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Topologically-Guided Color Image Enhancement
lib:e0fcae2a479a8522 (v1.0.0)
Authors: Junyi Tu,Paul Rosen
ArXiv: 1909.01456
Document: PDF DOI
Abstract URL: https://arxiv.org/abs/1909.01456v1
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.
ArXiv: 1909.01456
Document: PDF DOI
Abstract URL: https://arxiv.org/abs/1909.01456v1
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.
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