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17 March 2008Advances in image registration and fusion
Many image fusion systems involving passive sensors require the accurate registration of the sensor data prior to
performing fusion. Since depth information is not readily available in such systems, all registration algorithms are
intrinsically approximations based upon various assumption about the depth field. Although often overlooked, many
registration algorithms can break down in certain situations and this may adversely affect the image fusion performance.
In this paper, we discuss a framework for quantifying the accuracy and robustness of image registration algorithms
which allows a more precise understanding of their shortcomings. In addition, some novel algorithms have been
investigated that overcome some of these limitations. A second aspect of this work has considered the treatment of
images from multiple sensors whose angular and spatial separation is large and where conventional registration
algorithms break down (typically greater than a few degrees of separation). A range of novel approaches is reported
which exploit the use of parallax to estimate depth information and reconstruct a geometrical model of the scene. The
imagery can then be combined with this geometrical model to render a variety of useful representations of the data.
These techniques (which we term Volume Registration) show great promise as a means of gathering and presenting 3D
and 4D scene information for both military and civilian applications.
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Christopher Steer, Jeremy Rogers, Moira Smith, Jamie Heather, Mark Bernhardt, Duncan Hickman, "Advances in image registration and fusion," Proc. SPIE 6974, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2008, 697404 (17 March 2008); https://doi.org/10.1117/12.777070