Focus-and-Context Skeleton-based Image Simplification using Saliency Maps

Publication date

2021

Authors

Wang, JieyingORCID 0000-0002-0085-3551

Editors

Farinella, Giovanni Maria
Radeva, Petia
Braz, Jose
Bouatouch, Kadi

Advisors

Supervisors

Document Type

Part of book
Open Access logo

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