Automatic classification of histopathological image is vital in medical image processing field, and the effective feature extraction plays an key role to realize accurate diagnosis. A feature extraction algorithm based on Product of Experts (PoE) is proposed to realize the feature representation of the histopathological image. The maximum likelihood and Monte Carlo random sampling methods are used to train PoE models corresponding to different kinds of images, and the responses of image samples in the two models are concatenated as their eigenvectors. Finally, a support vector machine (SVM) classification model is built based on the eigenvectors of the trained image samples. The experiments are carried out to classify histopathological images of healthy and inflammatory organs of kidney, lung, and spleen, which are provided by the Animal Diagnostics Lab at Pennsylvania State University. The experimental results show that the proposed algorithm can achieve high accuracy in three organ image classifications.