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利用点扩展函数信息的变分图像去噪及增晰方法

姚伟1, 孙即祥1(国防科学技术大学电子科学与工程学院,长沙 410073)

摘 要
基于偏微分方程(PDE)及变分法的图像去噪方法利用其数学特性得到了优于传统方法的结果,但很多模型只考虑了去噪的问题。通过对最小化凸能量函数模型引入点扩展函数信息,构造了具有去模糊效果的变分去噪模型,采用了Kacˇanov线性化方法进行求解,得到了更好的结果,实验结果及数据证明了模型的有效性。
关键词
A Variational Image De-noising and De-blurring Method Incorporating Point Spread Function Information

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Abstract
With superior mathematical characteristics, PDE and variational image de-noising methods achieve better results than traditional methods. Many models deal with de-noising problems only. A new variational model incorporating point spread function information was constructed to deal with de-noising and de-blurring problems concurrently. Kacˇanov linearization technique was used to solve the new model. Experiments and related data proved the effectiveness of the model.
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