An Optimization Procedure for Robust Regression-Based Pansharpening

Carpentiero, Marco; Vivone, Gemine; Restaino, Rocco; Addesso, P.; Chanussot, Jocelyn

doi:10.1109/tgrs.2022.3179105

Cited by 3 publications

(2 citation statements)

References 57 publications

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“…First, the M k bands are lowpass-filtered with a cutoff frequency 1/R, providing the bands M kL degraded at the resolution of the RE bands. Then, the relationship between the RE band interpolated by R, H i , and M kL is modeled through a multivariate linear regression [31]:…”

Section: Hyper-sharpening Of Sentinel-2 Datamentioning

confidence: 99%

Fusion of VNIR Optical and C-Band Polarimetric SAR Satellite Data for Accurate Detection of Temporal Changes in Vegetated Areas

2023

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In this paper, we propose a processing chain jointly employing Sentinel-1 and Sentinel-2 data, aiming to monitor changes in the status of the vegetation cover by integrating the four 10 m visible and near-infrared (VNIR) bands with the three red-edge (RE) bands of Sentinel-2. The latter approximately span the gap between red and NIR bands (700 nm–800 nm), with bandwidths of 15/20 nm and 20 m pixel spacing. The RE bands are sharpened to 10 m, following the hyper-sharpening protocol, which holds, unlike pansharpening, when the sharpening band is not unique. The resulting 10 m fusion product may be integrated with polarimetric features calculated from the Interferometric Wide (IW) Ground Range Detected (GRD) product of Sentinel-1, available at 10 m pixel spacing, before the fused data are analyzed for change detection. A key point of the proposed scheme is that the fusion of optical and synthetic aperture radar (SAR) data is accomplished at level of change, through modulation of the optical change feature, namely the difference in normalized area over (reflectance) curve (NAOC), calculated from the sharpened RE bands, by the polarimetric SAR change feature, achieved as the temporal ratio of polarimetric features, where the latter is the pixel ratio between the co-polar and the cross-polar channels. Hyper-sharpening of Sentinel-2 RE bands, calculation of NAOC and modulation-based integration of Sentinel-1 polarimetric change features are applied to multitemporal datasets acquired before and after a fire event, over Mount Serra, in Italy. The optical change feature captures variations in the content of chlorophyll. The polarimetric SAR temporal change feature describes depolarization effects and changes in volumetric scattering of canopies. Their fusion shows an increased ability to highlight changes in vegetation status. In a performance comparison achieved by means of receiver operating characteristic (ROC) curves, the proposed change feature-based fusion approach surpasses a traditional area-based approach and the normalized burned ratio (NBR) index, which is widespread in the detection of burnt vegetation.

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Section: Hyper-sharpening Of Sentinel-2 Datamentioning

confidence: 99%

Fusion of VNIR Optical and C-Band Polarimetric SAR Satellite Data for Accurate Detection of Temporal Changes in Vegetated Areas

2023

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“…First, the M k bands are lowpass filtered with cutoff frequency 1/R, thus providing the bands M kL degraded at the resolution of the RE bands. Then, the relationship between the RE band interpolated by R, H i , and M kL , is modeled through a multivariate linear regression: 35,36…”

Section: Hyper-sharpening Of Sentinel-2 Datamentioning

confidence: 99%

Fusion of optical and SAR satellite data for environmental monitoring: assessment of damages and disturbances originated by forest fires

Alparone

Arienzo²,

Garzelli³

et al. 2022

Image and Signal Processing for Remote Sensing XXVIII

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In this paper, we propose a processing chain jointly employing Sentinel-1 and Sentinel-2 data aimed at monitoring changes in the status of the vegetation cover by integrating the four visible and near infrared (VNIR) bands with the three red-edge (RE) bands of Sentinel-2, approximately spanning the gap between Red and NIR bands (700 nm – 800 nm) with bandwidths of 15/20 nm and 20 m pixel spacing. The RE bands will be sharpened to 10 m and the resulting 7-bands, 10 m fusion product will be integrated with polarimetric features calculated from the Interferometric Wide (IW) Ground Range Detected (GRD) product of Sentinel-1, available at 10 m pixel spacing. Key point of the fusion of optical bands is the correction of atmospheric path radiance before fusion is accomplished through modulation of the interpolated band by a sharpening term achieved through the hyper-sharpening paradigm. Whenever surface reflectance data are available, haze estimation and correction can be skipped. Hyper-sharpening of Sentinel-2 multispectral (MS) bands and modulation-based integration of Sentinel-1 polarimetric synthetic aperture radar (SAR) features are applied on a multitemporal dataset acquired before and after a recent fire event.

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