Abstract: The cloud removal of remote sensing images is very important in the processing and analysis of remote sensing images and plays a crucial role in the subsequent image information extraction and other operations. Aiming at the high-quality requirements and low applicability of the reconstructed images in the cloud removal of multi-temporal remote sensing image fusion, a thick cloud removal algorithm based on one or more reference images was proposed, mainly including a selection of reference image, radiometric normalization, multi-temporal image fusion, and Poisson image editing. Firstly, the reference image was selected according to the image masking and the principal component information, and the radiometric normalization of the multi-source remote sensing image was carried out to preserve the change of ground feature information. Then, the image was fused based on the selective multi-source total variation model, and the boundary gradient discontinuity after image fusion was reduced by Poisson image editing. The experimental results show that the proposed method can effectively remove clouds from multi-source remote sensing images with thick clouds and different quality, and obtain higher image detail precision than traditional methods.