In computer vision all of the existing researches are interested in synthetic images features extraction. Theses images contain many types of features. Indeed, the features are classified in 1D feature (step, roof…) and 2D features (corners). Nevertheless, some approaches interest in the study of real images. Moreover, the satellite images are one most complex real image. It presents a widespread real application (weather, military…). Accordingly, many researches are developed in this way. The satellite images present a great variety of features due to the trouble what returns their treatment is little delicate. In this paper, we introduce a new application of phase congruency model for features extraction in satellite images. The aim of this paper is to exploit the advantages and the limitations of this model applied in satellite images features extraction. On the other hand, two smoothing algorithms are used to improve the features extraction procedure.

Satellite images, phase congruency model, smoothing algorithm