A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Signal Period Analysis Based on Hilbert-Huang Transform and Its Application to Texture Analysis
ICIG '04 Proceedings of the Third International Conference on Image and Graphics
Color transfer based remote sensing image fusion using non-separable wavelet frame transform
Pattern Recognition Letters
Nonseparable multidimensional perfect reconstruction filter banks and wavelet bases for Rn
IEEE Transactions on Information Theory - Part 2
Texture classification and segmentation using wavelet frames
IEEE Transactions on Image Processing
Multifocus image fusion and denoising: A variational approach
Pattern Recognition Letters
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A trous wavelet transform (AWT) and empirical mode decomposition (EMD) are two distinct methods used for analyzing nonlinear and nonstationary signals. In this paper, a combination of AWT and EMD is proposed as an improved method for fusing remote sensing images on the basis of the framework of AWT-based image fusion. The principle consists of performing a multiresolution decomposition on high resolution panchromatic image (HRPI) using AWT. The approximation component and low resolution multispectral image (LRMI) are fused through an intrinsic mode functions (IMFs) based model. Subsequently, the sharpening approximation component produced is substituted for the old one. High resolution multispectral image (HRMI) is then obtained through an inverse AWT (IAWT). QuickBird images are used to illustrate the advantage of this method over the traditional AWT and EMD based methods both visually and quantitatively.