Lossless compression of hyperspectral images: Look-up tables with varying degrees of confidence

State-of-the-art algorithms LUT and LAIS-LUT, proposed for lossless compression of hyperspectral images, exploit high spectral correlations in these images, and use look-up tables to perform predictions. However, there are cases where their predictions are not accurate. In this work we also use look-up tables, but give these tables different degrees of confidence, based on the local variations of the scaling factor. Our results are highly satisfactory and outperform both LUT and LAIS-LUT methods.