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

  • Authors:

  • Ming Cui;Peter Wonka;Anshuman Razdan;Jiuxiang Hu

  • Affiliations:

  • Arizona State University, Department of Computer Science and Engineering, Prism, 878609, 85287-9909, Tempe, AZ, USA;Arizona State University, Department of Computer Science and Engineering, Prism, 878609, 85287-9909, Tempe, AZ, USA;Arizona State University at Polytechnic Campus, I3DEA, 878609, 7001 E. Williams Field Rd. Bldg. 140, 85212, Mesa, AZ, USA;Arizona State University at Polytechnic Campus, I3DEA, 878609, 7001 E. Williams Field Rd. Bldg. 140, 85212, Mesa, AZ, USA

  • Venue:
  • The Visual Computer: International Journal of Computer Graphics
  • Year:
  • 2007

Quantified Score

Hi-index 0.07

Visualization

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.