Spectral Cube Reconstruction For a High Resolution Hyperspectral Camera Based on a Linear Variable Filter

摘要

Hyperspectral imaging based on a linear variable filter (LVF) close to the focal plane array (FPA) is an attractive technique since it gives a small, lightweight, and inexpensive sensor. Linear variable techniques can capture the full spectrum within a given spectral range in one image at the same time, but only records one wavelength in each pixel. Reconstruction of a spectrum for a point in the scene requires fusion of spectral information from a large number of registered images. We present a procedure to reconstruct a hyperspectral data cube by registering a large number of overlapping images with spectrally varying content using feature-based registration and transforming them to a joint coordinate system. The accuracy of the registration is evaluated and shown to yield a reconstruction error of less than one pixel.