Correction of spectral curvature effects (smile) in Hyperion datasets by Use of derivative calculations and minimum noise fraction (MNF) transform

Various pushbroom imaging spectroscopy systems experience low-frequency array effects that are often referred to as spectral curvature effect or smile/ frown and keystone interferences [1, 2]. The detector elements in a pushbroom system are arranged on a rectilinear grid, therefore dispersing the slit onto the straight rows of detector elements leads to spatial misalignment of the wavelength and bandwidth [3, 4]. Smile may also be a product of aberrations in the collimator and imaging optics [3]. Hyperion hyperspectral sensor on board the EarthObserving-1 (EO-1) spacecraft is a pushbroom imaging spectrometer [5-7]. Throughout the Hyperion operations, shifts of less than 1 nm have been observed in the SWIR wavelengths and 2.6 – 4.25 nm shifts in the VNIR detector wavelengths [8, 9]. Since the smile effect may render spectral absorption positions, the atmospheric correction may be insufficient, leading to a noisy reflectance product [9-11]; as a result, the thematic spectral based products may be erroneous [12] e.g., thematic misclassification of the data (Figure 1). Figure 1: Classification results for a VNIR Hyperion reflectance image of the research site. Figure1 presents Hyperion classification of rock types in the research site. Hyperion distinguished between most of the different rock types, excluding the right hand side of the image, for which only one class was assigned. Hyperion pre-launch smile estimates are inapplicable as the smile changes with time [8]. On the other hand, MNF-1 commonly used as a smile indicator does not