Filtering-Based Endmember Identification Method For Snapshot Spectral Images

In this paper, we propose a new endmember estimation method for snapshot spectral imaging (SSI) systems using Fabry-Perot filters. Indeed, such systems only provide a part of the spectral content of a classical multi- or hyperspectral camera and restoring the full hyperspectral datacube from an SSI matrix is named “demosaicing”. However, it was recently shown that a joint unmixing and demosaicing method allowed a much better unmixing performance than a two-stage approach consisting of a demosaicing step followed by an unmixing one. In this paper, we propose a new approach to estimate endmembers from the SSI image without requiring a demosaicing step. It inverts the Fabry-Perot filters and extends the “pure pixel” framework to the SSI sensor patch level, that we name the “pure patch” assumption. Our experiments show that our proposed scheme significantly outperforms state-of-the-art methods in terms of endmember estimation accuracy.