分数阶微分局部强反射的去噪方法应用

唐瑞尹; 沈鸿海; 何鸿鲲

doi:10.11999/JEIT150500

分数阶微分局部强反射的去噪方法应用

doi: 10.11999/JEIT150500

基金项目:

国家自然科学基金(51105273)

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- 被引次数: 0
出版历程
- 收稿日期: 2015-04-30
- 修回日期: 2015-07-27
- 刊出日期: 2015-12-19

Application of Denoising Method to Local Strong Reflection Based on Fractional Differentials

Funds:

The National Natural Science Foundation of China (51105273)

摘要

摘要: 针对具有强反射的表面光条图像出现散斑或复合散斑等严重噪声情况，该文提出一种利用分数阶微分增强的图像去噪声的处理算法，突出噪声的颗粒化特征，通过连通区域面积统计的方法对有效连续光条进行分离并去除散斑噪声，获得有效光条图像，最后利用灰度重心法提取有效光条的中心。经实验对比，该方法得到的信息熵值和光条中心提取精度都显著提高，体现了分数阶微分算法增强图像高频信息的同时，有效保留更多的低频信息的特点，保留了更多的图像纹理细节，显著提高了特征光条中心提取精度。
- 图像去噪 /
- 分数阶微分 /
- 强反射 /
- 光条中心提取 /
- 熵
Abstract: To deal with the problem of the serious speckle or composite speckle noise in the image of the strong reflection surface, an image denoising algorithm based on fractional differential enhancement is proposed, which can highlight the granular characteristics of noise, by means of the method of connected region area to remove speckle noise and separate the effective continuous light stripe. Finally, the center of the effective light stripe is extracted with the gray gravity method. By comparison, the method can significantly improve the information entropy and the extraction accuracy of the light stripe center. The fractional differential enhancement algorithm enhance the high frequency information of the image, at the same time it effectively preserves the features of the low frequency information and more details of image texture, and the accuracy of feature extraction is significantly improved.
- Image denoising /
- Fractional differentials /
- Strong reflection /
- Extraction of light stripe center /
- Entropy

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参考文献(19)

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