A reconstruction technique, based on the two-dimensional truncated singular value decomposition (TSVD), is first proposed to enhance the spatial resolution of radiometer earth observation (EO) measurements. The technique is very computer-time effective when the kernel is a two-dimensional tensor product. The key issue regarding the selection of the truncation parameter is addressed by the statistically-based Generalized Cross Validation (GCV) approach. Experiments undertaken on a data set consisting of both simulated and actual two-dimensional Special Sensor Microwave Imager (SSM/I) radiometer measurements show the robustness of the technique against the additive noise and its effectiveness in terms of processing time. A typical two-dimensional radiometer scene is processed in seconds by a standard PC processor.

Two-dimensional TSVD to enhance the spatial resolution of radiometer data

NUNZIATA, FERDINANDO;MIGLIACCIO, Maurizio;
2014

Abstract

A reconstruction technique, based on the two-dimensional truncated singular value decomposition (TSVD), is first proposed to enhance the spatial resolution of radiometer earth observation (EO) measurements. The technique is very computer-time effective when the kernel is a two-dimensional tensor product. The key issue regarding the selection of the truncation parameter is addressed by the statistically-based Generalized Cross Validation (GCV) approach. Experiments undertaken on a data set consisting of both simulated and actual two-dimensional Special Sensor Microwave Imager (SSM/I) radiometer measurements show the robustness of the technique against the additive noise and its effectiveness in terms of processing time. A typical two-dimensional radiometer scene is processed in seconds by a standard PC processor.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11367/1647
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