An adaptive multiplicative decomposition of non stationary multi-temporal satellite images: Application to urban changes detection

Ali Ben Abbes (1, 2) , Houcine Essid (1) , Imed Riadh Farah (1, 3) , Vincent Barra (2)

1 ENSI - École Nationale des Sciences de l'Informatique [Manouba]
2 LIMOS - Laboratoire d'Informatique, de Modélisation et d'optimisation des Systèmes
3 ITI - Département Image et Traitement Information

Nowadays, the process of change detection is regarded as an outstanding way for urban planning and design. The major concern of this paper is to investigate the nonstationary character of multi-temporal time series. To overcome this problem, we propose an adaptive multiplicative decomposition of non-stationary multi-temporal satellite image, which allows to decompose the series into three components: trend, seasonal and random, to properly model the evolution of land cover. We carried several experiments to validate our approach based on Landsat images covering the region of "Tres Cantos-Madrid" in Spain. The obtained results show the effectiveness of our proposed method comparing to some conventional methods.

Domaines: Traitement du signal et de l'image [eess.SP]

Ali Ben Abbes, Houcine Essid, Imed Riadh Farah, Vincent Barra. An adaptive multiplicative decomposition of non stationary multi-temporal satellite images: Application to urban changes detection. IPAS 2014 : First International Image Processing, Applications and Systems Conference, Nov 2014, Hammamet, Tunisia. pp.1 - 7, ⟨10.1109/IPAS.2014.7043314⟩. ⟨hal-01204960⟩