对空间自适应正则化图像盲复原方法的理论和相应算法进行分析。
This thesis analyzes the theoretics of a space-adaptive regularization method for blind image restoration.
为了改进空域IBD算法的病态，提出了一种自适应正则化算子，取得了较好的恢复结果。
For improving the ill-posed problem of the space IBD method, an adaptive operator is proposed in this paper. The results show that the improved algorithm works well.
在加权最小二乘的基础上，结合PDE正则化，提出了一种视频图像序列超分辨率重建的自适应滤波方法。
An adaptive filter for video image sequence super resolution reconstruction is proposed on the basis of the weighted least square and PDE regularization in this paper.
在标准正则化理论中建议一类局部相互作用场和自适应正则项。
A set of local interaction field and adaptive regularizers are introduced to usual regularization theory.
根据数据目标函数、模型约束目标函数和正则化因子之间的关系，提出了两种正则化因子自适应调节方法。
Third two adaptive methods of regularized factors are put forward based on the relations of data object function, model constraint object function, and regularized factor.
该算法通过对正则化线性斜率的自适应，更新动态优化代价函数，以降低对PET图像高频成分的抑制。
This algorithm can adaptively optimize the cost function and reduce the suppression of high frequency component of PET image by adaptively updating linear slope of the RP.
其基本思想是利用验前模型信息确定正则化矩阵，利用验后观测信息确定自适应因子。
The regularization matrix will be chosen by prior information of the model parameters and the adaptive factor, however, will be determined by posterior information.
同时给出一种自适应确定正则化参数的方法。
At the same time, the method to choose regularization parameter adaptively is given.
第二，在现有复原模型的完善上，重新构建正则化参数与正则化项，构造了新的具有空间自适应性质的正则化图像复原模型。
Secondly, to perfect the known restoring models, a new space-adaptive regularization model of image restoration is constructed by redesigning regularized parameter and regularized item.
第二，在现有复原模型的完善上，重新构建正则化参数与正则化项，构造了新的具有空间自适应性质的正则化图像复原模型。
Secondly, to perfect the known restoring models, a new space-adaptive regularization model of image restoration is constructed by redesigning regularized parameter and regularized item.
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