In order to improve the fusion quality of remote sensing image, a remote sensing image fusion algorithm based on non-downsampling shear wave transform coupled information quantity restriction rule is proposed. Multi-Spectral(MS) images are decomposed by using Intensity-Hue-Saturation(IHS) transformation to extract the brightness (I) component of MS images. Then, based on non-downsampling shear wave transform, I component and PANchromatic(PAN) image are decomposed to obtain high and low frequency coefficients. Finally, using the mean value of low-frequency coefficients and regional energy information, the information quantity restriction rule is established, and the influence degree of different low-frequency coefficients on fusion coefficients is analyzed. Different fusion methods are designed to fuse these low-frequency coefficients. The improved average gradient measurement model is adopted to finish the fusion of high frequency coefficients. The fused high and low frequency coefficients are computed by the inverse transformation of Non-Subsampled Shearlet Transform(NSST), and new brightness components are output. The fused remote sensing images are formed by combining them with the original Hue and Saturation components through the inverse transformation of IHS. The experimental results show that compared with the existing fusion scheme, the fusion image of the proposed algorithm contains more information and less spectral distortion.