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3D image interpolation based on anisotropic diffusion of feature point correspondence
Author(s) -
Sang Qiang,
Zhang JianZhou
Publication year - 2013
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.22069
Subject(s) - bilinear interpolation , interpolation (computer graphics) , anisotropic diffusion , feature (linguistics) , feature vector , computer science , anisotropy , point (geometry) , artificial intelligence , multivariate interpolation , algorithm , pattern recognition (psychology) , mathematics , computer vision , image (mathematics) , geometry , physics , optics , linguistics , philosophy
ABSTRACT An automatic method has been developed to interpolate between neighboring slices in a gray‐scale data set by anisotropic diffusion of feature point correspondence. The feature point extracted is registered to form the feature vector. Thus a three dimensional (3D) weight anisotropic vector diffusion is introduced to spread the feature vector to the correspondence vector, which estimates spatial correspondence between adjacent slices. Bilinear interpolation is made along the direction of correspondence vector. Experiments are performed on medical data sets to evaluate the proposed method, showing that the new algorithm achieves good quality and improvement in efficiency relative to the traditional methods. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 338–345, 2013