| 基于双树小波通用隐马尔可夫树模型的图像压缩感知 |
| |
| 引用本文： | 练秋生, 王艳. 基于双树小波通用隐马尔可夫树模型的图像压缩感知[J]. 电子与信息学报, 2010, 32(10): 2301-2306. doi: 10.3724/SP.J.1146.2009.01153 |
| |
| 作者姓名： | 练秋生 王艳 |
| |
| 作者单位： | 燕山大学信息科学与工程学院,秦皇岛,066004;燕山大学信息科学与工程学院,秦皇岛,066004 |
| |
| 基金项目： | 国家自然科学基金，河北省自然科学基金(F2010001294)资助课题 |
| |
| 摘 要： | 标准压缩感知图像重构仅利用图像小波系数具有稀疏性的先验知识，未能利用小波系数的结构分布特性。利用基于模型压缩感知重构思想，将能有效描述图像小波系数分布特性的隐马尔可夫树(HMT)模型引入到图像的压缩感知重构。经过理论推导，将基于HMT模型的重构转化为型如标准图像压缩感知重构的优化问题，并提出基于贝叶斯优化的凸集交替投影法进行求解。为进一步提高重构质量和速度，引入了双树小波域通用HMT (uHMT)模型及改进的uHMT (iuHMT)模型代替小波域HMT模型。实验结果表明，基于双树小波域iuHMT模型的重构图像的平均峰值信噪比(PSNR)比uHMT模型高0.97 dB.
|
| 关 键 词： | 压缩感知 模型压缩感知 双树小波 uHMT模型 凸集交替投影 |
| 收稿时间： | 2009-09-01 |
| 修稿时间： | 2010-05-13 |
Image Compressed Sensing Based on Universal HMT of the Dual-tree Wavelets |
| |
| Lian Qiu-Sheng, Wang Yan. Image Compressed Sensing Based on Universal HMT of the Dual-tree Wavelets[J]. Journal of Electronics & Information Technology, 2010, 32(10): 2301-2306. doi: 10.3724/SP.J.1146.2009.01153 |
| |
| Authors: | Lian Qiu-sheng Wang Yan |
| |
| Affiliation: | Institute of information science and technology, Yanshan University, Qinhuangdao 066004, China |
| |
| Abstract: | The standard Compressed Sensing(CS) reconstructions of image exploit simply the sparse priors of the wavelet coefficients,ignoring the structural information of the wavelet coefficients.In this paper,the Hidden Markov Tree(HMT ) model is integrated in the compressed sensing,which has been found successful in capturing the key features of the joint probability density of the wavelet coefficients of real-world image.An optimization issue which is similar to the standard compressed sensing is derived from the ... |
| |
| Keywords: | Compressed Sensing (CS) Model-based CS Dual-tree wavelet uHMT model Alternating convex projection |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《电子与信息学报》浏览原始摘要信息 |
|
点击此处可从《电子与信息学报》下载全文 |
