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In this paper we apply the recently proposed J-SparseFI data fusion method to the fusion of a low-resolution hyperspectral image and a high-resolution multispectral image. The high correlation of signals in adjacent hyperspectral channels is exploited by assuming signals in different channels are jointly sparse in suitable dictionaries that are created from the multispectral image. First experimental results using airborne HySpex hyperspectral data and synthesized WorldView-2 imagery are presented. [ABSTRACT FROM PUBLISHER]

In this paper, we extend the Sparse Fusion of Images (SparseFI, pronounced “sparsify”) algorithm, proposed by the authors before, to a Jointly Sparse Fusion of Images (J-SparseFI) algorithm by exploiting the possible signal structural correlations between different multispectral channels. The algorithm is evaluated using airborne UltraCam data. The superior performance of the proposed methods has been demonstrated by a statistic assessment. Moreover, first experimental result using airborne HySpex hyperspectral data is presented. [ABSTRACT FROM PUBLISHER]

DLR is operating a generic processing chain for imaging spectrometer data. This includes automatic invocation of system correction, parametric geocoding and atmospheric correction with accompanying quality measurements as well as the archiving of the resulting data products. Further HySpex, a pushbroom scanner, has been purchased in 2011 to be operated from spring 2012. This work describes the steps to be accomplished to incorporate this new sensor into the generic environment. [ABSTRACT FROM PUBLISHER]