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.
Donato Amitrano, Francesca Cecinati, Gerardo Di Martino, Antonio Iodice, Pierre-Philippe Mathieu, Daniele Riccio, and Giuseppe Ruello, "An end-user-oriented framework for RGB representation of multitemporal SAR images and visual data mining," Proc. SPIE 10004, Image and Signal Processing for Remote Sensing XXII, 100040Y (Presented at SPIE Remote Sensing: September 28, 2016; Published: 18 October 2016); https://doi.org/10.1117/12.2241257.
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