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In CIELab color space, we propose a remote sensing image fusion technique based on nonsubsampled shearlet transform (NSST) and pulse coupled neural network (PCNN), which aim to improve the efficiency and performance of the remote sensing image fusion by combining the excellent properties of the two methods. First, panchromatic (PAN) and multispectral (MS) are transformed into CIELab color space to get different color components. Second, PAN and L component of MS are decomposed by the NSST to obtain corresponding the low-frequency coefficients and high-frequency coefficients. Third, the low-frequency coefficients are fused by intersecting cortical model (ICM); the high-frequency coefficients are divided into several sub-blocks to calculate the average gradient (AG), and the linking strength of PCNN model is determined by the AG, so that the parameters can be adaptively set according to …