Urban Areas Enhancement in Multitemporal SAR RGB Images Using Adaptive Coherence Window and Texture Information

Donato Amitrano, Veronica Belfiore, Francesca Cecinati, Gerardo Di Martino, Antonio Iodice, Pierre Philippe Mathieu, Stefano Medagli, Davod Poreh, Daniele Riccio, Giuseppe Ruello

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)

Abstract

In this paper, we present a technique for improving the representation of built-up features in model-based multitemporal synthetic aperture radar (SAR) RGB composites. The proposed technique exploits the multitemporal adaptive processing (MAP3) framework to generate an a priori information which is used to implement an adaptive selection of the coherence window size. Image texture is used to support the coherence information in case of decorrelation. The coherence information, powered by texture analysis, and combined with backscattering amplitude, provides a unique representation of built-up features. This allows for an immediate detection of urban agglomerates by human operators, and is an advantaged starting point for urban area extraction algorithms.

Original languageEnglish
Article number7471417
Pages (from-to)3740-3752
Number of pages13
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume9
Issue number8
Early online date18 May 2016
DOIs
Publication statusPublished - 1 Aug 2016

Keywords

  • Data representation
  • fuzzy logic
  • multitemporal synthetic aperture radar (SAR)
  • urban areas

ASJC Scopus subject areas

  • Computers in Earth Sciences
  • Atmospheric Science

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