The invention discloses a method for the classification of natural scene images on the basis of regional potential semantic feature, aiming at carrying out the classification of the natural scene images by utilizing the regional potential semantic information of the images and the distribution rule of the information in space. The technical proposal comprises the following steps: firstly, a representative collection of the classification of the natural scene images is established; secondly, sampling point SIFT feature extraction is carried out to the images in the representative collection of the classification of the natural scene images to generate a general visual word list; thirdly, the regional potential semantic model of an image is produced on the representative collection of the classification of the natural scene images; fourthly, the extraction of the regional potential semantic feature of the image is carried out to any image; finally, a natural scene classification model is generate, and classification is carried out to the regional potential semantic feature of the image according to the natural scene classification model. The method inducts the regional potential semantic feature, thus not only describing the regional information of image sub-blocks, but also including the distribution information of the image sub-blocks in space; compared with other methods, the method of the invention can obtain higher accuracy, and no manual labeling is needed, thus having high degree of automation.