| 过完备字典稀疏表示的云图超分辨率算法 |
| |
| 引用本文： | 金炜,符冉迪,叶明.过完备字典稀疏表示的云图超分辨率算法[J].遥感学报,2012,16(2):275-285. |
| |
| 作者姓名： | 金炜 符冉迪 叶明 |
| |
| 作者单位： | 宁波大学 信息科学与工程学院, 浙江 宁波 315211;宁波大学 信息科学与工程学院, 浙江 宁波 315211;宁波大学 信息科学与工程学院, 浙江 宁波 315211 |
| |
| 基金项目： | 浙江省自然科学基金(编号:Y1080778,Y1111061);浙江省公益性技术应用研究计划(编号:2010C33104);国家教育部科学技术研究重点项目(编号:209155) |
| |
| 摘 要： | 提出一种基于过完备字典稀疏表示的云图超分辨率算法。首先,联合训练针对低分辨率与高分辨率云图块的两个字典Dl和Dh,保证对应的低分辨率与高分辨率云图块关于各自的字典具有相似的稀疏表示;其次,通过求解优化问题,获得待处理云图每个低分辨率云图块关于Dl的稀疏表示,并将表示系数用于Dh以生成对应的高分辨率云图块;最后,运用最速下降算法,得到满足重构约束的高分辨率云图。红外与可见光云图的数值实验验证了本文算法的有效性,表明本文算法在视觉效果及PSNR指标上均优于插值方法。
|
| 关 键 词： | 云图 超分辨率 过完备字典 字典训练 稀疏表示 |
| 收稿时间： | 3/3/2010 12:00:00 AM |
| 修稿时间： | 5/6/2010 12:00:00 AM |
Nephogram super-resolution algorithm using over-completedictionary via sparse representatio |
| |
| JIN Wei,FU Randi and YE Ming.Nephogram super-resolution algorithm using over-completedictionary via sparse representatio[J].Journal of Remote Sensing,2012,16(2):275-285. |
| |
| Authors: | JIN Wei FU Randi and YE Ming |
| |
| Institution: | Faculty of Information Science & Technology, Ningbo University, Ningbo 315211, China;Faculty of Information Science & Technology, Ningbo University, Ningbo 315211, China;Faculty of Information Science & Technology, Ningbo University, Ningbo 315211, China |
| |
| Abstract: | Motivated by the fact that image patch can be sparse represented using a suitable over-complete dictionary, a nephogramsuper-resolution algorithm via sparse representation using over-complete dictionary is presented. During the experimenttwo dictionaries Dl and Dh for the low-resolution and high-resolution nephogram patches were trained jointly in order to guaranteethat the low-resolution and high-resolution patch pair possesses similar sparse representations as to their own dictionary.Through solving optimization problem, the sparse representation for each low-resolution nephogram patch with respect to Dl wasobtained, and the representation coefficients were applied to Dh in order to generate the corresponding high-resolution nephogrampatch. At the end of experiment the high-resolution nephogram which satisfies the reconstruction constraint was achieved by usinggradient descent algorithm. Numerical experiments for infrared and visual nephogram demonstrate the effectiveness of theproposed algorithm. Moreover, the proposed algorithm outperforms interpolation based methods in terms of visual quality andthe Peak Signal to Noise Ratio (PSNR). |
| |
| Keywords: | nephogram super-resolution over-complete dictionary dictionary training sparse representation |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《遥感学报》浏览原始摘要信息 |
| 点击此处可从《遥感学报》下载免费的PDF全文 |
|
