Topologically-Guided Image Enhancement

Enhancement is an important step in post-processing digital images for personal use, in medical imaging, and for object recognition. Most existing manual techniques rely on region selection, similarity, and/or thresholding for editing, never really considering the topological structure of the image. In this paper, we leverage the contour tree to extract a hierarchical representation of the topology of an image. We propose 4 topology-aware transfer functions for editing features of the image using local topological properties, instead of global image properties. Finally, we evaluate our approach with grayscale and color images.

Junyi Tu, and Paul Rosen. Topologically-Guided Image Enhancement. International Symposium on Visual Computing, 2019.

@article{tu2019topologically,
  title = {Topologically-Guided Image Enhancement},
  author = {Tu, Junyi and Rosen, Paul},
  journal = {International Symposium on Visual Computing},
  year = {2019},
  abstract = {Enhancement is an important step in post-processing digital images for
    personal use, in medical imaging, and for object recognition. Most existing manual
    techniques rely on region selection, similarity, and/or thresholding for editing, never
    really considering the topological structure of the image. In this paper, we leverage
    the contour tree to extract a hierarchical representation of the topology of an image.
    We propose 4 topology-aware transfer functions for editing features of the image using
    local topological properties, instead of global image properties. Finally, we evaluate
    our approach with grayscale and color images.}
}