一种改进的边缘检测与分块相结合的噪声估计方法
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TP391

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陕西省教育厅专项科研计划项目,榆林学院高层次人才科研基金


An Improved Fast Noise Estimation Approach by Assembling t Edge detection and Block Based Methods
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Specific Research Program in Department of Education of Shaanxi province,Yulin College Research Funds on High-Level Talents

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    摘要:

    在图像处理中,噪声估计是个重要问题。Aishy和Eric[1]提出了一种针对高斯白噪声的方差估计方法,给了一种自适应选择平滑子块的方法和一个用来计算子块平滑度的结构分析器。此方法存在两个问题:1)含有边缘纹理的子块可能被选择为平滑子块而影响结果精度;2)一些特殊子块具有极高方差但平滑度极小,如果图像含有一个以上的特殊子块,可能造成非常严重的过估计。上述两个问题都是由边缘纹理造成的,本文提出一种边缘检测与分块相结合的估计方法。本文方法首先利用简单边缘检测算法除去含有连续边缘点的子块,然后用Aishy方法。实验结果表明本文方法能够有效避免特殊情况下的严重过估计,而且在一些噪声水平时比Aishy方法的结果更精确。

    Abstract:

    Noise estimation is one of the most important research topics in image processing. Aishy and Eric[1] have proposed a variance estimation method used in Gaussian white-noise, in which, a measure was provided to determine the homogeneous blocks and an analyzer was used in calculating the homogeneities. The approach should present two shortcomings corresponding to structures and textures. One is that the blocks with edge textures should be considered as intensity-homogeneous blocks that could have an effect on estimation accuracy. The other is that some special blocks have high variance but low homogeneity could result in over estimation. In order to avoid the two shortcomings mentioned above, in this paper we have proposed an improved noise estimation approach by combining fast edge detection and block based methods. The blocks with continuous points were firstly excluded rejected by using fast edge detection method. The experimental results indicated that our method can avoid over estimation effectively in special conditions and can obtain more accurate results than the Aishy and Eric’s method did.

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吴疆. 一种改进的边缘检测与分块相结合的噪声估计方法[J]. 科学技术与工程, 2011, (27): .
WUJIANG. An Improved Fast Noise Estimation Approach by Assembling t Edge detection and Block Based Methods[J]. Science Technology and Engineering,2011,(27).

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  • 收稿日期:2011-06-30
  • 最后修改日期:2011-07-06
  • 录用日期:2011-07-05
  • 在线发布日期: 2011-08-09
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