A Change Validation System for Aerial Images Based on a Probabilistic Latent Variable Model

Change detection is an important part of image interpretation and automated geographical data collection. In this paper, we show a quality control system for the verification of image changes detected by a human operator. The system is based on a probabilistic system that learns the operator behaviour and tests the founded changes. Maximum likelihood estimators for the model are presented and their derivation is shown. Computational results are given with real image data that show the performance of the system.