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Image registration using the epipolar constraint
Describes an algorithm for the automated registration of remotely-sensed imagery. The algorithm registers 6000/spl times/6000-pixel images to the subpixel level in less than 15 minutes on a RISC System/6000/sup TM/ workstation. The paper shows that the registration function for parallel projections is of the form F(x,y)=A(x,y)+h(x,y)e, where A(x,y) is an affine transformation, h(x,y) is a function that depends on the topographic heights, and e is a vector that defines the epipolar lines. The least squares estimate of the parameters of this function can be derived from a set of image match points. The search for additional match points is then a one-dimensional search along the epipolar lines, which greatly increases the speed and accuracy of the registration.<>
Image registration using the epipolar constraint
Describes an algorithm for the automated registration of remotely-sensed imagery. The algorithm registers 6000/spl times/6000-pixel images to the subpixel level in less than 15 minutes on a RISC System/6000/sup TM/ workstation. The paper shows that the registration function for parallel projections is of the form F(x,y)=A(x,y)+h(x,y)e, where A(x,y) is an affine transformation, h(x,y) is a function that depends on the topographic heights, and e is a vector that defines the epipolar lines. The least squares estimate of the parameters of this function can be derived from a set of image match points. The search for additional match points is then a one-dimensional search along the epipolar lines, which greatly increases the speed and accuracy of the registration.<>
Image registration using the epipolar constraint
Pritt, M.D. (author)
1993-01-01
236478 byte
Conference paper
Electronic Resource
English
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