A reconstruction technique, based on the 2-D truncated singular value decomposition, is first proposed to enhance the spatial resolution of radiometer earth observation measurements. The technique is very computer time effective when the kernel is a 2-D tensor product. The key issue regarding the selection of the truncation parameter is addressed by the statistically based generalized cross-validation approach. Experiments undertaken on a data set consisting of both simulated and actual 2-D special sensor microwave imager radiometer measurements show the robustness of the technique against the additive noise and its effectiveness in terms of processing time. A typical 2-D radiometer scene is processed in seconds by a standard PC processor
Two-dimensional TSVD to enhance the spatial resolution of radiometer data
RODRIGUEZ, GIUSEPPE
2014-01-01
Abstract
A reconstruction technique, based on the 2-D truncated singular value decomposition, is first proposed to enhance the spatial resolution of radiometer earth observation measurements. The technique is very computer time effective when the kernel is a 2-D tensor product. The key issue regarding the selection of the truncation parameter is addressed by the statistically based generalized cross-validation approach. Experiments undertaken on a data set consisting of both simulated and actual 2-D special sensor microwave imager radiometer measurements show the robustness of the technique against the additive noise and its effectiveness in terms of processing time. A typical 2-D radiometer scene is processed in seconds by a standard PC processorFile | Dimensione | Formato | |
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