Optimización de Deteccion de Cambios en una Imagen Pancromáticas Basada en Analisis de una Imagen Multibanda de Indice de Cambio (Optimizing Panchromatic Image Change Detection Based on Change Index Multiband Image Analysis)

Estibaliz Martinez Izquierdo (emartinez@fi.upm.es), Agueda Arquero Hidalgo (aarquero@fi.upm.es), Iñigo Molina Sanchez (inigo.molina@upm.es)


Universidad Politécnica de Madrid
This paper appears in: Revista IEEE América Latina

Publication Date: March 2015
Volume: 13,   Issue: 3 
ISSN: 1548-0992


Abstract:
This work proposes an optimization of a semisupervised Change Detection methodology based on a combination of Change Indices (CI) derived from an image multitemporal data set. For this purpose, SPOT 5 Panchromatic images with 2.5 m spatial resolution have been used, from which three Change Indices have been calculated. Two of them are usually known indices; however the third one has been derived considering the Kullbak-Leibler divergence. Then, these three indices have been combined forming a multiband image that has been used in as input for a Support Vector Machine (SVM) classifier where four different discriminant functions have been tested in order to differentiate between change and no_change categories. The performance of the suggested procedure has been assessed applying different quality measures, reaching in each case highly satisfactory values. These results have demonstrated that the simultaneous combination of basic change indices with others more sophisticated like the Kullback-Leibler distance, and the application of non-parametric discriminant functions like those employees in the SVM method, allows solving efficiently a change detection problem.

Index Terms:
Change detection, SPOT images, Change Indices, Kullback-Leibler distance, Support Vector Machines.   


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