Push-broom hyperspectral image calibration and enhancement by 2D deconvolution with a variant response function estimate.

Abstract

In this paper, we propose a novel method for spectral and spatial calibration and resolution enhancement of hyperspectral images by a two-step procedure. The spectral and spatial variability of the hyperspectral imaging system response function is characterized by a global parametric model, which is derived from a pair of calibration images corresponding to an exactly defined calibration target and a set of gas-discharge lamps. A 2D Richardson-Lucy deconvolution-based algorithm is used to remove the distortions and enhance the resolution of subsequently acquired hyperspectral images. The results of the characterization and deconvolution process obtained by the proposed method are thoroughly evaluated by an independent set of exactly defined calibration and spectral targets, and compared to the existing state-of-the-art characterization method. The proposed method significantly improves the spectral and spatial coregistration and provides more than five-fold resolution enhancement in the spatial and two-fold resolution enhancement in the spectral domain.