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| 基于序列子集共轭梯度的超分辨率图像重构 | |
| 引用本文： | 吴强,刘琚,乔建苹,王行愚.基于序列子集共轭梯度的超分辨率图像重构[J].计算机工程,2007,33(24):189-190. |
| 作者姓名： | 吴强 刘琚 乔建苹 王行愚 |
| 作者单位： | 1. 驻511厂军代表室,南京,210002 2. 山东大学信息科学与工程学院,济南,250100 3. 华东理工大学信息科学与工程学院,上海,200037 |
| 摘 要： | 提出一种基于序列子集共轭梯度最优化算法的超分辨率图像重建算法。通过图像配准算法估计得到不同低分辨率图像间的平移和旋转量，结合期望图像的统计先验对问题进行规整，建立优化的代价函数。利用序列子集共轭梯度最优化迭代算法求解，得到高分辨率图像。仿真结果表明，该算法可以使内存降低15％，运算速度提高20％。 |
| 关 键 词： | 图像重构 超分辨率 共轭梯度 |
| 文章编号： | 1000-3428(2007)24-0189-02 |
| 修稿时间： | 2007年6月30日 |
Super-resolution Image Reconstruction Based on Sequence of Subset Conjugate Graduate Optimization |
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| WU Qiang,LIU Ju,QIAO Jian-ping,WANG Xing-yu.Super-resolution Image Reconstruction Based on Sequence of Subset Conjugate Graduate Optimization[J].Computer Engineering,2007,33(24):189-190. | |
| Authors: | WU Qiang LIU Ju QIAO Jian-ping WANG Xing-yu |
| Affiliation: | 1. The No.511 Factory of the PLA, Nanjing 210002; 2. School of Information Science and Engineering, Shandong University, Jinan 250100; 3. School of Information Science and Engineering, East China University of Science & Technology, Shanghai 200037 |
| Abstract: | A sequence of subset conjugate graduate optimization based super-resolution algorithm is proposed for super-resolution,where image registration algorithm is used to estimate the displacement and rotation between different low-resolution images,prior knowledge is used for regulation and building the cost function,and the high-resolution image is estimated by using sequence subset conjugate graduate optimization algorithm.Simulation results demonstrate that the method can realize the super-resolution with 15% memory reduction and 20% high speed promotion. |
| Keywords: | image reconstruction super-resolution conjugate graduate |
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