Abstract | ||
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In this paper, we present a novel spatial and spectral fusion model (SASFM) that uses sparse matrix factorization to fuse remote sensing imagery with different spatial and spectral properties. By combining the spectral information from sensors with low spatial resolution (LSaR) but high spectral resolution (HSeR) (hereafter called HSeR sensors), with the spatial information from sensors with high spatial resolution (HSaR) but low spectral resolution (LSeR) (hereafter called HSaR sensors), the SASFM can generate synthetic remote sensing data with both HSaR and HSeR. Given two reasonable assumptions, the proposed model can integrate the LSaR and HSaR data via two stages. In the first stage, the model learns from the LSaR data a spectral dictionary containing pure signatures, and in the second stage, the desired HSaR and HSeR data are predicted using the learned spectral dictionary and the known HSaR data. The SASFM is tested with both simulated data and actual Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) acquisitions, and it is also compared to other representative algorithms. The experimental results demonstrate that the SASFM outperforms other algorithms in generating fused imagery with both the well-preserved spectral properties of MODIS and the spatial properties of ETM+. Generated imagery with simultaneous HSaR and HSeR opens new avenues for applications of MODIS and ETM+. |
Year | DOI | Venue |
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2014 | 10.1109/TGRS.2013.2253612 | IEEE T. Geoscience and Remote Sensing |
Keywords | Field | DocType |
geophysical techniques,modis acquisition,remote sensing,high spectral resolution (hser),spectral information,spatial and spectral fusion model (sasfm),image fusion,spatial-spectral fusion,lsar data,landsat 7 enhanced thematic mapper plus,moderate resolution imaging spectroradiometer (modis),spatial resolution,spectral image fusion,spatial property,spatial–spectral fusion,high spatial resolution (hsar),sparse coding,terra moderate resolution imaging spectroradiometer,sparse matrix factorization,spectral fusion model,remote sensing imagery,hsar data,geophysical image processing,spatial image fusion,matrix factorization,spatial fusion model,etm+ acquisition,landsat,spectral property,spectral resolution,synthetic remote sensing data | Spatial analysis,Computer vision,Thematic Mapper,Sparse matrix factorization,Moderate-resolution imaging spectroradiometer,Image fusion,Remote sensing,Spectral resolution,Artificial intelligence,Fuse (electrical),Image resolution,Mathematics | Journal |
Volume | Issue | ISSN |
52 | 3 | 0196-2892 |
Citations | PageRank | References |
12 | 0.66 | 0 |
Authors | ||
5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Bo Huang | 1 | 386 | 35.68 |
Huihui Song | 2 | 857 | 32.04 |
Hengbin Cui | 3 | 12 | 0.66 |
Ji-Gen Peng | 4 | 418 | 50.45 |
Zongben Xu | 5 | 3203 | 198.88 |