ABSTRACT
This chapter focuses on the use of Image reconstruction algorithms in spectral-spatial imaging. The image-reconstruction algorithms require that the integrated intensity of the projections be the same for all viewing angles. The algorithm that has given the best results to date for spectral-spatial imaging with incomplete data sets is the projection slice algorithm. Angular Iteration Method is an implementation of the general Gerchberg-Papoulis algorithm for spectral extrapolation. The image-reconstruction literature contains a wide variety of algorithms for data with a "missing angle''. The algorithms differ in their requirements for a priori information about the image and in their computational requirements and stability. The utility of other published algorithms for the spectral-spatial imaging problems is difficult to assess based on reported successes with gray-scale images. However, it becomes cumbersome for images with multiple species and would not be appropriate for images with variable linewidths.
