At present, many remote sensing image fusion algorithms mainly use the pixel features of independent pixels to complete the fusion of image subbands, ignoring the regional correlation of image subbands, resulting in the fusion of image discontinuity and fuzzy effects. Therefore, a remote sensing image fusion algorithm based on IHS transform coupled with adaptive region features is proposed in this paper. The IHS transform is introduced to decompose the multispectral image to obtain the intensity component, and then fuse it with the panchromatic image. The nondownsampling contourlet transform is used to decompose the PAN image and the intensity components to obtain the high and low frequency subband information. The adjustment factor of the lowfrequency subband fusion model is adaptively adjusted by using the regional energy and spatial characteristics of the image, so that the fusion subband can contain more spatial information. A highfrequency subband fusion model is constructed based on the region variance feature of the image, which makes the fusion highfrequency subband contain more texture information. Experimental results show that the proposed algorithm has better spectral and spatial characteristics than the current remote sensing image fusion algorithm.