Automated image registration with ARACHNID

Abstract

The next generation of military reconnaissance systems will generate larger images, with more bits per pixel, combined with improved spatial, spectral and temporal resolutions. This increase in the quantity of imagery requiring analysis to produce militarily useful reports, the "data deluge", will place a significant burden upon dissemination systems and upon traditional, largely manual, exploitation techniques. To avoid the possibility that imagery derived from expensive assets may go unexploited, an increased use of automated imagery exploitation tools is required to assist the Image Analysts (IAs) in their tasks.This paper describes the fully automated generation of time sequence datacubes from mixed imagery sources as cueing aids for IAs. In addition to facilitating quick and easy visual inspection, the datacubes provide the prealigned image sets needed for exploitation by some automated change detection and target detection algorithms. The ARACHNID system under development handles SAR, IR and EO imagery and will align image pairs obtained with widely differing sun, view and zenith angles. Edge enhancement pre-processing is employed to increase the similarity between images of disparate characteristics.Progress is reported on the automation of this registration task, on its current performance characteristics, its potential for integration into an operational system, and on its expected utility in this context.

Smart video surveillance for airborne platforms

“…Various image registration algorithms exist. These algorithms employ different techniques including optical flow, wavelets, 21 the Fourier transform, 26 correlation methods, 25 featurebased approaches. There are mainly four steps in the image registration process.…”