In this paper, we introduce a novel approach to enhance the spatial resolution of single-pass microwave data collected by mesoscale sensors. The proposed rationale is based on an Lp -minimization approach with a variable p exponent. The algorithm automatically adapts the p exponent to the region of the image to be reconstructed. This approach allows taking benefit of the advantages of both the regularization in Hilbert ( p=2 ) and Banach ( 1<2 ) spaces. Experiments are undertaken considering the microwave radiometer and refer to both actual and simulated data collected by the special sensor microwave imager (SSM/I). Results demonstrate the benefits of the proposed method in reconstructing abrupt discontinuities and smooth gradients with respect to conventional approaches in Hilbert or Banach spaces.

An Adaptive Lp-Penalization Method to Enhance the Spatial Resolution of Microwave Radiometer Measurements

ALPARONE, MATTEO;Nunziata, Ferdinando;Migliaccio, Maurizio
2019

Abstract

In this paper, we introduce a novel approach to enhance the spatial resolution of single-pass microwave data collected by mesoscale sensors. The proposed rationale is based on an Lp -minimization approach with a variable p exponent. The algorithm automatically adapts the p exponent to the region of the image to be reconstructed. This approach allows taking benefit of the advantages of both the regularization in Hilbert ( p=2 ) and Banach ( 1<2 ) spaces. Experiments are undertaken considering the microwave radiometer and refer to both actual and simulated data collected by the special sensor microwave imager (SSM/I). Results demonstrate the benefits of the proposed method in reconstructing abrupt discontinuities and smooth gradients with respect to conventional approaches in Hilbert or Banach spaces.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11367/76838
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