探讨了一种行投影块迭代算法来求解大型相容线性系统。
In this paper we discuss a block-iterative algorithm with row projection for solving large consistent linear system.
然后通过迭代反投影算法进行超分辨率重建。
Secondly, the super-resolution reconstruction is implemented using the iterative back projection algorithm.
文章在图像配准的基础之上，采用后向投影迭代算法对图像序列进行了高分辨率重构，并给出了其中详细的算法和实现过程。
In the paper, based on the image registration, iterative back-projection technique is used to construct high resolution from image sequences, in which algorithms and realization are given in detail.
同时也讨论了投影逼近迭代算法。
An approximation-projection iterative algorithm is investigated.
与已有的加权迭代特征算法比较，该算法避免了所有点参与计算相机的投影矩阵，运算速度更快。
Compared to previous methods, this algorithm does not involve the problem of computing projection matrix of camera with all the points and its computing speed is faster.
该算法将噪声的统计特性引入到投影迭代的限制条件之中，使得该推广的POCS算法具有很好的去噪声能力。
The generalized POCS algorithm introduces the statistics of the noise to the constraints of projection iteration so that the algorithm is able to eliminate the noise effectively.
该方法基于MAP算法，通过利用梯度投影的方法对重建结果不断进行迭代优化得到最终的理想高分辨率影像。
In order to attain a high-resolution image, the algorithm is based on the MAP algorithm, solving the optimization by proposed iteration steps with using the gradient projection method.
对于迭代重建，目前尚无很好地解决该问题的算法，特别是对扇束投影重建问题。
Unfortunately, up to now, there is no an efficient algorithm to deal with the iterative reconstruction algorithm, especially from fan-scanned projections.
详细分析了投影噪声、投影方向数、场分布性质对重建精度的影响，并与代数迭代重建算法结果进行对比。
The effects of noise, view numbers and distribution are analyzed and this algorithm is compared with ART algorithm.
提出一种实时帧迭代反向投影算法实现对图像序列的超分辨率处理。
A real-time frame iterative back-projection algorithm for image sequences superresolution is proposed.
通过迭代求解法和高斯金字塔模型，快速精确地估计得到配准参数，采用凸集投影（POCS）算法对图像序列进行了超分辨率重建。
Based on the set theoretic formulation, a projection onto convex sets (POCS) algorithm is applied to find the solution to face image reconstruction.
该算法根据均方偏差的收敛条件，在迭代过程中不断减小投影阶数。
According to the condition of convergence on the Mean-Square Deviation, the algorithm decreases its order as iteration goes on.
该算法简化了投影系数矩阵的计算，调整了迭代算法逐线校正的迭代顺序。
This method proposes simplified computation of projection matrix and effectively adjusts the successive line iterative sequences.
该算法简化了投影系数矩阵的计算，调整了迭代算法逐线校正的迭代顺序。
This method proposes simplified computation of projection matrix and effectively adjusts the successive line iterative sequences.
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