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Change detection is an important synthetic aperture radar (SAR) application,usually used to detect changes on the ground scene measurements in differentmoments in time. Traditionally, change detection algorithm (CDA) is mainlydesigned for two synthetic aperture radar (SAR) images retrieved at differentinstants. However, more images can be used to improve the algorithmsperformance, witch emerges as a research topic on SAR change detection. Imagestack information can be treated as a data series over time and can be modeledby autoregressive (AR) models. Thus, we present some initial findings on SARchange detection based on image stack considering AR models. Applying AR modelfor each pixel position in the image stack, we obtained an estimated image ofthe ground scene which can be used as a reference image for CDA. Theexperimental results reveal that ground scene estimates by the AR models isaccurate and can be used for change detection applications.

Autoregressive Model for Multi-Pass SAR Change Detection Based on Image Stacks