Full-Text Search:
Home|About CNKI|User Service|中文
Add to Favorite Get Latest Update

A Method on Remote Sensing Image Fusion based on à trous Wavelet Transform and Joint Sparse Representation

Xiao Xinyao;Xu Ning;You Hongjian;Key Laboratory of Technology in Geo-spatial Information Processing and Application System,IECAS;Institute of Electronics,Chinese Academy of Sciences;University of Chinese Academy of Sciences;  
Sparse representation using the trained dictionary can reflect the inherent characteristics and structure of signals.A novel fusion method based on theàtrous wavelet transform and joint sparse representation for multi-spectral image and panchromatic image is proposed,aiming to solve the spectral distortion.Firstly,the IHS transform is applied to multi-spectral image.Then,the panchromatic image and the intensity components of multi-spectral image are decomposed byàtrous wavelet transform.The trained dictionary is learned from their low components.By exploiting joint sparse representation model on their low frequency components,common component and innovation component can be obtained.The finally result is obtained by fusing the sparse coefficients.Experimental results on urban area and mountainous area from IKONOS satellite indicate that the fused image has higher spatial resolution and great spectral fidelity.And the proposed method outperforms traditional methods by visual analysis and quantitative evaluation.
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©CNKI All Rights Reserved