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A sensor-data-based denoising framework for hyperspectral images
2015
Optics Express
Many denoising approaches extend image processing to a hyperspectral cube structure, but do not take into account a sensor model nor the format of the recording. We propose a denoising framework for hyperspectral images that uses sensor data to convert an acquisition to a representation facilitating the noise-estimation, namely the photoncorrected image. This photon corrected image format accounts for the most common noise contributions and is spatially proportional to spectral radiance values.
doi:10.1364/oe.23.001938
pmid:25836066
fatcat:56z6lwohe5f2toymt63oahkr4y