NDLI: Fusion of remote sensing images based on Principal Component Analysis and Nonsubsampled Contourlet Transform

Content Provider	IEEE Xplore Digital Library
Author	Hailiang Shi Peixu Xing
Copyright Year	2010
Description	Author affiliation: Dept. of Math. & Info. Sci., Zhengzhou Univ. of Light Industry, 450002, China (Hailiang Shi; Peixu Xing)
Abstract	A novel fusion method is proposed for multispectral (MS) and panchromatic (PAN) satellite images using Principal Component Analysis (PCA) and Nonsubsampled Contourlet Transform (NSCT). This method first performs PCA on MS, and NSCT on PAN and the first principal component $(PC^{1})$ to get corresponding low-frequency and high-frequency coefficients, then fuses the approximation coefficients using PCA again for the tradeoff between the spectral and spatial information, and fuses the subbands coefficients based on Universal Image Qualigy Index (UIQI) and local sobel gradient for the spatial detail information, finally a fused image is formed through inverse NSCT and inverse PCA. Experimental results show that the proposed fusion method can effectively preserve spectral information while improving the spatial quality, and outperforms the general IHS-, PCA-, wavelet-, contourlet-based fusion methods.
File Size	932488
File Format	PDF
ISBN	9781424472352
e-ISBN	9781424472376
DOI	10.1109/ICCASM.2010.5622672
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-22
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Gallium Image resolution PSNR Nsct Computed tomography Local Sobel gradient UIQI Erbium Image fusion Principal component analysis Pca
Content Type	Text
Resource Type	Article

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