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17 March 2008 Advances in image registration and fusion
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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, and Duncan Hickman "Advances in image registration and fusion", Proc. SPIE 6974, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2008, 697404 (17 March 2008);


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