Urban is a kind of very complex living space, and includes many and many different objects. For urban imagery, it is hardly to get a satisfied classification result utilizing any kind of single classification method. Aiming at this problem, this paper adopts a kind of classification method based on stepping masking principle using the parallel-pipeline classification and the improved FCM method. With this classification principle, it not only enhances the computation efficiency of classification, but also realizes the accurate and reasonable classification to the different kinds of urban objects. Finally this paper evaluates the precision of classification results using the confusion matrix and the Kappa coefficient separately. Analyzing from the classification effect and precision, this algorithm can satisfy the requirement of classification in different level or the thematic mapping.