Optimal Computation of 3-D Similarity from Space Data with Inhomogeneous Noise Distributions

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Author(s)

Abstract

We optimally estimate the similarity (rotation, translation, and scale change) between two sets of 3-D data in the presence of inhomogeneous and anisotropic noise. Adopting the Lie algebra representation of the 3-D rotational change, we derive the Levenberg-Marquardt procedure for simultaneously optimizing the rotation, the translation, and the scale change. We test the performance of our method using simulated stereo data and real GPS geodetic sensing data. We conclude that the conventional method assuming homogeneous and isotropic noise is insufficient and that our simultaneous optimization scheme can produce an accurate solution.

Journal

  • Memoirs of the Faculty of Engineering, Okayama University

    Memoirs of the Faculty of Engineering, Okayama University (46), 1-9, 2012-01

    Faculty of Engineering, Okayama University

Codes

  • NII Article ID (NAID)
    80022451620
  • NII NACSIS-CAT ID (NCID)
    AA12014085
  • Text Lang
    ENG
  • Article Type
    departmental bulletin paper
  • ISSN
    1349-6115
  • Data Source
    IR 
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