The mutual information based visual servo uses the global information of the image to realize servo control, which avoids the extraction, matching and tracking of traditional geometric features, and is robust to light changes and partial occlusion. However, due to the high nonlinearity of its cost function, this method has the disadvantage of small convergence region. A mutual information visual servo method based on principal component analysis (PCA) for dimension-reduced image reconstruction is proposed, which effectively decreases the nonlinearity of the cost function. The convergence region size and convergence speed of mutual information visual servo based on PCA reconstructed image and original image were compared through experiments, and the influence of the number of principal components in PCA is considered. The results show that the mutual information visual servo based on PCA reconstruction image effectively expands the convergence region of mutual information visual servo and has faster convergence speed.