AUTOMATED IMAGE REGISTRATION USING GEOMETRICALLY INVARIANT PARAMETER SPACE CLUSTERING (GIPSC)
Gamal H. Seedahmed, Louis M. Martucci · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2002
Accurate, robust, and automatic image registration is a critical ta sk in many typical applications that employ multi-sensor and /or multi-date imagery information. In this paper we present a new a pproach to automatic image registration, which obviates the nee d for feature matching and solves for the registration parameters in a Hough-like approach. The basic idea underpinning GIPSC methodology is to pair each data element belonging to two overlapping images, with all other data in each image, through a mathematical transformation. The results of pairing are encoded and exploited in histogram-like arrays as clusters of votes. Geometrically invariant features are adopted in this approach to reduce the computational complexity generated by the high dimensionality of the mathematical transformation. In this way, the problem of image registration is characterized, not by spat ial or radiometric properties, but by the mathematical transformation that describes the geometrical relationship between the two imag es or more. While this approach does not require feature matching, it does permit recovery of matched features (e.g., points) as a us eful by-product. The developed methodology incorporates uncertainty modeling using a least squares solution. Su ccessful and promising experimental results of multi-date automatic image registration are reported in this paper.