Using Multiple Subpixel Shifted Images With Spatial-Spectral Information in Soft-Then-Hard Subpixel Mapping

被引:22
|
作者
Wang, Peng [1 ]
Wang, Liguo [1 ]
Mura, Mauro Dalla [2 ]
Chanussot, Jocelyn [2 ,3 ]
机构
[1] Harbin Engn Univ, Coll Informat & Commun Engn, Harbin 150001, Heilongjiang, Peoples R China
[2] Grenoble Inst Technol, Grenoble Images Parole Signals Automat Lab GIPSA, F-38402 St Martin Dheres, France
[3] Univ Iceland, Fac Elect & Comp Engn, IS-101 Reykjavik, Iceland
基金
中国国家自然科学基金;
关键词
Hyperspectral image; image interpolation; multiple subpixel shifted images (MSIs); soft-then-hard subpixel mapping (STHSPM); HOPFIELD NEURAL-NETWORK; REMOTELY-SENSED IMAGES; HYPERSPECTRAL IMAGERY; ATTRACTION MODEL; SUPERRESOLUTION; INTERPOLATION; RESOLUTION; CONSTRAINTS;
D O I
10.1109/JSTARS.2017.2713439
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
Multiple subpixel shifted images (MSIs) from the same area can be incorporated to improve the accuracy of soft-then-hard subpixel mapping (STHSPM). In this paper, a novel method that derives higher resolution MSIs with more spatial-spectral information (MSI-SS) is proposed. First, coarse MSIs produce two high-resolution MSIs for each class respectively by two paths at the same time. The spatial path produces the high-resolution MSIs by soft classification followed by interpolation. And, the other high-resolution MSIs are derived from the spectral path by interpolation followed by soft classification. Then the higher resolution MSIs with more spatial-spectral information for each class are derived by integrating the aforementioned two kinds of high-resolution MSIs by the appropriate weight. Finally, the integrated higher resolution MSIs for each class are used to allocate hard class labels to subpixels. The proposed method is fast and takes more spatial-spectral information of the original MSIs into account. Experiments on three real hyperspectral remote sensing images show that the proposed method produce higher SPM accuracy result.
引用
收藏
页码:2950 / 2959
页数:10
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