Neural Style Transfer for Remote Sensing

• URL: http://arxiv.org/abs/2007.15920v1
• Date: Fri, 31 Jul 2020 09:30:48 GMT
• Title: Neural Style Transfer for Remote Sensing
• Authors: Maria Karatzoglidi, Georgios Felekis and Eleni Charou
• Abstract summary: The purpose of this study is to present a method for creating artistic maps from satellite images, based on the NST algorithm. This method includes three basic steps (i.e. application of semantic image segmentation on the original satellite image, dividing its content into classes, application of neural style transfer for each class and creation of a collage)
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The well-known technique outlined in the paper of Leon A. Gatys et al., A Neural Algorithm of Artistic Style, has become a trending topic both in academic literature and industrial applications. Neural Style Transfer (NST) constitutes an essential tool for a wide range of applications, such as artistic stylization of 2D images, user-assisted creation tools and production tools for entertainment applications. The purpose of this study is to present a method for creating artistic maps from satellite images, based on the NST algorithm. This method includes three basic steps (i) application of semantic image segmentation on the original satellite image, dividing its content into classes (i.e. land, water), (ii) application of neural style transfer for each class and (iii) creation of a collage, i.e. an artistic image consisting of a combination of the two stylized image generated on the previous step.

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