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Open Access

Tree Image Growth Analysis Using Instantaneous Phase Modulation

  • Janakiramanan Ramachandran1,
  • Marios S. Pattichis1Email author,
  • Louis A. Scuderi2 and
  • Justin S. Baba1, 3
EURASIP Journal on Advances in Signal Processing20112011:586865

https://doi.org/10.1155/2011/586865

Received: 1 July 2010

Accepted: 19 January 2011

Published: 20 February 2011

Abstract

We propose the use of Amplitude-Modulation Frequency-Modulation (AM-FM) methods for tree growth analysis. Tree growth is modeled using phase modulation. For adapting AM-FM methods to different images, we introduce the use of fast filterbank filter coefficient computation based on piecewise linear polynomials and radial frequency magnitude estimation using integer-based Savitzky-Golay filters for derivative estimation. For a wide range of images, a simple filterbank design with only 4 channel filters is used. Filterbank specification is based on two different methods. For each input image, the FM image is estimated using dominant component analysis. A tree growth model is developed to characterize and depict quarterly and half-seasonal growth of trees using instantaneous phase. Qualitative evaluation of inter- and intraring reconstruction is performed on 20 aspen images and a mixture of 12 tree images of various types. Qualitative scores indicate that the results were mostly of good to excellent quality (4.4/5.0 and 4.0/5.0 for the two databases, resp.).

Keywords

Tree GrowthMagnitude EstimationGrowth AnalysisFilter CoefficientInstantaneous Phase

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Authors’ Affiliations

(1)
Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, USA
(2)
Department of Earth and Planetary Sciences, The University of New Mexico, Albuquerque, USA
(3)
Measurement Science and Systems Engineering Division, Oak Ridge National Laboratory, Oak Ridge, USA

Copyright

© Janakiramanan Ramachandran et al. 2011

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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