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基于小波和各向异性扩散的PET图像MLEM重建算法
  • 期刊名称:计算机应用及软件
  • 时间:2013.11.11
  • 页码:50-53
  • 分类:TN911.73[电子电信—通信与信息系统;电子电信—信息与通信工程]
  • 作者机构:中北大学电子测试技术重点实验室,山西太原030051
  • 相关基金:National Natural Science Foundation of China (No. 61271357); International S &T Cooperation Program of Shanxi Province (No. 2013081035)
  • 相关项目:低剂量X射线CT重建算法研究
作者: 桂志国|
中文摘要:

针对图像细节增强过程中梯度对噪声敏感的缺点,本文提出了一种改进的基于差分曲率和对比度场的细节增强算法.首先,该算法利用差分曲率代替梯度值决定系数的放大倍数,以差分曲率作为自变量的放大系数函数考虑了更多的邻域像素,从而克服了图像梯度对噪声敏感的缺点;然后,利用该放大系数非线性地放大对比度场,并构造能量泛函;最后,通过变分方法得到增强后的图像.标准测试图像和工业X射线图像的实验结果表明,本文提出的算法在有效增强图像对比度的同时,能够较好地抑制噪声.

英文摘要:

The gradient image is always sensitive to noise in image detail enhancement. To overcome this shortage, an improved detail enhancement algorithm based on difference curvature and contrast field is proposed. Firstly, the difference curvature is utilized to determine the amplification coefficient instead of the gradient. This new amplification function of the difference curvature takes more neighboring points into account, it is therefore not sensitive to noise. Secondly, the contrast field is nonlinearly amplified according to the new amplification coefficient. And then, with the enhanced contrast field, we construct the energy functional. Finally, the enhanced image is reconstructed by the variational method. Experimental results of standard testing image and industrial X-ray image show that the proposed algorithm can perform well on increasing contrast and sharpening edges of images while suppressing noise at the same time.

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