Logistic regression for detecting changes between databases and remote sensing images
This paper studies database updating using optical and synthetic aperture radar images. Logistic regression is used to model the conditional probability of presence/absence of buildings given features extracted from the images. The logistic regression parameters are estimated using the maximum likelihood method. Binary hypothesis tests are then constructed from these estimates to detect changes between the optical/radar images and the existing database. The estimation and detection algorithms are evaluated using simulated and real data sets.