The new launched ZiYuan-3 (ZY-3) satellite with multispectral (MS) bands and a panchromatic (PAN) band has presented a new opportunity to assess image fusion methods for coastal wetland mapping. This study focuses on image fusion quality assessment through both quantitative spectral and spatial quality analysis and object-oriented classification comparison. Various methods for pan-sharpening ZY-3 MS and PAN bands are tested, including generalized intensity-hue-saturation transform (GIHS), à trous wavelet transform (AWT), nonsubsampled contourlet transform (NSCT), and a combination of NSCT with GIHS (NSCT_GIHS). Spectral fidelity and spatial preservation of fused bands are compared with the original MS bands as reference, and spatial information injections of fused bands are compared with the resampled PAN band as reference. The fusion results demonstrate that, on average, the NSCT_GIHS method has the best performance on spectral fidelity and spatial preservation as well as spatial information injection. The near-infrared (NIR) band has the best spatial information injection in terms of entropy and cross-entropy indices, whereas the NIR band has the best spatial preservation in terms of entropy and structure similarity indices. The classification results show that NSCT_GIHS method also obtains the highest overall accuracy (96%) and Kappa coefficient (0.9425); this is in agreement with the quantitative analysis.