Change detection provides a powerful means for the initial detection of small target objects of interest. However, speckle
effects mean this type of approach can be difficult to apply to Synthetic Aperture Radar (SAR) imagery. This paper
examines methods for object detection using change between a registered pair of SAR images.
The techniques discussed are designed to detect change over small areas ranging in size from a few to perhaps a few
hundred pixels. The techniques considered include the ratio of pixels and the ratio of variances covering small regions.
The former is a straightforward approach and can provide a good performance baseline. The latter utilises the
observation that many man-made objects have a somewhat spiky scattering response, the variance tends to capture this
type of response and the ratio of variance enables comparison.
Ideally any test statistic should be characterized by a known statistical distribution such that formal tests of a null
hypothesis might be carried out. Here the null hypothesis corresponds to no change, and knowledge of the distribution of
the test statistic enables the implementation of a Constant False-Alarm Rate (CFAR) detection process. The analysis
carried out herein considers the distribution of the ratio statistics under realistic operating parameterisations for target
detection in SAR imagery. Results are presented for a registered image pair in the form of detection maps. The simple
ratio is found to be considerably more sensitive to image speckle than techniques covering small regions in the imagery.