Change detection in SAR imagery

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Abstract
The two major difficulties associated with SAR image change detection are addressed. These are the removal of speckle noise and the registration of information between images. The problem of image registration is severe in airborne SAR imagery due to the unpredictable nature of the aircraft track. Although inertial navigation systems may be employed to measure this motion, the accuracy obtained is insufficient to allow the creation of large rectilinear images. However, autofocus techniques are used here to measure residual aircraft motions thus allowing the production of large geometrically accurate images. The second problem of speckle reduction has been approached in two ways. The first technique applies an intensity segmentation algorithm to each image and the regions generated by this segmentation are then compared using the change detection algorithm. An alternative approach to the problem of speckle removal is to use neural network methods to learn the speckle removal and region generation task. To reduce this problem to a manageable size a factorization method for the multi-layer-perceptron has been invented.

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