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| 增强稀疏编码的超分辨率重建 | |
| 引用本文： | 李民,程建,乐翔,罗环敏,刘小芳.增强稀疏编码的超分辨率重建[J].光电工程,2011,38(1):127-133. |
| 作者姓名： | 李民 程建 乐翔 罗环敏 刘小芳 |
| 作者单位： | 1. 电子科技大学地表空间信息技术研究所,成都,611731;桂林空军学院科研部,广西,桂林,541003 2. 电子科技大学地表空间信息技术研究所,成都,611731;电子科技大学电子工程学院,成都,611731 3. 电子科技大学电子工程学院,成都,611731 4. 电子科技大学地表空间信息技术研究所,成都,611731 |
| 基金项目： | 国家973项目，国家博士后基金，电子科枝大学青年科技基金重点项日资助 |
| 摘 要： | 本文提出一种基于稀疏字典编码的超分辫率方法.该方法有效地建立高、低分辫率图像高频块间的稀疏关联,并将这种关联作为先验知识来指导基于稀疏字典的超分辫率重建.较超完备字典,稀疏字典对先验知识的表达更紧凑、更高效.字典训练过程中,本文选用高频信息作为高分辫率图像的特征,更有效地建立高、低分辫率图像决间的稀疏关联,所需的训练样... |
| 关 键 词： | 超分辫率 基于学习 稀疏编码 稀疏字典 稀硫K-SVD |
Super-resolution Reconstruction Based on Improved Sparse Coding |
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| LI Min,CHENG Jian,LE Xiang,LUO Huan-min,LIU Xiao-fang.Super-resolution Reconstruction Based on Improved Sparse Coding[J].Opto-Electronic Engineering,2011,38(1):127-133. | |
| Authors: | LI Min CHENG Jian LE Xiang LUO Huan-min LIU Xiao-fang |
| Affiliation: | LI Min1a,2,CHENG Jian1a,1b,LE Xiang1b,LUO Huan-min1a,LIU Xiao-fang1a ( 1.a. Institute of Geo-Spatial Information Science and Technology,b. School of Electronic Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China,2. Department of Scientific Research,Guilin Airforce Academy,Guilin 541003,Guangxi Zhuang Automomous Region,China ) |
| Abstract: | A super-resolution method based on sparse dictionary is presented. The method efficiently builds sparse association between high-frequency components of HR image patches and LR image feature patches, and defines the association as a prior knowledge to guide super-resolution reconstruction based on sparse dictionary. Compared with overcomplete dictionary, sparse dictionary is more compact and effective to express the prior knowledge. We choose the high-frequency component of the HR image patch as its feature... |
| Keywords: | super-resolution learning-based sparse coding sparse dictionary sparse K-SVD |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |
