Detector anomaly detection and stripe correction of hyperspectral data

Since SWIR hyperspectral data provides useful information on minerals and soils, the applications to geology, mining and agriculture are expected. In the SWIR region, hyperspectral sensors use mercury cadmium telluride detectors that have more defects and show non-uniform responses to input radiances. Therefore, the pushbroom scanning of hyperspectral sensors causes stripe noises that disturb the minute spectral analysis. This work correct the artifact due to stripe noise at first using the conventional correction method, such as momentum matching. The remaining stripe patterns are corrected using a sparse coding technique, which is examined using real data.