition (EMD) noise suppression, an image denoising method based on EMD-CLEAN is proposed. Firstly, the noisy image is analyzed by EMD, which is automatically decomposed into a series of local mode functions (IMF), and then the number of high-frequency noisy IMF is automatically determined by information entropy difference, and CLEAN is used Finally, the low-frequency IMF is superimposed with the high-frequency IMF after noise suppression to obtain the reconstructed image. The experimental results of simulation data show that the proposed method can effectively suppress the noise component and retain the details of the image, which has a certain application prospect. |
| keywords:image denoising empirical mode decomposition information entropy CLEAN algorithm |
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