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A new image registration scheme based on curvature scale space curve matching

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Abstract

We propose a new image registration scheme for remote sensing images. This scheme includes three steps in sequence. First, a segmentation process is performed on the input image pair. Then the boundaries of the segmented regions in two images are extracted and matched. These matched regions are called confidence regions. Finally, a non-linear optimization is performed in the matched regions only to obtain a global set of transform parameters. Experiments show that this scheme is more robust and converges faster than registration of the original image pair. We also develop a new curve-matching algorithm based on curvature scale space to facilitate the second step.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Prism, Arizona State University, 878609, Tempe, AZ, 85287-9909, USA

    Ming Cui & Peter Wonka

  2. I3DEA, Arizona State University at Polytechnic Campus, 7001 E. Williams Field Rd. Bldg. 140, Mesa, AZ, 85212, USA

    Anshuman Razdan & Jiuxiang Hu

Authors
  1. Ming Cui
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  2. Peter Wonka
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  3. Anshuman Razdan
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  4. Jiuxiang Hu
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Correspondence to Ming Cui.

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Cui, M., Wonka, P., Razdan, A. et al. A new image registration scheme based on curvature scale space curve matching. Visual Comput 23, 607–618 (2007). https://doi.org/10.1007/s00371-007-0164-1

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