There has been considerable interest in the application of real-time processing techniques to the problem of hyperspectral scene analysis. Recent satellite and aircraft systems can produce data at a rate far faster than the data can be analyzed by interactive computer procedures. Automated and fast procedures for preparing the data for analyst inspection are required for even laboratory use of the large quantities of data. In addition, there are several real-time applications where the data must be processed as it is being acquired. A typical application is a computing system on-board an airplane for operator analysis of the scene as the hyperspectral sensor collects data. In this paper the possible tradeoffs fore rapid analysis are discussed, including choice of algorithm, possible dimensionality reduction, and reduced display level. A real time anomaly detection processing system based on the N- FINDR algorithm has been designed and implemented for the Night Vision Imaging Spectrometer (NVIS). The N-FINDR algorithm is a linear unmixing based algorithm that automatically finds spectral endmembers. The algorithm works by inflating a simplex inside the data, beginning with a random set of pixels. Once these endmember spectra have been found, the image cube can be unmixed using a least-squares approach into a map of fractional abundances of each endmember material in each pixel. In addition to the N-FINDR algorithm, the real-time processing system performs calibration, bad pixel removal, and display of selected fraction planes. The real-time processor is implemented in a commercial Pentium IV computer.