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分?jǐn)?shù)階微分局部強(qiáng)反射的去噪方法應(yīng)用

唐瑞尹,  沈鴻海,  何鴻鯤

唐瑞尹, 沈鴻海, 何鴻鯤. 分?jǐn)?shù)階微分局部強(qiáng)反射的去噪方法應(yīng)用[J]. 電子與信息學(xué)報(bào), 2015, 37(12): 3046-3050. doi: 10.11999/JEIT150500
引用本文: 唐瑞尹, 沈鴻海, 何鴻鯤. 分?jǐn)?shù)階微分局部強(qiáng)反射的去噪方法應(yīng)用[J]. 電子與信息學(xué)報(bào), 2015, 37(12): 3046-3050. doi: 10.11999/JEIT150500
Tang Rui-yin, Shen Hong-hai, He Hong-kun. Application of Denoising Method to Local Strong Reflection Based on Fractional Differentials[J]. Journal of Electronics & Information Technology, 2015, 37(12): 3046-3050. doi: 10.11999/JEIT150500
Citation: Tang Rui-yin, Shen Hong-hai, He Hong-kun. Application of Denoising Method to Local Strong Reflection Based on Fractional Differentials[J]. Journal of Electronics & Information Technology, 2015, 37(12): 3046-3050. doi: 10.11999/JEIT150500

分?jǐn)?shù)階微分局部強(qiáng)反射的去噪方法應(yīng)用

doi: 10.11999/JEIT150500 cstr: 32379.14.JEIT150500
基金項(xiàng)目: 

國(guó)家自然科學(xué)基金(51105273)

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

Funds: 

The National Natural Science Foundation of China (51105273)

  • 摘要: 針對(duì)具有強(qiáng)反射的表面光條圖像出現(xiàn)散斑或復(fù)合散斑等嚴(yán)重噪聲情況，該文提出一種利用分?jǐn)?shù)階微分增強(qiáng)的圖像去噪聲的處理算法，突出噪聲的顆?；卣?，通過(guò)連通區(qū)域面積統(tǒng)計(jì)的方法對(duì)有效連續(xù)光條進(jìn)行分離并去除散斑噪聲，獲得有效光條圖像，最后利用灰度重心法提取有效光條的中心。經(jīng)實(shí)驗(yàn)對(duì)比，該方法得到的信息熵值和光條中心提取精度都顯著提高，體現(xiàn)了分?jǐn)?shù)階微分算法增強(qiáng)圖像高頻信息的同時(shí)，有效保留更多的低頻信息的特點(diǎn)，保留了更多的圖像紋理細(xì)節(jié)，顯著提高了特征光條中心提取精度。
    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.
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出版歷程
  • 收稿日期:  2015-04-30
  • 修回日期:  2015-07-27
  • 刊出日期:  2015-12-19

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