The main problem in scene matching is the differences between multi-sensor images, such as resolution difference and gray-level difference, which make it very difficult to register two images. This paper describes the statistic properties and an autocorrelation model of the gray-level difference between these images to attempt to rectify the gray-level of sensed image to solve the problem. It is well known the Gaussian-Markov random process can be acquired from the output of a linear system whose input is Gaussian white noise. Supposing the gray-level difference is an ergodic wide-sense stationary 2D random field with zero mean value in a local region, the autocorrelation model of the gray-level difference is studied to identify a linear system through which the simulated difference distribution is acquired to rectify the gray-level of sensed image. After rectified, the gray-level of sensed image and reference image will be similar so that the registration is much easier. The validity of this method is verified by the experiment results with several pairs of aerial image and satellite image.
"Image gray level rectifying in scene matching", Proc. SPIE 3088, Enhanced and Synthetic Vision 1997, (26 June 1997); doi: 10.1117/12.277239; https://doi.org/10.1117/12.277239