Remote sensing has emerged as a powerful tool in a number of applications, but many challenges such as the development of “smart’ (knowledgeable), effective and efficient Earth observation (EO) image-content extraction and content-based image retrieval systems in response to big sensory data acquisitions by ever-increasing spaceborne EO imaging sensors remain unsolved. In this paper, we discuss the need to explicitly specify a priori 4D spatiotemporal scene domain knowledge to be mapped onto the image domain in terms of 2D image features and spatial constraints. This 4D-to-2D mapping capability implies the solution of the vision problems, where the semantic gap from sensory data to high-level information products must be filled in.
|Journal||International Conference on GIScience Short Paper Proceedings|
|Publication status||Published - 2016|
Belgiu, M., Sudmanns, M., Tiede, D., Baraldi, A., & Lang, S. (2016). Spatiotemporal enabled Content-based Image Retrieval. International Conference on GIScience Short Paper Proceedings, 1(1), 13-16. https://doi.org/10.21433/B311729295dw