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;
2014-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
