Evaluation on Pleiades Satellite Image Fusion for Beijing Plain Afforested Area

doi:10.13466/j.cnki.lyzygl.2016.03.023

Abstract

Abstract: Eight different image fusion methods were adopted,including the CN spectrum fusion,PCA principal component transformation,Brovey transform,HCS transform,HPF high-pass filter transform,PanSharpen transformation,GS spectrum sharpening,based on a brightness control SFIM smoothing,to fuse the Pleiades satellite panchromatic and multi-spectral image of forest in Cai jiahe basin plain afforestated area,Yanqing county,Beijing.The qualitative and quantitative result of remote sensing image fusion on spectral fidelity was analyzed,and the accuracy of automatic identification forest trees in the artificial planting area using fused image was evaluated.Results show that the eight kinds of image fusion methods have their own advantages,but the HCS fusion method is simple,the remote sensing image spectral fidelity,artificial planting area of forests automatic identification precision is highest.So it is a suitable method for the Pleiades satellite images fusion to monitor forest.

Key words: remote sensing, image fusion, satellite Pleiades, plain planted land, Beijing

CLC Number:

P237
S771.8

DONG Xi, LI Cunjun, XIA Chaozong, WANG Erli, YANG Xinbing, ZHOU Jingping, HU Haitang. Evaluation on Pleiades Satellite Image Fusion for Beijing Plain Afforested Area[J]. FOREST RESOURCES WANAGEMENT, 2016, (3): 128-134.

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