| 基于多重解析字典学习和观测矩阵优化的压缩感知 |
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| 引用本文： | 练秋生,王小娜,石保顺,陈书贞. 基于多重解析字典学习和观测矩阵优化的压缩感知[J]. 计算机学报, 2015, 38(6) |
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| 作者姓名： | 练秋生 王小娜 石保顺 陈书贞 |
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| 作者单位： | 燕山大学信息科学与工程学院 河北秦皇岛 066004 |
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| 基金项目： | 国家自然科学基金，河北省自然科学基金(F2014203076)资助.This work is supported by the National Natural Science Foundation of China with the titles:"The Study of Compressive Imaging Method Based on Union Dictionary Sparse Representation of Atoms and Molecules"，"The Study of Phase Retrieval and Image Reconstruction Based on Nonlinear Compressed Sensing and Adaptive Dictionary Learning"，the National Natural Science Foundation of Hebei Province with the title "Adaptive Dictionary Learning and Its Application on Image Reconstruction" |
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| 摘 要： | ![]()
文中提出了一种基于子空间解析字典学习和观测矩阵优化的图像压缩感知算法.该算法根据图像的局部方向特征,将整个图像空间分成多个子空间,并且采用几何共轭梯度算法分别在各个子空间学习解析字典,以实现对不同子空间图像块的最优稀疏表示.在图像重构过程中,首先在所有的子空间对每个图像块分别进行估计,然后根据稀疏表示最小误差准则获得每个图像块的最优估计.为了进一步提高图像重构质量,文中通过对不同子空间的图像块进行线性判别分析获得优化观测矩阵.实验表明文中算法可以实现高质量的压缩感知图像重构.
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| 关 键 词： | 稀疏表示 压缩感知 解析模型 解析字典 观测矩阵优化 |
Compressed Sensing Based on Multiple Learning Analysis Dictionaries and Optimizing Measurement Matrix |
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| LIAN Qiu-Sheng,WANG Xiao-Na,SHI Bao-Shun,CHEN Shu-Zhen. Compressed Sensing Based on Multiple Learning Analysis Dictionaries and Optimizing Measurement Matrix[J]. Chinese Journal of Computers, 2015, 38(6) |
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| Authors: | LIAN Qiu-Sheng WANG Xiao-Na SHI Bao-Shun CHEN Shu-Zhen |
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| Abstract: | ![]()
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| Keywords: | sparse representation compressed sensing analysis model analysis dictionary measurement matrix optimizing |
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