The curvature driven diffusion (CDD) inpainting algorithm requires a significant number of iterations and long time for repairing images. In addition, this algorithm cannot repair the damaged points in the image boundary. Herein, an algorithm based on corrosion treatment and multi-parameter factors is proposed to address the limitations of the CDD inpainting algorithm. The main steps of the algorithm can be given as follows. First, the image mask to be repaired is corroded to eliminate the wastage of time because of an oversized mask. Second, a natural logarithmic exponential factor and a linear exponential factor are introduced in the curvature and gradient modulus calculations, respectively. Further, the effect of unreasonable gradient modulus and curvature values on the diffusion rate can be avoided by adjusting the parameters of different exponential factors. In addition, a self-adaptive positive lifting parameter that varies with the number of iterations is introduced to calculate the curvature and gradient modulus, improving the repair of the damaged area. Finally, the corresponding boundary treatment conditions are adopted according to the boundary locations of the images with broken boundaries, avoiding the problem that a broken boundary cannot be repaired. The simulation results demonstrate that the improved CDD inpainting algorithm improves the repairing speed and that images with broken boundaries can also be repaired.