Towards automatic tree crown detection and delineation in spectral feature space using PCNN and morphological reconstruction

  • Authors:
  • Zhengrong Li;Ross Hayward;Jinglan Zhang;Yuee Liu;Rodney Walker

  • Affiliations:
  • Cooperative Research Centre for Spatial Information, Australia and Queensland University of Technology, Australia;Queensland University of Technology, Australia;Queensland University of Technology, Australia;Queensland University of Technology, Australia;Queensland University of Technology, Australia

  • Venue:
  • ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
  • Year:
  • 2009

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Abstract

The application of object-based approaches to the problem of extracting vegetation information from images requires accurate delineation of individual tree crowns. This paper presents an automated method for individual tree crown detection and delineation by applying a simplified PCNN model in spectral feature space followed by post-processing using morphological reconstruction. The algorithm was tested on high resolution multi-spectral aerial images and the results are compared with two existing image segmentation algorithms. The results demonstrate that our algorithm outperforms the other two solutions with the average accuracy of 81.8%.