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| 基于低分辨率图像的自适应超分辨率重构算法 | |
| 引用本文： | 侯跃谦,谭庆昌,孙秋成. 基于低分辨率图像的自适应超分辨率重构算法[J]. 计算机工程, 2010, 36(16): 192-194 |
| 作者姓名： | 侯跃谦 谭庆昌 孙秋成 |
| 作者单位： | 1. 吉林大学机械科学与工程学院,长春,130025;长春大学机械工程学院,长春,130022 2. 吉林大学机械科学与工程学院,长春,130025 3. 吉林大学机械科学与工程学院,长春,130025;长春工业大学基础科学学院,长春,130000 |
| 基金项目： | 吉林省教育厅"十一五"科学技术研究基金 |
| 摘 要： | 提出一种适用于内部独立运动、静态等多种模型的、基于多幅低分辨率图像的超分辨率重构算法。该算法赋予各低分辨率图像不同的权重和正则化参数，在每次迭代时对权重系数和正则化参数进行更新，采用松弛迭代法得到最优解，从而获得重构图像。实验结果表明，该算法获得的重构图像效果优于双三次B样条插值法和传统的最大后验概率估计方法。 |
| 关 键 词： | 自适应 正则化 超分辨率 松弛迭代 |
Self-adaptive Super-resolution Reconstruction Algorithm Based on Low-resolution Images |
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| HOU Yue-qian,TAN Qing-chang,SUN Qiu-cheng. Self-adaptive Super-resolution Reconstruction Algorithm Based on Low-resolution Images[J]. Computer Engineering, 2010, 36(16): 192-194 | |
| Authors: | HOU Yue-qian TAN Qing-chang SUN Qiu-cheng |
| Affiliation: | (1. Institute of Mechanical Science and Engineering, Jilin University, Changchun 130025; 2. Mechanical Engineering College, Changchun University, Changchun 130022; 3. College of Basic Science, Changchun University of Technology, Changchun 130000) |
| Abstract: | This paper proposes a super-resolution reconstruction algorithm based on multiple low-resolution images, which is suitable for inner independence model or static state model. Various weights and regularization parameters are assigned to each low-resolution image, and weights and regularization parameters are updated in each iteration process. The optimal solutions are obtained with relaxation iteration method, so that the image is reconstructed. Experimental result shows that the effect of reconstruction with the algorithm is better than those of cubic B-spline interpolation and traditional MAP estimation method. |
| Keywords: | self-adaptive regularization super-resolution relaxation iteration |
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