Least absolute deviation (LAD) image matching

Abstract The robust estimator properties of the L,-norm or least absolute deviation (LAD) is shown to provide better subpixel matching accuracy in the presence of outlier points than the least squares method widely employed for image matching applications. Two LAD algorithms are compared with each other and with the least squares (LS) method and the iteratively reweighted least squares (IRLS) method. Results indicate that the Barrodale-Roberts LAD algorithm can be used advantageously in conjunction with or in place of the IRLS and LS algorithms.