A remote sensing image change detection method of multi-temporal binary change detection based on image transformation (BIT) is proposed to address issues related to seasonal and radiometric variations (color discrepancies) between remotely sensed images acquired at different times but from the same geographic area. This method incorporates remote sensing images from multiple past time points and combines the results of pairwise change detection between the current image and the past temporal images to obtain a stable change detection outcome. This method helps mitigate false alarms caused by seasonal and radiometric variations, thereby enhancing the accuracy of change detection. Multiple remote sensing images from different time points in the past are utilized to eliminate the influence of non-target building changes. The pixel difference value of change points is introduced as a regularization term in the loss function, further improving the robustness and reliability of change detection. In this study, a three-temporal (three images from different time points) example is provided, and experiments are conducted with a remote sensing image dataset of building changes. The experimental results demonstrate that the multi-temporal BIT method outperforms change detection methods that only consider two temporal images in the task of remote sensing image change detection.