The robust estimator properties of the L(1)-norm or least absolute dev
iation (LAD) is shown to provide better subpixel matching accuracy in
the presence of outlier points than the least squares method widely em
ployed for image matching applications. Two LAD algorithms are compare
d with each other and with the least squares (LS) method and the itera
tively reweighted least squares (IRLS) method. Results indicate that t
he Barrodale-Roberts LAD algorithm can be used advantageously in conju
nction with or in place of the IRLS and LS algorithms.