基于空间变化点扩展函数的图像直接复原方法

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。

Abstract

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.

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周程灏, 王治乐, 刘尚阔. 基于空间变化点扩展函数的图像直接复原方法[J]. 光学学报, 2017, 37(1): 0110001. Zhou Chenghao, Wang Zhile, Liu Shangkuo. Method of Image Restoration Directly Based on Spatial Varied Point Spread Function[J]. Acta Optica Sinica, 2017, 37(1): 0110001.

基于空间变化点扩展函数的图像直接复原方法

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