Focus-and-Context Skeleton-based Image Simplification using Saliency Maps
Publication date
2021
Editors
Farinella, Giovanni Maria
Radeva, Petia
Braz, Jose
Bouatouch, Kadi
Advisors
Supervisors
Document Type
Part of book
Metadata
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License
cc_by_nc_nd
Abstract
Medial descriptors offer a promising way for representing, simplifying, manipulating, and compressing images. However, to date, these have been applied in a global manner that is oblivious to salient features. In this paper, we adapt medial descriptors to use the information provided by saliency maps to selectively simplify and encode an image while preserving its salient regions. This allows us to improve the trade-off between compression ratio and image quality as compared to the standard dense-skeleton method while keeping perceptually salient features, in a focus-and-context manner. We show how our method can be combined with JPEG to increase overall compression rates at the cost of a slightly lower image quality. We demonstrate our method on a benchmark composed of a broad set of images.
Keywords
Dense Skeleton, Image Simplification, Medial Axis, Saliency Map, Computer Graphics and Computer-Aided Design, Computer Science Applications, Computer Vision and Pattern Recognition
Citation
Wang, J 2021, Focus-and-Context Skeleton-based Image Simplification using Saliency Maps. in G M Farinella, P Radeva, J Braz & K Bouatouch (eds), Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,. vol. 4, INSTICC, pp. 45-55, 16th International Conference on Computer Graphics Theory and Applications, 8/02/21. https://doi.org/10.5220/0010193400450055, conference