The dual-camera coded aperture snapshot spectral imager(DC-CASSI) includes the coded aperture snapshot spectral imager(CASSI) and panchromatic imager. CASSI can obtain the three-dimensional spectral image information of the target in a single coding within a single integral time, but it is difficult to achieve high-quality reconstruction of spectral image in a single coding. Therefore, the panchromatic image acquired by the panchromatic imager should be fused with it to obtain high-quality multispectral reconstruction images. Based on the imaging characteristics of DC-CASSI, a multispectral and panchromatic image fusion algorithm based on Non-subsampled Shearlets Transform (NSST) and improved Pulse Coupled Neural Network(PCNN) is proposed. The fusion experimental results show that compared with other traditional fusion algorithms, the proposed fusion algorithm can be well applied to DC-CASSI and maximum improving the spatial resolution of multispectral coded image while preserving spectral characteristics of the multispectral coded image. © 2021 SPIE.