Content-Based Expansion for Image Matching

Yalin Xiong
tech. report CMU-RI-TR-96-26, Robotics Institute, Carnegie Mellon University, June, 1996


Download
  • Adobe portable document format (pdf) (929KB)
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract
This paper challenges the two popular approaches used in image matching: the gradient approach and the phase approach. We demonstrate from both theoretical and experimental points of view that the gradient approach has large model-incurred errors when the images contain significant high frequency information, and the phase approach has the same kind of errors when the images contain mainly low frequency information. Both are due to inappropriate signal expansion models. Based on such a unified perspective on those approaches, we propose a content-based expansion scheme, in which the exact form of the signal expansion depends on the content of band-passed signals. We show that such a scheme eliminates the risk of large model-incurred errors. Finally, we implement the content-based approach based on FFT (Fast Fourier Transform) and compare it with both gradient and phase approaches in performance.

Notes
Grant ID: NAGW-1175
Number of pages: 30

Text Reference
Yalin Xiong, "Content-Based Expansion for Image Matching," tech. report CMU-RI-TR-96-26, Robotics Institute, Carnegie Mellon University, June, 1996

BibTeX Reference
@techreport{Xiong_1996_418,
   author = "Yalin Xiong",
   title = "Content-Based Expansion for Image Matching",
   booktitle = "",
   institution = "Robotics Institute",
   month = "June",
   year = "1996",
   number= "CMU-RI-TR-96-26",
   address= "Pittsburgh, PA",
}