Brightness inconsistency and obvious boundary affect the reconstruction results of multi-temporal remote sensing images. In order to solve the problem, an improved thick cloud removal algorithm for multi-temporal remote sensing image was proposed by combining total variation model and Poisson equation. Firstly, the brightness correction coefficient was calculated by the brightness information of the common area of multi-temporal remote sensing images in order to correct the brightness of the images, so as to reduce the effect of brightness differences on cloud removal results. Then, multi-temporal images after brightness correction were reconstructed based on selective multi-source total variation model, and the fusion results' spatial smoothnesses and their similarities with the original images were improved. Finally, the local areas of the reconstruction image were optimized by using Poisson equation. The experimental results show that this method can effectively solve the problems of brightness inconsistency and boundary.