By utilizing images calculated on-the-fly as a filter improvements in real-time performance of object measurement and feature extraction can be achieved for automated aerial photograph analysis. The process requires the rapid calculation of images from an existing terrain database. The calculated images are then compared to incoming sensor data. The difference between the calculated and sensor image is then utilized as a parallel error signal for updating the state of knowledge of the objects and features measured. The advantage of this image feedback technique is that the calculation of sensor realistic perspective views from parameterized object models is easier than the direct interpretation of complex images. The feedback technique effectively eliminates what is already known from the measurement signal and thereby reduces the amount of data which must be processed by pattern recognition techniques by orders of magnitude. The paper presents the mathematical description of the image feedback technique and estimates update frame rates which can be expected for real time applications. We then discuss the incremental software development approach and the system design we are using for implementing the technique. The state of the current system is presented along with a discussion of experiments and experiences gained in building large-scale high-resolution terrain databases. The paper concludes by defining future research areas that need to be addressed for improving performance and accuracy.