Tissue image interpolation based on fractional Brownian motion.

Ching Lin Li, Wen Hung Ting, Kuo Shang Cheng

Research output: Contribution to journalArticlepeer-review

Abstract

Fractal Brownian Motion (fBm) has been proven in a viewpoint of irregularity characterization for quantifying the structure of the tissue images. Breast masses were selected as the target sample because breast-associated diseases have become prevalent in Taiwan. In this paper, the ability of fractal dimension in fractal interpolation schemes is investigated and compared with the traditional interpolation schemes including bilinear and bicubic methods. Using three image quality indices the difference between original and interpolated images may have evaluated. Interpolated images by fractal interpolation can maintain fractal characteristics better than traditional interpolation methods. Fractal features can be preserved in the interpolated images. Thus, interpolated tissue images based on fBm model are superior to conventional methods.

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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