Overview of Passive Optical Multispectral and Hyperspectral Image Simulation Techniques

Abstract

The simulation of optical images can play key roles in the development of new instruments, the quantitative evaluation of algorithms and in the training of both image analysis software and human analysts. Methods for image simulation include surrogate data collections, operations on empirical imagery, statistical generation techniques, and full physical modeling approaches. Each method offers advantages or disadvantages in terms of time, cost, and realism. Current state of the art suggests three-dimensional radiative transfer models capture most of the significant characteristics of real imagery and find valuable use in system development and evaluation programs. Emerging computational power available from multithreading, graphical processing units, and techniques from deep learning will continue to enable even more realistic simulations in the near future.