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。
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. Kacanov linearization technique was used to solve the new model. Experiments and related data proved the effectiveness of the model.
出处
《中国图象图形学报》
CSCD
北大核心
2009年第9期1796-1801,共6页
Journal of Image and Graphics
关键词
变分法
点扩展函数
图像去噪
图像增晰
variational calculus, point spread function, image de-noising, image de-blurring
