An end-user-oriented framework for RGB representation of multitemporal SAR images and visual data mining

Donato Amitrano; Francesca Cecinati; Gerardo Di Martino; Antonio Iodice; Pierre Philippe Mathieu; Daniele Riccio; Giuseppe Ruello

doi:10.1117/12.2241257

An end-user-oriented framework for RGB representation of multitemporal SAR images and visual data mining

Donato Amitrano, Francesca Cecinati, Gerardo Di Martino, Antonio Iodice, Pierre Philippe Mathieu, Daniele Riccio, Giuseppe Ruello

Department of Architecture & Civil Engineering

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

1 Citation (SciVal)

Abstract

In this paper, we present a new framework for the generation of two new classes of RGB products derived from multitemporal SAR data. The aim of our processing chain is to provide products characterized by a high degree of interpretability (thanks to a consistent rendering of the underlying electromagnetic scattering mechanisms) and by the possibility to be exploited in combination with simple algorithms for information extraction. The physical rationale of the proposed RGB products is presented through examples highlighting their principal properties. Finally, the suitability of these products with applications is demonstrated through two examples dealing with feature extraction and classification activities.

Original language	English
Title of host publication	Proceedings Volume 10004
Subtitle of host publication	Image and Signal Processing for Remote Sensing XXII
Editors	Lorenzo Bruzzone, Francesca Bovolo
Publisher	SPIE
Number of pages	7
Volume	10004
ISBN (Electronic)	9781510604124
DOIs	https://doi.org/10.1117/12.2241257
Publication status	Published - 18 Oct 2016
Event	Image and Signal Processing for Remote Sensing XXII - Edinburgh, UK United Kingdom Duration: 26 Sept 2016 → 28 Sept 2016

Conference

Conference	Image and Signal Processing for Remote Sensing XXII
Country/Territory	UK United Kingdom
City	Edinburgh
Period	26/09/16 → 28/09/16

Keywords

classification
image enhancement
Level-1α products
Level-1β products
multitemporal SAR
self-organizing maps
synthetic aperture radar

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

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10.1117/12.2241257

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Amitrano, D., Cecinati, F., Di Martino, G., Iodice, A., Mathieu, P. P., Riccio, D., & Ruello, G. (2016). An end-user-oriented framework for RGB representation of multitemporal SAR images and visual data mining. In L. Bruzzone, & F. Bovolo (Eds.), Proceedings Volume 10004: Image and Signal Processing for Remote Sensing XXII (Vol. 10004). Article 100040Y SPIE. https://doi.org/10.1117/12.2241257

An end-user-oriented framework for RGB representation of multitemporal SAR images and visual data mining. / Amitrano, Donato; Cecinati, Francesca; Di Martino, Gerardo et al.
Proceedings Volume 10004: Image and Signal Processing for Remote Sensing XXII. ed. / Lorenzo Bruzzone; Francesca Bovolo. Vol. 10004 SPIE, 2016. 100040Y.

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

Amitrano, D, Cecinati, F, Di Martino, G, Iodice, A, Mathieu, PP, Riccio, D & Ruello, G 2016, An end-user-oriented framework for RGB representation of multitemporal SAR images and visual data mining. in L Bruzzone & F Bovolo (eds), Proceedings Volume 10004: Image and Signal Processing for Remote Sensing XXII. vol. 10004, 100040Y, SPIE, Image and Signal Processing for Remote Sensing XXII, Edinburgh, UK United Kingdom, 26/09/16. https://doi.org/10.1117/12.2241257

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An end-user-oriented framework for RGB representation of multitemporal SAR images and visual data mining

Abstract

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Keywords

ASJC Scopus subject areas

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