SPARSE REPRESENTATION BASED PAN-SHARPENING

被引:0
作者
Yin, Wen [1 ]
Li, Yuanxiang [1 ]
Yu, Wenxian [1 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Aeronaut & Astronaut, Shanghai 200240, Peoples R China
来源
2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2013年
关键词
remote sensing; image fusion; sparse representation; component substitution;
D O I
10.1109/IGARSS.2013.6721295
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we propose a novel pan-sharpening method which combines classical component substitution with recently developed sparse representation. We explore the sparse representations of multispectral and panchromatic images through two dictionaries which are trained to have the same sparse representations for each high-resolution and low-resolution image patch pair. The merging procedure is implemented in sparse domain. In order to avoid spectral distortion, partial replacement is used to extract details. At the same time, the introducing of dictionary pair also reduces the distortion caused by interpolating the MS at the initialization of the fusion process. As inherent characteristics and structure of signals are reflected better via sparse representation, the proposed method can well preserve spectral and spatial details of the source images. Experimental results on IKONOS and Quickbird images demonstrate our method's superiority in both the spatial resolution improvement and the spectral information preservation.
引用
收藏
页码:860 / 863
页数:4
相关论文
共 50 条
[31]   A NEW VARIATIONAL METHOD FOR PAN-SHARPENING [J].
Liu, Pengfei ;
Xiao, Liang ;
Tang, Songze .
2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2015, :597-600
[32]   ON THE EFFECTS OF PAN-SHARPENING TO TARGET DETECTION [J].
Garzelli, Andrea ;
Capobianco, Luca ;
Nencini, Filippo .
2009 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-5, 2009, :387-+
[33]   Application of pan-sharpening to SIMS imaging [J].
Tarolli, Jay ;
Tian, Hua ;
Winograd, Nicholas .
SURFACE AND INTERFACE ANALYSIS, 2014, 46 :217-220
[34]   Image Degradation for Quality Assessment of Pan-Sharpening Methods [J].
Dou, Wen .
REMOTE SENSING, 2018, 10 (01)
[35]   Pan-sharpening via conditional invertible neural network [J].
Wang, Jiaming ;
Lu, Tao ;
Huang, Xiao ;
Zhang, Ruiqian ;
Feng, Xiaoxiao .
INFORMATION FUSION, 2024, 101
[36]   An Adaptive IHS Pan-Sharpening Method [J].
Rahmani, Sheida ;
Strait, Melissa ;
Merkurjev, Daria ;
Moeller, Michael ;
Wittman, Todd .
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2010, 7 (04) :746-750
[37]   QUALITY ASSESSMENT OF PAN-SHARPENING METHODS [J].
Palubinskas, Gintautas .
2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2014, :2526-2529
[38]   A Comparative Study on Pan-Sharpening Algorithms [J].
Abu Alhin, Khaldoun ;
Niemeyer, Irmgard .
IMAGIN [E,G] EUROPE, 2010, :1-9
[39]   Pan-sharpening via the contourlet transform [J].
Shah, Vijay P. ;
Younan, Nicolas H. ;
Kin, Roger .
IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET, 2007, :310-+
[40]   A Dual-Path Fusion Network for Pan-Sharpening [J].
Wang, Jiaming ;
Shao, Zhenfeng ;
Huang, Xiao ;
Lu, Tao ;
Zhang, Ruiqian .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2022, 60