Abstract: Image fusion aims to construct images that are more appropriate and understandable for human and machine perception. In remote sensing applications, the fusion of the high-resolution panchromatic (PAN) image and the low-resolution multi-spectral (MS) image has always been a problem and has drawn much attention. In this paper, we proposed a PAN and MS image fusion algorithm based on wavelet transform. After performing a wavelet transform on both images, the PAN image's low-frequency component is fused into the MS image's low-frequency component using the edge intensity factor (EIF). Then, the high-frequency components of images are fused to obtain high-frequency features based on the maximum local standard deviation criterion (MLSTD). Finally, the high-resolution and multi-spectral fused image can be obtained by wavelet inverse transform from the fused low-frequency and high-frequency components. Examples illustrated that the fused images are well equipped with desired features, and the proposed algorithm performs better than several classics methods.

Key words: Image fusion ,  Wavelet transform ,  Edge intensity factor ,  Local standard deviation