Volume XLI-B3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 899-903, 2016
https://doi.org/10.5194/isprs-archives-XLI-B3-899-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 899-903, 2016
https://doi.org/10.5194/isprs-archives-XLI-B3-899-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  10 Jun 2016

10 Jun 2016

SEARCHING REMOTELY SENSED IMAGES FOR MEANINGFUL NESTED GESTALTEN

E. Michaelsen, D. Muench, and M. Arens E. Michaelsen et al.
  • Fraunhofer IOSB, 76275 Ettlingen, Germany

Keywords: Perceptual grouping, Symmetry, Urban structure recognition

Abstract. Even non-expert human observers sometimes still outperform automatic extraction of man-made objects from remotely sensed data. We conjecture that some of this remarkable capability can be explained by Gestalt mechanisms. Gestalt algebra gives a mathematical structure capturing such part-aggregate relations and the laws to form an aggregate called Gestalt. Primitive Gestalten are obtained from an input image and the space of all possible Gestalt algebra terms is searched for well-assessed instances. This can be a very challenging combinatorial effort. The contribution at hand gives some tools and structures unfolding a finite and comparably small subset of the possible combinations. Yet, the intended Gestalten still are contained and found with high probability and moderate efforts. Experiments are made with images obtained from a virtual globe system, and use the SIFT method for extraction of the primitive Gestalten. Comparison is made with manually extracted ground-truth Gestalten salient to human observers.