Abstract
The phase map obtained in observation of Mount Fuji presented in Chapter 5 shows the reflection phase modulo 2π. Therefore, the fringe curves are contours showing the geography in the observation area. Given one knows the fact, one can imagine the landscape of Mount Fuji to some extent. Computers can perform a similar processing to yield a height map, which we call a digital elevation map (or digital elevation model: DEM). The process to unwrap the phase image wrapped within –π to π is the phase unwrapping. The phase unwrapping is, however, known as a difficult process for conventional computers because of the existence of phase singular points. In this chapter, first we explain the singular points, which is a serious noise induced in the interferometric observation. Then we present a method to remove the singular points effectively by using a complex-valued neural network, and generate a high-quality DEM with a smaller calculation cost.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Hirose, A. (2012). Removal of Phase Singular Points to Create Digital Elevation Map. In: Complex-Valued Neural Networks. Studies in Computational Intelligence, vol 400. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27632-3_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-27632-3_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27631-6
Online ISBN: 978-3-642-27632-3
eBook Packages: EngineeringEngineering (R0)