Hyperspectral Image Registration and Construction From Irregularly Sampled Data

Abstract: Hyperspectral imaging based on the use of an exponentially variable filter gives the possibility to construct a lightweight hyperspectral sensor. The exponentially variable filter captures the whole spectral range in each image where each column captures a different wavelength. To gather the full spectrum for any given point in the image requires the fusion of several gathered images with movement in between captures. The construction of a hyperspectral cube requires registration of the gathered images. With a lightweight sensor comes the possibility to mount the hyperspectral sensor on an unmanned aerial vehicle to collect aerial footage. This thesis presents a registration algorithm capable of constructing a complete hyperspectral cube of almost any chosen area in the captured region. The thesis presents the result of a construction method using a multi-frame super-resolution algorithm trying to increase the spectral resolution and a spline interpolation method interpolating missing spectral data. The result of an algorithm trying to suggest the optimal spectral and spatial resolution before constructing the hyperspectral cube is also presented. Lastly, the result of an algorithm providing information about the quality of the constructed hyperspectral cube is also presented.