分数阶微分局部强反射的去噪方法应用.pdfVIP

第 37卷第 12期 电 子 与 信 息 学 报 Vol.37 No.12 2015年 12月 Journal of Electronics Information Technology Dec. 2015 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 (华北理工大学电气工程学院 唐山 063000) 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。 关键词：图像去噪；分数阶微分；强反射；光条中心提取；熵 中图分类号： TP391.4 文献标识码： A 文章编号：1009-5896(2015)12-3046-05 DOI: 10.11999/JEIT150500 Application of Denoising Method to Local Strong Reflection Based on Fractional Differentials Tang Rui-yin Shen Hong-hai He Hong-kun (College of Electrical Engineering, North China University of Science and Technology, Tangshan 063000, China) 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. Key words: Image denoising; Fractional differentials; Strong reflection; Extraction of light stripe center; Entropy 1 引言 常见的光条中心线提取方法有灰度重心法、极 值法、梯度阈值法和利