Open Access
Peer-Reviewed
Original Research
On the Restoration of Semantic Features in Raster Topographic Images
Abstract
Raster topographic images consist of a set of layers depicted in arbitrary color. There exist strong correspondence between the color of the layer and its semantic meaning. Often there is a need to separate or extract semantic layers from the map. The separation results in severe artifacts in places where semantic layers would overlap (e.g. elevations lines drawn on top of the topographic map). In the current work, we design the technique to reconstruct the sema ntic layers from the color layers resulting from the image separation process. The proposed technique pr ovides good visual quality of the reconstructed image layers, and can therefore be applied for se lective layer removal/extraction, which is often necessary in map processing and analyzing applications. It improves the accuracy of the data analysis and measurement tasks. The technique requires few co mputation resources and can be successfully used in mobile computers and terminals.
Keywords
Topographic images
semantic
restoration
morphology.
Declarations & Ethics
Funding:
This research received academic dissemination support through ESCAP / JournalsHub publishing programs.
Conflicts of Interest:
The authors declare no competing financial or institutional interests.
Peer Review:
Double-blind peer reviewed by international subject specialists.
License:
Creative Commons Attribution 4.0 International (CC BY 4.0).
How to Cite This Article
APA / MLA / BibTeX
Ageenko, et al. (2006). On the Restoration of Semantic Features in Raster Topographic Images. IADIS International Journal on Computer Science and Information Systems, 1(1). https://doi.org/10.33965/ijcsis_2006_v1i1_09
Ageenko, et al. "On the Restoration of Semantic Features in Raster Topographic Images." IADIS International Journal on Computer Science and Information Systems, vol. 1, no. 1, 2006. https://doi.org/10.33965/ijcsis_2006_v1i1_09
Ageenko, et al. "On the Restoration of Semantic Features in Raster Topographic Images." IADIS International Journal on Computer Science and Information Systems 1, no. 1 (2006). https://doi.org/10.33965/ijcsis_2006_v1i1_09