Robust detection of road segments in noisy aerial images

This paper treats the problem of detecting straight or circular pieces of road in noisy aerial images. It first uses a local nonlinear operator to detect pixels whose neighborhoods are line-like, and then applies (robust) estimation techniques to find sets of such pixels that lie on, or near straight or circular loci. An (unbiased) ordinary least squares estimator cannot handle outlying data; on the other hand, conventional robust techniques for fitting circular arcs are severely affected by digitization effects and the fact that road circular segments are typically short and shallow. We therefore introduce an estimator that is both robust and statistically efficient.