摘要
采用点插值法、循环矩阵模型、拉普拉斯正则化方法和共轭梯度迭代法,解决了空间变化图像复原过程中空间变化点扩展函数的获取、反卷积的计算模型、反问题的病态性以及复原算法等问题。在此基础上,建立了空间变化图像复原方法,并分析了图像复原的基本模型。最后,通过仿真对比了提出的空间变化图像复原算法和空间不变图像复原算法,结果表明,空间变化算法的图像复原结果好于空间不变算法。
The acquisition of point spread function varying with space,the calculation model of deconvolution,the morbidness of inverse problem,and the renatured algorithm are solved using point interpolation method,cyclic matrix model,Laplace regularization and conjugate gradient iteration.Upon which,the image restoration algorithm with varying space is established and the basic model of image restoration is analyzed.At last,the image restoration algorithms with and without varying space are compared with simulation,the result shows that the image restoration algorithm with varying space is better than spatial invariant algorithm.
出处
《光学学报》
EI
CAS
CSCD
北大核心
2017年第1期113-121,共9页
Acta Optica Sinica
基金
中国航天科技五院CAST创新基金重点项目(CASTHCKJ)
关键词
图像处理
线性空间变化
主元分析
点插值
拉普拉斯正则化
image processing
linear spatial variation
principal component analysis
point interpolation
Laplace regularization
