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International Journal of Biomedical Imaging
Volume 2012, Article ID 958142, 8 pages
Research Article

Selective Extraction of Entangled Textures via Adaptive PDE Transform

1Department of Mathematics, Michigan State University, East Lansing, MI 48824, USA
2Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA

Received 29 August 2011; Accepted 11 October 2011

Academic Editor: Shan Zhao

Copyright © 2012 Yang Wang et al. 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.


Texture and feature extraction is an important research area with a wide range of applications in science and technology. Selective extraction of entangled textures is a challenging task due to spatial entanglement, orientation mixing, and high-frequency overlapping. The partial differential equation (PDE) transform is an efficient method for functional mode decomposition. The present work introduces adaptive PDE transform algorithm to appropriately threshold the statistical variance of the local variation of functional modes. The proposed adaptive PDE transform is applied to the selective extraction of entangled textures. Successful separations of human face, clothes, background, natural landscape, text, forest, camouflaged sniper and neuron skeletons have validated the proposed method.