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We propose a new algorithm, hypothesis-based estimation with regularization (HyBER), to reconstruct and denoise hyperspectral image data without extra statistical assumptions. The hypothesis test selects the best statistical model approximating measurements based on the data only. A regularized maximum log-likelihood estimation method is derived based on the selected model. A spatially dependent w...

Quantitative Reconstruction and Denoising Method HyBER for Hyperspectral Image Data and Its Application to CRISM